chore(deps): bump golang.org/x/net

Bumps [golang.org/x/net](https://github.com/golang/net) from 0.0.0-20201110031124-69a78807bb2b to 0.7.0.
- [Release notes](https://github.com/golang/net/releases)
- [Commits](https://github.com/golang/net/commits/v0.7.0)

---
updated-dependencies:
- dependency-name: golang.org/x/net
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>

Dockerfile

@@ -12,6 +12,7 @@ FROM golang:1.15.5
 COPY --from=builder /go/bin/core .
 COPY --from=builder /go/src/db ./db
 COPY --from=builder /go/bin/goose .
+COPY --from=builder /go/src/manifest ./manifest
 
 EXPOSE 8888
 EXPOSE 8887

README.md

@@ -6,12 +6,11 @@
 [![sdk](https://img.shields.io/pypi/v/onepanel-sdk?color=01579b&label=sdk)](https://pypi.org/project/onepanel-sdk/)
 [![docs](https://img.shields.io/github/v/release/onepanelio/core?color=01579b&label=docs)](https://docs.onepanel.io)
 [![issues](https://img.shields.io/github/issues-raw/onepanelio/core?color=01579b&label=issues)](https://github.com/onepanelio/core/issues)
-[![chat](https://img.shields.io/badge/support-slack-01579b)](https://join.slack.com/t/onepanel-ce/shared_invite/zt-eyjnwec0-nLaHhjif9Y~gA05KuX6AUg)
 [![lfai](https://img.shields.io/badge/link-LFAI-01579b)](https://landscape.lfai.foundation/?selected=onepanel)
 [![license](https://img.shields.io/github/license/onepanelio/core?color=01579b)](https://opensource.org/licenses/Apache-2.0)
 
 ## End-to-end computer vision platform
-Label, build, train, tune, deploy and automate, all in one platform that runs on any cloud and on-premises.
+Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
 
 https://user-images.githubusercontent.com/1211823/116489376-afc60000-a849-11eb-8e8b-b0c64c07c144.mp4
 
@@ -21,14 +20,9 @@ https://user-images.githubusercontent.com/1211823/116489376-afc60000-a849-11eb-8
 ## Quick start
 See [quick start guide](https://docs.onepanel.ai/docs/getting-started/quickstart) to get started.
 
-## Online demo
-For a quick look at some features see this shared, read-only [online demo](https://onepanel.typeform.com/to/kQfDX5Vf?product=github).
-
 ## Community
 To submit a feature request, report a bug or documentation issue, please open a GitHub [pull request](https://github.com/onepanelio/core/pulls) or [issue](https://github.com/onepanelio/core/issues).
 
-For help, questions, release announcements and contribution discussions, join us on [Slack](https://join.slack.com/t/onepanel-ce/shared_invite/zt-eyjnwec0-nLaHhjif9Y~gA05KuX6AUg).
-
 ## Contributing
 Onepanel is modular and consists of [multiple repositories](https://docs.onepanel.ai/docs/getting-started/contributing/#project-repositories).
 
@@ -37,12 +31,9 @@ See [contribution guide](https://docs.onepanel.ai/docs/getting-started/contribut
 ## Acknowledgments
 Onepanel seamlessly integrates the following open source projects under the hood:
 
-[Argo](https://github.com/argoproj/argo) | [Couler](https://github.com/couler-proj/couler) | [CVAT](https://github.com/opencv/cvat) | [JupyterLab](https://github.com/jupyterlab/jupyterlab) | [NNI](https://github.com/microsoft/nni)
+[Argo](https://github.com/argoproj/argo-workflows) | [Couler](https://github.com/couler-proj/couler) | [CVAT](https://github.com/opencv/cvat) | [JupyterLab](https://github.com/jupyterlab/jupyterlab) | [NNI](https://github.com/microsoft/nni)
 
 We are grateful for the support these communities provide and do our best to contribute back as much as possible.
 
 ## License
-Onepanel is licensed under [Apache 2.0](https://github.com/onepanelio/core/blob/master/LICENSE).
-
-## Enterprise support
-Need enterprise features and support? Visit our [website](https://www.onepanel.ai/) for more information.
+Onepanel is licensed under [Apache 2.0](https://github.com/onepanelio/core/blob/master/LICENSE).

api/api.swagger.json

@@ -3,7 +3,7 @@
   "info": {
     "title": "Onepanel",
     "description": "Onepanel API",
-    "version": "1.0.0",
+    "version": "1.0.2",
     "contact": {
       "name": "Onepanel project",
       "url": "https://github.com/onepanelio/core"
@@ -677,6 +677,200 @@
         ]
       }
     },
+    "/apis/v1beta1/{namespace}/files/list/{path}": {
+      "get": {
+        "operationId": "ListFiles",
+        "responses": {
+          "200": {
+            "description": "A successful response.",
+            "schema": {
+              "$ref": "#/definitions/ListFilesResponse"
+            }
+          },
+          "default": {
+            "description": "An unexpected error response.",
+            "schema": {
+              "$ref": "#/definitions/google.rpc.Status"
+            }
+          }
+        },
+        "parameters": [
+          {
+            "name": "namespace",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          },
+          {
+            "name": "path",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          },
+          {
+            "name": "page",
+            "in": "query",
+            "required": false,
+            "type": "integer",
+            "format": "int32"
+          },
+          {
+            "name": "perPage",
+            "in": "query",
+            "required": false,
+            "type": "integer",
+            "format": "int32"
+          }
+        ],
+        "tags": [
+          "FileService"
+        ]
+      }
+    },
+    "/apis/v1beta1/{namespace}/files/presigned-url/{key}": {
+      "get": {
+        "operationId": "GetObjectDownloadPresignedURL",
+        "responses": {
+          "200": {
+            "description": "A successful response.",
+            "schema": {
+              "$ref": "#/definitions/GetPresignedUrlResponse"
+            }
+          },
+          "default": {
+            "description": "An unexpected error response.",
+            "schema": {
+              "$ref": "#/definitions/google.rpc.Status"
+            }
+          }
+        },
+        "parameters": [
+          {
+            "name": "namespace",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          },
+          {
+            "name": "key",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          }
+        ],
+        "tags": [
+          "FileService"
+        ]
+      }
+    },
+    "/apis/v1beta1/{namespace}/inferenceservice": {
+      "post": {
+        "operationId": "CreateInferenceService",
+        "responses": {
+          "200": {
+            "description": "A successful response.",
+            "schema": {
+              "$ref": "#/definitions/GetInferenceServiceResponse"
+            }
+          },
+          "default": {
+            "description": "An unexpected error response.",
+            "schema": {
+              "$ref": "#/definitions/google.rpc.Status"
+            }
+          }
+        },
+        "parameters": [
+          {
+            "name": "namespace",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          },
+          {
+            "name": "body",
+            "in": "body",
+            "required": true,
+            "schema": {
+              "$ref": "#/definitions/CreateInferenceServiceRequest"
+            }
+          }
+        ],
+        "tags": [
+          "InferenceService"
+        ]
+      }
+    },
+    "/apis/v1beta1/{namespace}/inferenceservice/{name}": {
+      "get": {
+        "operationId": "GetInferenceService",
+        "responses": {
+          "200": {
+            "description": "A successful response.",
+            "schema": {
+              "$ref": "#/definitions/GetInferenceServiceResponse"
+            }
+          },
+          "default": {
+            "description": "An unexpected error response.",
+            "schema": {
+              "$ref": "#/definitions/google.rpc.Status"
+            }
+          }
+        },
+        "parameters": [
+          {
+            "name": "namespace",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          },
+          {
+            "name": "name",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          }
+        ],
+        "tags": [
+          "InferenceService"
+        ]
+      },
+      "delete": {
+        "operationId": "DeleteInferenceService",
+        "responses": {
+          "200": {
+            "description": "A successful response.",
+            "schema": {
+              "properties": {}
+            }
+          },
+          "default": {
+            "description": "An unexpected error response.",
+            "schema": {
+              "$ref": "#/definitions/google.rpc.Status"
+            }
+          }
+        },
+        "parameters": [
+          {
+            "name": "namespace",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          },
+          {
+            "name": "name",
+            "in": "path",
+            "required": true,
+            "type": "string"
+          }
+        ],
+        "tags": [
+          "InferenceService"
+        ]
+      }
+    },
     "/apis/v1beta1/{namespace}/secrets": {
       "get": {
         "operationId": "ListSecrets",
@@ -1275,48 +1469,6 @@
         ]
       }
     },
-    "/apis/v1beta1/{namespace}/workflow_executions/{uid}/artifacts/{key}": {
-      "get": {
-        "operationId": "GetArtifact",
-        "responses": {
-          "200": {
-            "description": "A successful response.",
-            "schema": {
-              "$ref": "#/definitions/ArtifactResponse"
-            }
-          },
-          "default": {
-            "description": "An unexpected error response.",
-            "schema": {
-              "$ref": "#/definitions/google.rpc.Status"
-            }
-          }
-        },
-        "parameters": [
-          {
-            "name": "namespace",
-            "in": "path",
-            "required": true,
-            "type": "string"
-          },
-          {
-            "name": "uid",
-            "in": "path",
-            "required": true,
-            "type": "string"
-          },
-          {
-            "name": "key",
-            "in": "path",
-            "required": true,
-            "type": "string"
-          }
-        ],
-        "tags": [
-          "WorkflowService"
-        ]
-      }
-    },
     "/apis/v1beta1/{namespace}/workflow_executions/{uid}/cron_start_statistics": {
       "post": {
         "operationId": "CronStartWorkflowExecutionStatistic",
@@ -1361,62 +1513,6 @@
         ]
       }
     },
-    "/apis/v1beta1/{namespace}/workflow_executions/{uid}/files/{path}": {
-      "get": {
-        "operationId": "ListFiles",
-        "responses": {
-          "200": {
-            "description": "A successful response.",
-            "schema": {
-              "$ref": "#/definitions/ListFilesResponse"
-            }
-          },
-          "default": {
-            "description": "An unexpected error response.",
-            "schema": {
-              "$ref": "#/definitions/google.rpc.Status"
-            }
-          }
-        },
-        "parameters": [
-          {
-            "name": "namespace",
-            "in": "path",
-            "required": true,
-            "type": "string"
-          },
-          {
-            "name": "uid",
-            "in": "path",
-            "required": true,
-            "type": "string"
-          },
-          {
-            "name": "path",
-            "in": "path",
-            "required": true,
-            "type": "string"
-          },
-          {
-            "name": "page",
-            "in": "query",
-            "required": false,
-            "type": "integer",
-            "format": "int32"
-          },
-          {
-            "name": "perPage",
-            "in": "query",
-            "required": false,
-            "type": "integer",
-            "format": "int32"
-          }
-        ],
-        "tags": [
-          "WorkflowService"
-        ]
-      }
-    },
     "/apis/v1beta1/{namespace}/workflow_executions/{uid}/metric": {
       "post": {
         "operationId": "AddWorkflowExecutionMetrics",
@@ -3272,12 +3368,40 @@
         }
       }
     },
-    "ArtifactResponse": {
+    "Container": {
       "type": "object",
       "properties": {
-        "data": {
-          "type": "string",
-          "format": "byte"
+        "image": {
+          "type": "string"
+        },
+        "name": {
+          "type": "string"
+        },
+        "env": {
+          "type": "array",
+          "items": {
+            "$ref": "#/definitions/Env"
+          }
+        }
+      }
+    },
+    "CreateInferenceServiceRequest": {
+      "type": "object",
+      "properties": {
+        "namespace": {
+          "type": "string"
+        },
+        "name": {
+          "type": "string"
+        },
+        "defaultTransformerImage": {
+          "type": "string"
+        },
+        "predictor": {
+          "$ref": "#/definitions/InferenceServicePredictor"
+        },
+        "transformer": {
+          "$ref": "#/definitions/InferenceServiceTransformer"
         }
       }
     },
@@ -3326,6 +3450,9 @@
           "items": {
             "$ref": "#/definitions/KeyValue"
           }
+        },
+        "captureNode": {
+          "type": "boolean"
         }
       }
     },
@@ -3380,6 +3507,17 @@
         }
       }
     },
+    "Env": {
+      "type": "object",
+      "properties": {
+        "name": {
+          "type": "string"
+        },
+        "value": {
+          "type": "string"
+        }
+      }
+    },
     "File": {
       "type": "object",
       "properties": {
@@ -3449,6 +3587,23 @@
         }
       }
     },
+    "GetInferenceServiceResponse": {
+      "type": "object",
+      "properties": {
+        "ready": {
+          "type": "boolean"
+        },
+        "conditions": {
+          "type": "array",
+          "items": {
+            "$ref": "#/definitions/InferenceServiceCondition"
+          }
+        },
+        "predictUrl": {
+          "type": "string"
+        }
+      }
+    },
     "GetLabelsResponse": {
       "type": "object",
       "properties": {
@@ -3468,6 +3623,18 @@
         }
       }
     },
+    "GetPresignedUrlResponse": {
+      "type": "object",
+      "properties": {
+        "url": {
+          "type": "string"
+        },
+        "size": {
+          "type": "string",
+          "format": "int64"
+        }
+      }
+    },
     "GetWorkflowExecutionMetricsResponse": {
       "type": "object",
       "properties": {
@@ -3503,6 +3670,72 @@
         }
       }
     },
+    "InferenceServiceCondition": {
+      "type": "object",
+      "properties": {
+        "lastTransitionTime": {
+          "type": "string"
+        },
+        "status": {
+          "type": "string"
+        },
+        "type": {
+          "type": "string"
+        }
+      }
+    },
+    "InferenceServicePredictor": {
+      "type": "object",
+      "properties": {
+        "name": {
+          "type": "string"
+        },
+        "runtimeVersion": {
+          "type": "string"
+        },
+        "storageUri": {
+          "type": "string"
+        },
+        "nodeSelector": {
+          "type": "string"
+        },
+        "minCpu": {
+          "type": "string"
+        },
+        "minMemory": {
+          "type": "string"
+        },
+        "maxCpu": {
+          "type": "string"
+        },
+        "maxMemory": {
+          "type": "string"
+        }
+      }
+    },
+    "InferenceServiceTransformer": {
+      "type": "object",
+      "properties": {
+        "containers": {
+          "type": "array",
+          "items": {
+            "$ref": "#/definitions/Container"
+          }
+        },
+        "minCpu": {
+          "type": "string"
+        },
+        "minMemory": {
+          "type": "string"
+        },
+        "maxCpu": {
+          "type": "string"
+        },
+        "maxMemory": {
+          "type": "string"
+        }
+      }
+    },
     "IsAuthorized": {
       "type": "object",
       "properties": {
@@ -3951,6 +4184,9 @@
       "properties": {
         "name": {
           "type": "string"
+        },
+        "sourceName": {
+          "type": "string"
         }
       }
     },

api/gen/files.pb.go

@@ -0,0 +1,580 @@
+// Code generated by protoc-gen-go. DO NOT EDIT.
+// versions:
+// 	protoc-gen-go v1.25.0
+// 	protoc        v3.14.0
+// source: files.proto
+
+package gen
+
+import (
+	proto "github.com/golang/protobuf/proto"
+	_ "google.golang.org/genproto/googleapis/api/annotations"
+	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
+	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
+	reflect "reflect"
+	sync "sync"
+)
+
+const (
+	// Verify that this generated code is sufficiently up-to-date.
+	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
+	// Verify that runtime/protoimpl is sufficiently up-to-date.
+	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
+)
+
+// This is a compile-time assertion that a sufficiently up-to-date version
+// of the legacy proto package is being used.
+const _ = proto.ProtoPackageIsVersion4
+
+type File struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Path         string `protobuf:"bytes,1,opt,name=path,proto3" json:"path,omitempty"`
+	Name         string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"`
+	Extension    string `protobuf:"bytes,3,opt,name=extension,proto3" json:"extension,omitempty"`
+	Size         int64  `protobuf:"varint,4,opt,name=size,proto3" json:"size,omitempty"`
+	ContentType  string `protobuf:"bytes,5,opt,name=contentType,proto3" json:"contentType,omitempty"`
+	LastModified string `protobuf:"bytes,6,opt,name=lastModified,proto3" json:"lastModified,omitempty"`
+	Directory    bool   `protobuf:"varint,7,opt,name=directory,proto3" json:"directory,omitempty"`
+}
+
+func (x *File) Reset() {
+	*x = File{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_files_proto_msgTypes[0]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *File) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*File) ProtoMessage() {}
+
+func (x *File) ProtoReflect() protoreflect.Message {
+	mi := &file_files_proto_msgTypes[0]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use File.ProtoReflect.Descriptor instead.
+func (*File) Descriptor() ([]byte, []int) {
+	return file_files_proto_rawDescGZIP(), []int{0}
+}
+
+func (x *File) GetPath() string {
+	if x != nil {
+		return x.Path
+	}
+	return ""
+}
+
+func (x *File) GetName() string {
+	if x != nil {
+		return x.Name
+	}
+	return ""
+}
+
+func (x *File) GetExtension() string {
+	if x != nil {
+		return x.Extension
+	}
+	return ""
+}
+
+func (x *File) GetSize() int64 {
+	if x != nil {
+		return x.Size
+	}
+	return 0
+}
+
+func (x *File) GetContentType() string {
+	if x != nil {
+		return x.ContentType
+	}
+	return ""
+}
+
+func (x *File) GetLastModified() string {
+	if x != nil {
+		return x.LastModified
+	}
+	return ""
+}
+
+func (x *File) GetDirectory() bool {
+	if x != nil {
+		return x.Directory
+	}
+	return false
+}
+
+type ListFilesRequest struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Namespace string `protobuf:"bytes,1,opt,name=namespace,proto3" json:"namespace,omitempty"`
+	Path      string `protobuf:"bytes,2,opt,name=path,proto3" json:"path,omitempty"`
+	Page      int32  `protobuf:"varint,3,opt,name=page,proto3" json:"page,omitempty"`
+	PerPage   int32  `protobuf:"varint,4,opt,name=perPage,proto3" json:"perPage,omitempty"`
+}
+
+func (x *ListFilesRequest) Reset() {
+	*x = ListFilesRequest{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_files_proto_msgTypes[1]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *ListFilesRequest) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*ListFilesRequest) ProtoMessage() {}
+
+func (x *ListFilesRequest) ProtoReflect() protoreflect.Message {
+	mi := &file_files_proto_msgTypes[1]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use ListFilesRequest.ProtoReflect.Descriptor instead.
+func (*ListFilesRequest) Descriptor() ([]byte, []int) {
+	return file_files_proto_rawDescGZIP(), []int{1}
+}
+
+func (x *ListFilesRequest) GetNamespace() string {
+	if x != nil {
+		return x.Namespace
+	}
+	return ""
+}
+
+func (x *ListFilesRequest) GetPath() string {
+	if x != nil {
+		return x.Path
+	}
+	return ""
+}
+
+func (x *ListFilesRequest) GetPage() int32 {
+	if x != nil {
+		return x.Page
+	}
+	return 0
+}
+
+func (x *ListFilesRequest) GetPerPage() int32 {
+	if x != nil {
+		return x.PerPage
+	}
+	return 0
+}
+
+type ListFilesResponse struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Count      int32   `protobuf:"varint,1,opt,name=count,proto3" json:"count,omitempty"`
+	TotalCount int32   `protobuf:"varint,2,opt,name=totalCount,proto3" json:"totalCount,omitempty"`
+	Page       int32   `protobuf:"varint,3,opt,name=page,proto3" json:"page,omitempty"`
+	Pages      int32   `protobuf:"varint,4,opt,name=pages,proto3" json:"pages,omitempty"`
+	Files      []*File `protobuf:"bytes,5,rep,name=files,proto3" json:"files,omitempty"`
+	ParentPath string  `protobuf:"bytes,6,opt,name=parentPath,proto3" json:"parentPath,omitempty"`
+}
+
+func (x *ListFilesResponse) Reset() {
+	*x = ListFilesResponse{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_files_proto_msgTypes[2]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *ListFilesResponse) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*ListFilesResponse) ProtoMessage() {}
+
+func (x *ListFilesResponse) ProtoReflect() protoreflect.Message {
+	mi := &file_files_proto_msgTypes[2]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use ListFilesResponse.ProtoReflect.Descriptor instead.
+func (*ListFilesResponse) Descriptor() ([]byte, []int) {
+	return file_files_proto_rawDescGZIP(), []int{2}
+}
+
+func (x *ListFilesResponse) GetCount() int32 {
+	if x != nil {
+		return x.Count
+	}
+	return 0
+}
+
+func (x *ListFilesResponse) GetTotalCount() int32 {
+	if x != nil {
+		return x.TotalCount
+	}
+	return 0
+}
+
+func (x *ListFilesResponse) GetPage() int32 {
+	if x != nil {
+		return x.Page
+	}
+	return 0
+}
+
+func (x *ListFilesResponse) GetPages() int32 {
+	if x != nil {
+		return x.Pages
+	}
+	return 0
+}
+
+func (x *ListFilesResponse) GetFiles() []*File {
+	if x != nil {
+		return x.Files
+	}
+	return nil
+}
+
+func (x *ListFilesResponse) GetParentPath() string {
+	if x != nil {
+		return x.ParentPath
+	}
+	return ""
+}
+
+type GetObjectPresignedUrlRequest struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Namespace string `protobuf:"bytes,1,opt,name=namespace,proto3" json:"namespace,omitempty"`
+	Key       string `protobuf:"bytes,2,opt,name=key,proto3" json:"key,omitempty"`
+}
+
+func (x *GetObjectPresignedUrlRequest) Reset() {
+	*x = GetObjectPresignedUrlRequest{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_files_proto_msgTypes[3]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *GetObjectPresignedUrlRequest) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*GetObjectPresignedUrlRequest) ProtoMessage() {}
+
+func (x *GetObjectPresignedUrlRequest) ProtoReflect() protoreflect.Message {
+	mi := &file_files_proto_msgTypes[3]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use GetObjectPresignedUrlRequest.ProtoReflect.Descriptor instead.
+func (*GetObjectPresignedUrlRequest) Descriptor() ([]byte, []int) {
+	return file_files_proto_rawDescGZIP(), []int{3}
+}
+
+func (x *GetObjectPresignedUrlRequest) GetNamespace() string {
+	if x != nil {
+		return x.Namespace
+	}
+	return ""
+}
+
+func (x *GetObjectPresignedUrlRequest) GetKey() string {
+	if x != nil {
+		return x.Key
+	}
+	return ""
+}
+
+type GetPresignedUrlResponse struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Url  string `protobuf:"bytes,1,opt,name=url,proto3" json:"url,omitempty"`
+	Size int64  `protobuf:"varint,2,opt,name=size,proto3" json:"size,omitempty"`
+}
+
+func (x *GetPresignedUrlResponse) Reset() {
+	*x = GetPresignedUrlResponse{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_files_proto_msgTypes[4]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *GetPresignedUrlResponse) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*GetPresignedUrlResponse) ProtoMessage() {}
+
+func (x *GetPresignedUrlResponse) ProtoReflect() protoreflect.Message {
+	mi := &file_files_proto_msgTypes[4]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use GetPresignedUrlResponse.ProtoReflect.Descriptor instead.
+func (*GetPresignedUrlResponse) Descriptor() ([]byte, []int) {
+	return file_files_proto_rawDescGZIP(), []int{4}
+}
+
+func (x *GetPresignedUrlResponse) GetUrl() string {
+	if x != nil {
+		return x.Url
+	}
+	return ""
+}
+
+func (x *GetPresignedUrlResponse) GetSize() int64 {
+	if x != nil {
+		return x.Size
+	}
+	return 0
+}
+
+var File_files_proto protoreflect.FileDescriptor
+
+var file_files_proto_rawDesc = []byte{
+	0x0a, 0x0b, 0x66, 0x69, 0x6c, 0x65, 0x73, 0x2e, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x12, 0x03, 0x61,
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+	0x62, 0x06, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x33,
+}
+
+var (
+	file_files_proto_rawDescOnce sync.Once
+	file_files_proto_rawDescData = file_files_proto_rawDesc
+)
+
+func file_files_proto_rawDescGZIP() []byte {
+	file_files_proto_rawDescOnce.Do(func() {
+		file_files_proto_rawDescData = protoimpl.X.CompressGZIP(file_files_proto_rawDescData)
+	})
+	return file_files_proto_rawDescData
+}
+
+var file_files_proto_msgTypes = make([]protoimpl.MessageInfo, 5)
+var file_files_proto_goTypes = []interface{}{
+	(*File)(nil),                         // 0: api.File
+	(*ListFilesRequest)(nil),             // 1: api.ListFilesRequest
+	(*ListFilesResponse)(nil),            // 2: api.ListFilesResponse
+	(*GetObjectPresignedUrlRequest)(nil), // 3: api.GetObjectPresignedUrlRequest
+	(*GetPresignedUrlResponse)(nil),      // 4: api.GetPresignedUrlResponse
+}
+var file_files_proto_depIdxs = []int32{
+	0, // 0: api.ListFilesResponse.files:type_name -> api.File
+	3, // 1: api.FileService.GetObjectDownloadPresignedURL:input_type -> api.GetObjectPresignedUrlRequest
+	1, // 2: api.FileService.ListFiles:input_type -> api.ListFilesRequest
+	4, // 3: api.FileService.GetObjectDownloadPresignedURL:output_type -> api.GetPresignedUrlResponse
+	2, // 4: api.FileService.ListFiles:output_type -> api.ListFilesResponse
+	3, // [3:5] is the sub-list for method output_type
+	1, // [1:3] is the sub-list for method input_type
+	1, // [1:1] is the sub-list for extension type_name
+	1, // [1:1] is the sub-list for extension extendee
+	0, // [0:1] is the sub-list for field type_name
+}
+
+func init() { file_files_proto_init() }
+func file_files_proto_init() {
+	if File_files_proto != nil {
+		return
+	}
+	if !protoimpl.UnsafeEnabled {
+		file_files_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*File); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_files_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*ListFilesRequest); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_files_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*ListFilesResponse); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_files_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*GetObjectPresignedUrlRequest); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_files_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*GetPresignedUrlResponse); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+	}
+	type x struct{}
+	out := protoimpl.TypeBuilder{
+		File: protoimpl.DescBuilder{
+			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
+			RawDescriptor: file_files_proto_rawDesc,
+			NumEnums:      0,
+			NumMessages:   5,
+			NumExtensions: 0,
+			NumServices:   1,
+		},
+		GoTypes:           file_files_proto_goTypes,
+		DependencyIndexes: file_files_proto_depIdxs,
+		MessageInfos:      file_files_proto_msgTypes,
+	}.Build()
+	File_files_proto = out.File
+	file_files_proto_rawDesc = nil
+	file_files_proto_goTypes = nil
+	file_files_proto_depIdxs = nil
+}

api/gen/files.pb.gw.go

@@ -0,0 +1,342 @@
+// Code generated by protoc-gen-grpc-gateway. DO NOT EDIT.
+// source: files.proto
+
+/*
+Package gen is a reverse proxy.
+
+It translates gRPC into RESTful JSON APIs.
+*/
+package gen
+
+import (
+	"context"
+	"io"
+	"net/http"
+
+	"github.com/grpc-ecosystem/grpc-gateway/v2/runtime"
+	"github.com/grpc-ecosystem/grpc-gateway/v2/utilities"
+	"google.golang.org/grpc"
+	"google.golang.org/grpc/codes"
+	"google.golang.org/grpc/grpclog"
+	"google.golang.org/grpc/metadata"
+	"google.golang.org/grpc/status"
+	"google.golang.org/protobuf/proto"
+)
+
+// Suppress "imported and not used" errors
+var _ codes.Code
+var _ io.Reader
+var _ status.Status
+var _ = runtime.String
+var _ = utilities.NewDoubleArray
+var _ = metadata.Join
+
+func request_FileService_GetObjectDownloadPresignedURL_0(ctx context.Context, marshaler runtime.Marshaler, client FileServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq GetObjectPresignedUrlRequest
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["key"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "key")
+	}
+
+	protoReq.Key, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "key", err)
+	}
+
+	msg, err := client.GetObjectDownloadPresignedURL(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
+	return msg, metadata, err
+
+}
+
+func local_request_FileService_GetObjectDownloadPresignedURL_0(ctx context.Context, marshaler runtime.Marshaler, server FileServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq GetObjectPresignedUrlRequest
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["key"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "key")
+	}
+
+	protoReq.Key, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "key", err)
+	}
+
+	msg, err := server.GetObjectDownloadPresignedURL(ctx, &protoReq)
+	return msg, metadata, err
+
+}
+
+var (
+	filter_FileService_ListFiles_0 = &utilities.DoubleArray{Encoding: map[string]int{"namespace": 0, "path": 1}, Base: []int{1, 1, 2, 0, 0}, Check: []int{0, 1, 1, 2, 3}}
+)
+
+func request_FileService_ListFiles_0(ctx context.Context, marshaler runtime.Marshaler, client FileServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq ListFilesRequest
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["path"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "path")
+	}
+
+	protoReq.Path, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "path", err)
+	}
+
+	if err := req.ParseForm(); err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
+	}
+	if err := runtime.PopulateQueryParameters(&protoReq, req.Form, filter_FileService_ListFiles_0); err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
+	}
+
+	msg, err := client.ListFiles(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
+	return msg, metadata, err
+
+}
+
+func local_request_FileService_ListFiles_0(ctx context.Context, marshaler runtime.Marshaler, server FileServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq ListFilesRequest
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["path"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "path")
+	}
+
+	protoReq.Path, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "path", err)
+	}
+
+	if err := req.ParseForm(); err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
+	}
+	if err := runtime.PopulateQueryParameters(&protoReq, req.Form, filter_FileService_ListFiles_0); err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
+	}
+
+	msg, err := server.ListFiles(ctx, &protoReq)
+	return msg, metadata, err
+
+}
+
+// RegisterFileServiceHandlerServer registers the http handlers for service FileService to "mux".
+// UnaryRPC     :call FileServiceServer directly.
+// StreamingRPC :currently unsupported pending https://github.com/grpc/grpc-go/issues/906.
+// Note that using this registration option will cause many gRPC library features to stop working. Consider using RegisterFileServiceHandlerFromEndpoint instead.
+func RegisterFileServiceHandlerServer(ctx context.Context, mux *runtime.ServeMux, server FileServiceServer) error {
+
+	mux.Handle("GET", pattern_FileService_GetObjectDownloadPresignedURL_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		var stream runtime.ServerTransportStream
+		ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.FileService/GetObjectDownloadPresignedURL")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := local_request_FileService_GetObjectDownloadPresignedURL_0(rctx, inboundMarshaler, server, req, pathParams)
+		md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_FileService_GetObjectDownloadPresignedURL_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	mux.Handle("GET", pattern_FileService_ListFiles_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		var stream runtime.ServerTransportStream
+		ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.FileService/ListFiles")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := local_request_FileService_ListFiles_0(rctx, inboundMarshaler, server, req, pathParams)
+		md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_FileService_ListFiles_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	return nil
+}
+
+// RegisterFileServiceHandlerFromEndpoint is same as RegisterFileServiceHandler but
+// automatically dials to "endpoint" and closes the connection when "ctx" gets done.
+func RegisterFileServiceHandlerFromEndpoint(ctx context.Context, mux *runtime.ServeMux, endpoint string, opts []grpc.DialOption) (err error) {
+	conn, err := grpc.Dial(endpoint, opts...)
+	if err != nil {
+		return err
+	}
+	defer func() {
+		if err != nil {
+			if cerr := conn.Close(); cerr != nil {
+				grpclog.Infof("Failed to close conn to %s: %v", endpoint, cerr)
+			}
+			return
+		}
+		go func() {
+			<-ctx.Done()
+			if cerr := conn.Close(); cerr != nil {
+				grpclog.Infof("Failed to close conn to %s: %v", endpoint, cerr)
+			}
+		}()
+	}()
+
+	return RegisterFileServiceHandler(ctx, mux, conn)
+}
+
+// RegisterFileServiceHandler registers the http handlers for service FileService to "mux".
+// The handlers forward requests to the grpc endpoint over "conn".
+func RegisterFileServiceHandler(ctx context.Context, mux *runtime.ServeMux, conn *grpc.ClientConn) error {
+	return RegisterFileServiceHandlerClient(ctx, mux, NewFileServiceClient(conn))
+}
+
+// RegisterFileServiceHandlerClient registers the http handlers for service FileService
+// to "mux". The handlers forward requests to the grpc endpoint over the given implementation of "FileServiceClient".
+// Note: the gRPC framework executes interceptors within the gRPC handler. If the passed in "FileServiceClient"
+// doesn't go through the normal gRPC flow (creating a gRPC client etc.) then it will be up to the passed in
+// "FileServiceClient" to call the correct interceptors.
+func RegisterFileServiceHandlerClient(ctx context.Context, mux *runtime.ServeMux, client FileServiceClient) error {
+
+	mux.Handle("GET", pattern_FileService_GetObjectDownloadPresignedURL_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.FileService/GetObjectDownloadPresignedURL")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := request_FileService_GetObjectDownloadPresignedURL_0(rctx, inboundMarshaler, client, req, pathParams)
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_FileService_GetObjectDownloadPresignedURL_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	mux.Handle("GET", pattern_FileService_ListFiles_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.FileService/ListFiles")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := request_FileService_ListFiles_0(rctx, inboundMarshaler, client, req, pathParams)
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_FileService_ListFiles_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	return nil
+}
+
+var (
+	pattern_FileService_GetObjectDownloadPresignedURL_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 2, 4, 3, 0, 4, 1, 5, 5}, []string{"apis", "v1beta1", "namespace", "files", "presigned-url", "key"}, ""))
+
+	pattern_FileService_ListFiles_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 2, 4, 3, 0, 4, 1, 5, 5}, []string{"apis", "v1beta1", "namespace", "files", "list", "path"}, ""))
+)
+
+var (
+	forward_FileService_GetObjectDownloadPresignedURL_0 = runtime.ForwardResponseMessage
+
+	forward_FileService_ListFiles_0 = runtime.ForwardResponseMessage
+)

api/gen/files_grpc.pb.go

@@ -0,0 +1,133 @@
+// Code generated by protoc-gen-go-grpc. DO NOT EDIT.
+
+package gen
+
+import (
+	context "context"
+	grpc "google.golang.org/grpc"
+	codes "google.golang.org/grpc/codes"
+	status "google.golang.org/grpc/status"
+)
+
+// This is a compile-time assertion to ensure that this generated file
+// is compatible with the grpc package it is being compiled against.
+const _ = grpc.SupportPackageIsVersion7
+
+// FileServiceClient is the client API for FileService service.
+//
+// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream.
+type FileServiceClient interface {
+	GetObjectDownloadPresignedURL(ctx context.Context, in *GetObjectPresignedUrlRequest, opts ...grpc.CallOption) (*GetPresignedUrlResponse, error)
+	ListFiles(ctx context.Context, in *ListFilesRequest, opts ...grpc.CallOption) (*ListFilesResponse, error)
+}
+
+type fileServiceClient struct {
+	cc grpc.ClientConnInterface
+}
+
+func NewFileServiceClient(cc grpc.ClientConnInterface) FileServiceClient {
+	return &fileServiceClient{cc}
+}
+
+func (c *fileServiceClient) GetObjectDownloadPresignedURL(ctx context.Context, in *GetObjectPresignedUrlRequest, opts ...grpc.CallOption) (*GetPresignedUrlResponse, error) {
+	out := new(GetPresignedUrlResponse)
+	err := c.cc.Invoke(ctx, "/api.FileService/GetObjectDownloadPresignedURL", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *fileServiceClient) ListFiles(ctx context.Context, in *ListFilesRequest, opts ...grpc.CallOption) (*ListFilesResponse, error) {
+	out := new(ListFilesResponse)
+	err := c.cc.Invoke(ctx, "/api.FileService/ListFiles", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+// FileServiceServer is the server API for FileService service.
+// All implementations must embed UnimplementedFileServiceServer
+// for forward compatibility
+type FileServiceServer interface {
+	GetObjectDownloadPresignedURL(context.Context, *GetObjectPresignedUrlRequest) (*GetPresignedUrlResponse, error)
+	ListFiles(context.Context, *ListFilesRequest) (*ListFilesResponse, error)
+	mustEmbedUnimplementedFileServiceServer()
+}
+
+// UnimplementedFileServiceServer must be embedded to have forward compatible implementations.
+type UnimplementedFileServiceServer struct {
+}
+
+func (UnimplementedFileServiceServer) GetObjectDownloadPresignedURL(context.Context, *GetObjectPresignedUrlRequest) (*GetPresignedUrlResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method GetObjectDownloadPresignedURL not implemented")
+}
+func (UnimplementedFileServiceServer) ListFiles(context.Context, *ListFilesRequest) (*ListFilesResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method ListFiles not implemented")
+}
+func (UnimplementedFileServiceServer) mustEmbedUnimplementedFileServiceServer() {}
+
+// UnsafeFileServiceServer may be embedded to opt out of forward compatibility for this service.
+// Use of this interface is not recommended, as added methods to FileServiceServer will
+// result in compilation errors.
+type UnsafeFileServiceServer interface {
+	mustEmbedUnimplementedFileServiceServer()
+}
+
+func RegisterFileServiceServer(s grpc.ServiceRegistrar, srv FileServiceServer) {
+	s.RegisterService(&_FileService_serviceDesc, srv)
+}
+
+func _FileService_GetObjectDownloadPresignedURL_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(GetObjectPresignedUrlRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(FileServiceServer).GetObjectDownloadPresignedURL(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/api.FileService/GetObjectDownloadPresignedURL",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(FileServiceServer).GetObjectDownloadPresignedURL(ctx, req.(*GetObjectPresignedUrlRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _FileService_ListFiles_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(ListFilesRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(FileServiceServer).ListFiles(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/api.FileService/ListFiles",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(FileServiceServer).ListFiles(ctx, req.(*ListFilesRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+var _FileService_serviceDesc = grpc.ServiceDesc{
+	ServiceName: "api.FileService",
+	HandlerType: (*FileServiceServer)(nil),
+	Methods: []grpc.MethodDesc{
+		{
+			MethodName: "GetObjectDownloadPresignedURL",
+			Handler:    _FileService_GetObjectDownloadPresignedURL_Handler,
+		},
+		{
+			MethodName: "ListFiles",
+			Handler:    _FileService_ListFiles_Handler,
+		},
+	},
+	Streams:  []grpc.StreamDesc{},
+	Metadata: "files.proto",
+}

api/gen/inference_service.pb.go

@@ -0,0 +1,999 @@
+// Code generated by protoc-gen-go. DO NOT EDIT.
+// versions:
+// 	protoc-gen-go v1.25.0
+// 	protoc        v3.14.0
+// source: inference_service.proto
+
+package gen
+
+import (
+	proto "github.com/golang/protobuf/proto"
+	_ "google.golang.org/genproto/googleapis/api/annotations"
+	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
+	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
+	emptypb "google.golang.org/protobuf/types/known/emptypb"
+	reflect "reflect"
+	sync "sync"
+)
+
+const (
+	// Verify that this generated code is sufficiently up-to-date.
+	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
+	// Verify that runtime/protoimpl is sufficiently up-to-date.
+	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
+)
+
+// This is a compile-time assertion that a sufficiently up-to-date version
+// of the legacy proto package is being used.
+const _ = proto.ProtoPackageIsVersion4
+
+type InferenceServiceIdentifier struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Namespace string `protobuf:"bytes,1,opt,name=namespace,proto3" json:"namespace,omitempty"`
+	Name      string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"`
+}
+
+func (x *InferenceServiceIdentifier) Reset() {
+	*x = InferenceServiceIdentifier{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[0]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *InferenceServiceIdentifier) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*InferenceServiceIdentifier) ProtoMessage() {}
+
+func (x *InferenceServiceIdentifier) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[0]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use InferenceServiceIdentifier.ProtoReflect.Descriptor instead.
+func (*InferenceServiceIdentifier) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{0}
+}
+
+func (x *InferenceServiceIdentifier) GetNamespace() string {
+	if x != nil {
+		return x.Namespace
+	}
+	return ""
+}
+
+func (x *InferenceServiceIdentifier) GetName() string {
+	if x != nil {
+		return x.Name
+	}
+	return ""
+}
+
+type Env struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Name  string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
+	Value string `protobuf:"bytes,2,opt,name=value,proto3" json:"value,omitempty"`
+}
+
+func (x *Env) Reset() {
+	*x = Env{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[1]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *Env) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*Env) ProtoMessage() {}
+
+func (x *Env) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[1]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use Env.ProtoReflect.Descriptor instead.
+func (*Env) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{1}
+}
+
+func (x *Env) GetName() string {
+	if x != nil {
+		return x.Name
+	}
+	return ""
+}
+
+func (x *Env) GetValue() string {
+	if x != nil {
+		return x.Value
+	}
+	return ""
+}
+
+type Container struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Image string `protobuf:"bytes,1,opt,name=image,proto3" json:"image,omitempty"`
+	Name  string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"`
+	Env   []*Env `protobuf:"bytes,3,rep,name=env,proto3" json:"env,omitempty"`
+}
+
+func (x *Container) Reset() {
+	*x = Container{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[2]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *Container) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*Container) ProtoMessage() {}
+
+func (x *Container) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[2]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use Container.ProtoReflect.Descriptor instead.
+func (*Container) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{2}
+}
+
+func (x *Container) GetImage() string {
+	if x != nil {
+		return x.Image
+	}
+	return ""
+}
+
+func (x *Container) GetName() string {
+	if x != nil {
+		return x.Name
+	}
+	return ""
+}
+
+func (x *Container) GetEnv() []*Env {
+	if x != nil {
+		return x.Env
+	}
+	return nil
+}
+
+type InferenceServiceTransformer struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Containers []*Container `protobuf:"bytes,1,rep,name=containers,proto3" json:"containers,omitempty"`
+	MinCpu     string       `protobuf:"bytes,2,opt,name=minCpu,proto3" json:"minCpu,omitempty"`
+	MinMemory  string       `protobuf:"bytes,3,opt,name=minMemory,proto3" json:"minMemory,omitempty"`
+	MaxCpu     string       `protobuf:"bytes,4,opt,name=maxCpu,proto3" json:"maxCpu,omitempty"`
+	MaxMemory  string       `protobuf:"bytes,5,opt,name=maxMemory,proto3" json:"maxMemory,omitempty"`
+}
+
+func (x *InferenceServiceTransformer) Reset() {
+	*x = InferenceServiceTransformer{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[3]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *InferenceServiceTransformer) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*InferenceServiceTransformer) ProtoMessage() {}
+
+func (x *InferenceServiceTransformer) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[3]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use InferenceServiceTransformer.ProtoReflect.Descriptor instead.
+func (*InferenceServiceTransformer) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{3}
+}
+
+func (x *InferenceServiceTransformer) GetContainers() []*Container {
+	if x != nil {
+		return x.Containers
+	}
+	return nil
+}
+
+func (x *InferenceServiceTransformer) GetMinCpu() string {
+	if x != nil {
+		return x.MinCpu
+	}
+	return ""
+}
+
+func (x *InferenceServiceTransformer) GetMinMemory() string {
+	if x != nil {
+		return x.MinMemory
+	}
+	return ""
+}
+
+func (x *InferenceServiceTransformer) GetMaxCpu() string {
+	if x != nil {
+		return x.MaxCpu
+	}
+	return ""
+}
+
+func (x *InferenceServiceTransformer) GetMaxMemory() string {
+	if x != nil {
+		return x.MaxMemory
+	}
+	return ""
+}
+
+type InferenceServicePredictor struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Name           string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
+	RuntimeVersion string `protobuf:"bytes,2,opt,name=runtimeVersion,proto3" json:"runtimeVersion,omitempty"`
+	StorageUri     string `protobuf:"bytes,3,opt,name=storageUri,proto3" json:"storageUri,omitempty"`
+	NodeSelector   string `protobuf:"bytes,4,opt,name=nodeSelector,proto3" json:"nodeSelector,omitempty"`
+	MinCpu         string `protobuf:"bytes,5,opt,name=minCpu,proto3" json:"minCpu,omitempty"`
+	MinMemory      string `protobuf:"bytes,6,opt,name=minMemory,proto3" json:"minMemory,omitempty"`
+	MaxCpu         string `protobuf:"bytes,7,opt,name=maxCpu,proto3" json:"maxCpu,omitempty"`
+	MaxMemory      string `protobuf:"bytes,8,opt,name=maxMemory,proto3" json:"maxMemory,omitempty"`
+}
+
+func (x *InferenceServicePredictor) Reset() {
+	*x = InferenceServicePredictor{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[4]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *InferenceServicePredictor) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*InferenceServicePredictor) ProtoMessage() {}
+
+func (x *InferenceServicePredictor) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[4]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use InferenceServicePredictor.ProtoReflect.Descriptor instead.
+func (*InferenceServicePredictor) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{4}
+}
+
+func (x *InferenceServicePredictor) GetName() string {
+	if x != nil {
+		return x.Name
+	}
+	return ""
+}
+
+func (x *InferenceServicePredictor) GetRuntimeVersion() string {
+	if x != nil {
+		return x.RuntimeVersion
+	}
+	return ""
+}
+
+func (x *InferenceServicePredictor) GetStorageUri() string {
+	if x != nil {
+		return x.StorageUri
+	}
+	return ""
+}
+
+func (x *InferenceServicePredictor) GetNodeSelector() string {
+	if x != nil {
+		return x.NodeSelector
+	}
+	return ""
+}
+
+func (x *InferenceServicePredictor) GetMinCpu() string {
+	if x != nil {
+		return x.MinCpu
+	}
+	return ""
+}
+
+func (x *InferenceServicePredictor) GetMinMemory() string {
+	if x != nil {
+		return x.MinMemory
+	}
+	return ""
+}
+
+func (x *InferenceServicePredictor) GetMaxCpu() string {
+	if x != nil {
+		return x.MaxCpu
+	}
+	return ""
+}
+
+func (x *InferenceServicePredictor) GetMaxMemory() string {
+	if x != nil {
+		return x.MaxMemory
+	}
+	return ""
+}
+
+type CreateInferenceServiceRequest struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Namespace               string                       `protobuf:"bytes,1,opt,name=namespace,proto3" json:"namespace,omitempty"`
+	Name                    string                       `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"`
+	DefaultTransformerImage string                       `protobuf:"bytes,3,opt,name=defaultTransformerImage,proto3" json:"defaultTransformerImage,omitempty"`
+	Predictor               *InferenceServicePredictor   `protobuf:"bytes,4,opt,name=predictor,proto3" json:"predictor,omitempty"`
+	Transformer             *InferenceServiceTransformer `protobuf:"bytes,5,opt,name=transformer,proto3" json:"transformer,omitempty"`
+}
+
+func (x *CreateInferenceServiceRequest) Reset() {
+	*x = CreateInferenceServiceRequest{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[5]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *CreateInferenceServiceRequest) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*CreateInferenceServiceRequest) ProtoMessage() {}
+
+func (x *CreateInferenceServiceRequest) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[5]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use CreateInferenceServiceRequest.ProtoReflect.Descriptor instead.
+func (*CreateInferenceServiceRequest) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{5}
+}
+
+func (x *CreateInferenceServiceRequest) GetNamespace() string {
+	if x != nil {
+		return x.Namespace
+	}
+	return ""
+}
+
+func (x *CreateInferenceServiceRequest) GetName() string {
+	if x != nil {
+		return x.Name
+	}
+	return ""
+}
+
+func (x *CreateInferenceServiceRequest) GetDefaultTransformerImage() string {
+	if x != nil {
+		return x.DefaultTransformerImage
+	}
+	return ""
+}
+
+func (x *CreateInferenceServiceRequest) GetPredictor() *InferenceServicePredictor {
+	if x != nil {
+		return x.Predictor
+	}
+	return nil
+}
+
+func (x *CreateInferenceServiceRequest) GetTransformer() *InferenceServiceTransformer {
+	if x != nil {
+		return x.Transformer
+	}
+	return nil
+}
+
+type DeployModelResponse struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Status string `protobuf:"bytes,1,opt,name=status,proto3" json:"status,omitempty"`
+}
+
+func (x *DeployModelResponse) Reset() {
+	*x = DeployModelResponse{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[6]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *DeployModelResponse) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*DeployModelResponse) ProtoMessage() {}
+
+func (x *DeployModelResponse) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[6]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use DeployModelResponse.ProtoReflect.Descriptor instead.
+func (*DeployModelResponse) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{6}
+}
+
+func (x *DeployModelResponse) GetStatus() string {
+	if x != nil {
+		return x.Status
+	}
+	return ""
+}
+
+type InferenceServiceCondition struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	LastTransitionTime string `protobuf:"bytes,1,opt,name=lastTransitionTime,proto3" json:"lastTransitionTime,omitempty"`
+	Status             string `protobuf:"bytes,2,opt,name=status,proto3" json:"status,omitempty"`
+	Type               string `protobuf:"bytes,3,opt,name=type,proto3" json:"type,omitempty"`
+}
+
+func (x *InferenceServiceCondition) Reset() {
+	*x = InferenceServiceCondition{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[7]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *InferenceServiceCondition) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*InferenceServiceCondition) ProtoMessage() {}
+
+func (x *InferenceServiceCondition) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[7]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use InferenceServiceCondition.ProtoReflect.Descriptor instead.
+func (*InferenceServiceCondition) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{7}
+}
+
+func (x *InferenceServiceCondition) GetLastTransitionTime() string {
+	if x != nil {
+		return x.LastTransitionTime
+	}
+	return ""
+}
+
+func (x *InferenceServiceCondition) GetStatus() string {
+	if x != nil {
+		return x.Status
+	}
+	return ""
+}
+
+func (x *InferenceServiceCondition) GetType() string {
+	if x != nil {
+		return x.Type
+	}
+	return ""
+}
+
+type GetInferenceServiceResponse struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Ready      bool                         `protobuf:"varint,1,opt,name=ready,proto3" json:"ready,omitempty"`
+	Conditions []*InferenceServiceCondition `protobuf:"bytes,2,rep,name=conditions,proto3" json:"conditions,omitempty"`
+	PredictUrl string                       `protobuf:"bytes,3,opt,name=predictUrl,proto3" json:"predictUrl,omitempty"`
+}
+
+func (x *GetInferenceServiceResponse) Reset() {
+	*x = GetInferenceServiceResponse{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[8]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *GetInferenceServiceResponse) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*GetInferenceServiceResponse) ProtoMessage() {}
+
+func (x *GetInferenceServiceResponse) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[8]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use GetInferenceServiceResponse.ProtoReflect.Descriptor instead.
+func (*GetInferenceServiceResponse) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{8}
+}
+
+func (x *GetInferenceServiceResponse) GetReady() bool {
+	if x != nil {
+		return x.Ready
+	}
+	return false
+}
+
+func (x *GetInferenceServiceResponse) GetConditions() []*InferenceServiceCondition {
+	if x != nil {
+		return x.Conditions
+	}
+	return nil
+}
+
+func (x *GetInferenceServiceResponse) GetPredictUrl() string {
+	if x != nil {
+		return x.PredictUrl
+	}
+	return ""
+}
+
+type InferenceServiceEndpoints struct {
+	state         protoimpl.MessageState
+	sizeCache     protoimpl.SizeCache
+	unknownFields protoimpl.UnknownFields
+
+	Predict string `protobuf:"bytes,1,opt,name=predict,proto3" json:"predict,omitempty"`
+}
+
+func (x *InferenceServiceEndpoints) Reset() {
+	*x = InferenceServiceEndpoints{}
+	if protoimpl.UnsafeEnabled {
+		mi := &file_inference_service_proto_msgTypes[9]
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		ms.StoreMessageInfo(mi)
+	}
+}
+
+func (x *InferenceServiceEndpoints) String() string {
+	return protoimpl.X.MessageStringOf(x)
+}
+
+func (*InferenceServiceEndpoints) ProtoMessage() {}
+
+func (x *InferenceServiceEndpoints) ProtoReflect() protoreflect.Message {
+	mi := &file_inference_service_proto_msgTypes[9]
+	if protoimpl.UnsafeEnabled && x != nil {
+		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
+		if ms.LoadMessageInfo() == nil {
+			ms.StoreMessageInfo(mi)
+		}
+		return ms
+	}
+	return mi.MessageOf(x)
+}
+
+// Deprecated: Use InferenceServiceEndpoints.ProtoReflect.Descriptor instead.
+func (*InferenceServiceEndpoints) Descriptor() ([]byte, []int) {
+	return file_inference_service_proto_rawDescGZIP(), []int{9}
+}
+
+func (x *InferenceServiceEndpoints) GetPredict() string {
+	if x != nil {
+		return x.Predict
+	}
+	return ""
+}
+
+var File_inference_service_proto protoreflect.FileDescriptor
+
+var file_inference_service_proto_rawDesc = []byte{
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+	0x62, 0x06, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x33,
+}
+
+var (
+	file_inference_service_proto_rawDescOnce sync.Once
+	file_inference_service_proto_rawDescData = file_inference_service_proto_rawDesc
+)
+
+func file_inference_service_proto_rawDescGZIP() []byte {
+	file_inference_service_proto_rawDescOnce.Do(func() {
+		file_inference_service_proto_rawDescData = protoimpl.X.CompressGZIP(file_inference_service_proto_rawDescData)
+	})
+	return file_inference_service_proto_rawDescData
+}
+
+var file_inference_service_proto_msgTypes = make([]protoimpl.MessageInfo, 10)
+var file_inference_service_proto_goTypes = []interface{}{
+	(*InferenceServiceIdentifier)(nil),    // 0: api.InferenceServiceIdentifier
+	(*Env)(nil),                           // 1: api.Env
+	(*Container)(nil),                     // 2: api.Container
+	(*InferenceServiceTransformer)(nil),   // 3: api.InferenceServiceTransformer
+	(*InferenceServicePredictor)(nil),     // 4: api.InferenceServicePredictor
+	(*CreateInferenceServiceRequest)(nil), // 5: api.CreateInferenceServiceRequest
+	(*DeployModelResponse)(nil),           // 6: api.DeployModelResponse
+	(*InferenceServiceCondition)(nil),     // 7: api.InferenceServiceCondition
+	(*GetInferenceServiceResponse)(nil),   // 8: api.GetInferenceServiceResponse
+	(*InferenceServiceEndpoints)(nil),     // 9: api.InferenceServiceEndpoints
+	(*emptypb.Empty)(nil),                 // 10: google.protobuf.Empty
+}
+var file_inference_service_proto_depIdxs = []int32{
+	1,  // 0: api.Container.env:type_name -> api.Env
+	2,  // 1: api.InferenceServiceTransformer.containers:type_name -> api.Container
+	4,  // 2: api.CreateInferenceServiceRequest.predictor:type_name -> api.InferenceServicePredictor
+	3,  // 3: api.CreateInferenceServiceRequest.transformer:type_name -> api.InferenceServiceTransformer
+	7,  // 4: api.GetInferenceServiceResponse.conditions:type_name -> api.InferenceServiceCondition
+	5,  // 5: api.InferenceService.CreateInferenceService:input_type -> api.CreateInferenceServiceRequest
+	0,  // 6: api.InferenceService.GetInferenceService:input_type -> api.InferenceServiceIdentifier
+	0,  // 7: api.InferenceService.DeleteInferenceService:input_type -> api.InferenceServiceIdentifier
+	8,  // 8: api.InferenceService.CreateInferenceService:output_type -> api.GetInferenceServiceResponse
+	8,  // 9: api.InferenceService.GetInferenceService:output_type -> api.GetInferenceServiceResponse
+	10, // 10: api.InferenceService.DeleteInferenceService:output_type -> google.protobuf.Empty
+	8,  // [8:11] is the sub-list for method output_type
+	5,  // [5:8] is the sub-list for method input_type
+	5,  // [5:5] is the sub-list for extension type_name
+	5,  // [5:5] is the sub-list for extension extendee
+	0,  // [0:5] is the sub-list for field type_name
+}
+
+func init() { file_inference_service_proto_init() }
+func file_inference_service_proto_init() {
+	if File_inference_service_proto != nil {
+		return
+	}
+	if !protoimpl.UnsafeEnabled {
+		file_inference_service_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*InferenceServiceIdentifier); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*Env); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*Container); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*InferenceServiceTransformer); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*InferenceServicePredictor); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*CreateInferenceServiceRequest); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*DeployModelResponse); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[7].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*InferenceServiceCondition); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[8].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*GetInferenceServiceResponse); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+		file_inference_service_proto_msgTypes[9].Exporter = func(v interface{}, i int) interface{} {
+			switch v := v.(*InferenceServiceEndpoints); i {
+			case 0:
+				return &v.state
+			case 1:
+				return &v.sizeCache
+			case 2:
+				return &v.unknownFields
+			default:
+				return nil
+			}
+		}
+	}
+	type x struct{}
+	out := protoimpl.TypeBuilder{
+		File: protoimpl.DescBuilder{
+			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
+			RawDescriptor: file_inference_service_proto_rawDesc,
+			NumEnums:      0,
+			NumMessages:   10,
+			NumExtensions: 0,
+			NumServices:   1,
+		},
+		GoTypes:           file_inference_service_proto_goTypes,
+		DependencyIndexes: file_inference_service_proto_depIdxs,
+		MessageInfos:      file_inference_service_proto_msgTypes,
+	}.Build()
+	File_inference_service_proto = out.File
+	file_inference_service_proto_rawDesc = nil
+	file_inference_service_proto_goTypes = nil
+	file_inference_service_proto_depIdxs = nil
+}

api/gen/inference_service.pb.gw.go

@@ -0,0 +1,439 @@
+// Code generated by protoc-gen-grpc-gateway. DO NOT EDIT.
+// source: inference_service.proto
+
+/*
+Package gen is a reverse proxy.
+
+It translates gRPC into RESTful JSON APIs.
+*/
+package gen
+
+import (
+	"context"
+	"io"
+	"net/http"
+
+	"github.com/grpc-ecosystem/grpc-gateway/v2/runtime"
+	"github.com/grpc-ecosystem/grpc-gateway/v2/utilities"
+	"google.golang.org/grpc"
+	"google.golang.org/grpc/codes"
+	"google.golang.org/grpc/grpclog"
+	"google.golang.org/grpc/metadata"
+	"google.golang.org/grpc/status"
+	"google.golang.org/protobuf/proto"
+)
+
+// Suppress "imported and not used" errors
+var _ codes.Code
+var _ io.Reader
+var _ status.Status
+var _ = runtime.String
+var _ = utilities.NewDoubleArray
+var _ = metadata.Join
+
+func request_InferenceService_CreateInferenceService_0(ctx context.Context, marshaler runtime.Marshaler, client InferenceServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq CreateInferenceServiceRequest
+	var metadata runtime.ServerMetadata
+
+	newReader, berr := utilities.IOReaderFactory(req.Body)
+	if berr != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", berr)
+	}
+	if err := marshaler.NewDecoder(newReader()).Decode(&protoReq); err != nil && err != io.EOF {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
+	}
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	msg, err := client.CreateInferenceService(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
+	return msg, metadata, err
+
+}
+
+func local_request_InferenceService_CreateInferenceService_0(ctx context.Context, marshaler runtime.Marshaler, server InferenceServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq CreateInferenceServiceRequest
+	var metadata runtime.ServerMetadata
+
+	newReader, berr := utilities.IOReaderFactory(req.Body)
+	if berr != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", berr)
+	}
+	if err := marshaler.NewDecoder(newReader()).Decode(&protoReq); err != nil && err != io.EOF {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
+	}
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	msg, err := server.CreateInferenceService(ctx, &protoReq)
+	return msg, metadata, err
+
+}
+
+func request_InferenceService_GetInferenceService_0(ctx context.Context, marshaler runtime.Marshaler, client InferenceServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq InferenceServiceIdentifier
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["name"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "name")
+	}
+
+	protoReq.Name, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "name", err)
+	}
+
+	msg, err := client.GetInferenceService(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
+	return msg, metadata, err
+
+}
+
+func local_request_InferenceService_GetInferenceService_0(ctx context.Context, marshaler runtime.Marshaler, server InferenceServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq InferenceServiceIdentifier
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["name"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "name")
+	}
+
+	protoReq.Name, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "name", err)
+	}
+
+	msg, err := server.GetInferenceService(ctx, &protoReq)
+	return msg, metadata, err
+
+}
+
+func request_InferenceService_DeleteInferenceService_0(ctx context.Context, marshaler runtime.Marshaler, client InferenceServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq InferenceServiceIdentifier
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["name"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "name")
+	}
+
+	protoReq.Name, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "name", err)
+	}
+
+	msg, err := client.DeleteInferenceService(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
+	return msg, metadata, err
+
+}
+
+func local_request_InferenceService_DeleteInferenceService_0(ctx context.Context, marshaler runtime.Marshaler, server InferenceServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
+	var protoReq InferenceServiceIdentifier
+	var metadata runtime.ServerMetadata
+
+	var (
+		val string
+		ok  bool
+		err error
+		_   = err
+	)
+
+	val, ok = pathParams["namespace"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
+	}
+
+	protoReq.Namespace, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
+	}
+
+	val, ok = pathParams["name"]
+	if !ok {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "name")
+	}
+
+	protoReq.Name, err = runtime.String(val)
+	if err != nil {
+		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "name", err)
+	}
+
+	msg, err := server.DeleteInferenceService(ctx, &protoReq)
+	return msg, metadata, err
+
+}
+
+// RegisterInferenceServiceHandlerServer registers the http handlers for service InferenceService to "mux".
+// UnaryRPC     :call InferenceServiceServer directly.
+// StreamingRPC :currently unsupported pending https://github.com/grpc/grpc-go/issues/906.
+// Note that using this registration option will cause many gRPC library features to stop working. Consider using RegisterInferenceServiceHandlerFromEndpoint instead.
+func RegisterInferenceServiceHandlerServer(ctx context.Context, mux *runtime.ServeMux, server InferenceServiceServer) error {
+
+	mux.Handle("POST", pattern_InferenceService_CreateInferenceService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		var stream runtime.ServerTransportStream
+		ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.InferenceService/CreateInferenceService")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := local_request_InferenceService_CreateInferenceService_0(rctx, inboundMarshaler, server, req, pathParams)
+		md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_InferenceService_CreateInferenceService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	mux.Handle("GET", pattern_InferenceService_GetInferenceService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		var stream runtime.ServerTransportStream
+		ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.InferenceService/GetInferenceService")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := local_request_InferenceService_GetInferenceService_0(rctx, inboundMarshaler, server, req, pathParams)
+		md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_InferenceService_GetInferenceService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	mux.Handle("DELETE", pattern_InferenceService_DeleteInferenceService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		var stream runtime.ServerTransportStream
+		ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.InferenceService/DeleteInferenceService")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := local_request_InferenceService_DeleteInferenceService_0(rctx, inboundMarshaler, server, req, pathParams)
+		md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_InferenceService_DeleteInferenceService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	return nil
+}
+
+// RegisterInferenceServiceHandlerFromEndpoint is same as RegisterInferenceServiceHandler but
+// automatically dials to "endpoint" and closes the connection when "ctx" gets done.
+func RegisterInferenceServiceHandlerFromEndpoint(ctx context.Context, mux *runtime.ServeMux, endpoint string, opts []grpc.DialOption) (err error) {
+	conn, err := grpc.Dial(endpoint, opts...)
+	if err != nil {
+		return err
+	}
+	defer func() {
+		if err != nil {
+			if cerr := conn.Close(); cerr != nil {
+				grpclog.Infof("Failed to close conn to %s: %v", endpoint, cerr)
+			}
+			return
+		}
+		go func() {
+			<-ctx.Done()
+			if cerr := conn.Close(); cerr != nil {
+				grpclog.Infof("Failed to close conn to %s: %v", endpoint, cerr)
+			}
+		}()
+	}()
+
+	return RegisterInferenceServiceHandler(ctx, mux, conn)
+}
+
+// RegisterInferenceServiceHandler registers the http handlers for service InferenceService to "mux".
+// The handlers forward requests to the grpc endpoint over "conn".
+func RegisterInferenceServiceHandler(ctx context.Context, mux *runtime.ServeMux, conn *grpc.ClientConn) error {
+	return RegisterInferenceServiceHandlerClient(ctx, mux, NewInferenceServiceClient(conn))
+}
+
+// RegisterInferenceServiceHandlerClient registers the http handlers for service InferenceService
+// to "mux". The handlers forward requests to the grpc endpoint over the given implementation of "InferenceServiceClient".
+// Note: the gRPC framework executes interceptors within the gRPC handler. If the passed in "InferenceServiceClient"
+// doesn't go through the normal gRPC flow (creating a gRPC client etc.) then it will be up to the passed in
+// "InferenceServiceClient" to call the correct interceptors.
+func RegisterInferenceServiceHandlerClient(ctx context.Context, mux *runtime.ServeMux, client InferenceServiceClient) error {
+
+	mux.Handle("POST", pattern_InferenceService_CreateInferenceService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.InferenceService/CreateInferenceService")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := request_InferenceService_CreateInferenceService_0(rctx, inboundMarshaler, client, req, pathParams)
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_InferenceService_CreateInferenceService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	mux.Handle("GET", pattern_InferenceService_GetInferenceService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.InferenceService/GetInferenceService")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := request_InferenceService_GetInferenceService_0(rctx, inboundMarshaler, client, req, pathParams)
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_InferenceService_GetInferenceService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	mux.Handle("DELETE", pattern_InferenceService_DeleteInferenceService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
+		ctx, cancel := context.WithCancel(req.Context())
+		defer cancel()
+		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
+		rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.InferenceService/DeleteInferenceService")
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+		resp, md, err := request_InferenceService_DeleteInferenceService_0(rctx, inboundMarshaler, client, req, pathParams)
+		ctx = runtime.NewServerMetadataContext(ctx, md)
+		if err != nil {
+			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
+			return
+		}
+
+		forward_InferenceService_DeleteInferenceService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
+
+	})
+
+	return nil
+}
+
+var (
+	pattern_InferenceService_CreateInferenceService_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3}, []string{"apis", "v1beta1", "namespace", "inferenceservice"}, ""))
+
+	pattern_InferenceService_GetInferenceService_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4}, []string{"apis", "v1beta1", "namespace", "inferenceservice", "name"}, ""))
+
+	pattern_InferenceService_DeleteInferenceService_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4}, []string{"apis", "v1beta1", "namespace", "inferenceservice", "name"}, ""))
+)
+
+var (
+	forward_InferenceService_CreateInferenceService_0 = runtime.ForwardResponseMessage
+
+	forward_InferenceService_GetInferenceService_0 = runtime.ForwardResponseMessage
+
+	forward_InferenceService_DeleteInferenceService_0 = runtime.ForwardResponseMessage
+)

api/gen/inference_service_grpc.pb.go

@@ -0,0 +1,170 @@
+// Code generated by protoc-gen-go-grpc. DO NOT EDIT.
+
+package gen
+
+import (
+	context "context"
+	grpc "google.golang.org/grpc"
+	codes "google.golang.org/grpc/codes"
+	status "google.golang.org/grpc/status"
+	emptypb "google.golang.org/protobuf/types/known/emptypb"
+)
+
+// This is a compile-time assertion to ensure that this generated file
+// is compatible with the grpc package it is being compiled against.
+const _ = grpc.SupportPackageIsVersion7
+
+// InferenceServiceClient is the client API for InferenceService service.
+//
+// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream.
+type InferenceServiceClient interface {
+	CreateInferenceService(ctx context.Context, in *CreateInferenceServiceRequest, opts ...grpc.CallOption) (*GetInferenceServiceResponse, error)
+	GetInferenceService(ctx context.Context, in *InferenceServiceIdentifier, opts ...grpc.CallOption) (*GetInferenceServiceResponse, error)
+	DeleteInferenceService(ctx context.Context, in *InferenceServiceIdentifier, opts ...grpc.CallOption) (*emptypb.Empty, error)
+}
+
+type inferenceServiceClient struct {
+	cc grpc.ClientConnInterface
+}
+
+func NewInferenceServiceClient(cc grpc.ClientConnInterface) InferenceServiceClient {
+	return &inferenceServiceClient{cc}
+}
+
+func (c *inferenceServiceClient) CreateInferenceService(ctx context.Context, in *CreateInferenceServiceRequest, opts ...grpc.CallOption) (*GetInferenceServiceResponse, error) {
+	out := new(GetInferenceServiceResponse)
+	err := c.cc.Invoke(ctx, "/api.InferenceService/CreateInferenceService", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *inferenceServiceClient) GetInferenceService(ctx context.Context, in *InferenceServiceIdentifier, opts ...grpc.CallOption) (*GetInferenceServiceResponse, error) {
+	out := new(GetInferenceServiceResponse)
+	err := c.cc.Invoke(ctx, "/api.InferenceService/GetInferenceService", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *inferenceServiceClient) DeleteInferenceService(ctx context.Context, in *InferenceServiceIdentifier, opts ...grpc.CallOption) (*emptypb.Empty, error) {
+	out := new(emptypb.Empty)
+	err := c.cc.Invoke(ctx, "/api.InferenceService/DeleteInferenceService", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+// InferenceServiceServer is the server API for InferenceService service.
+// All implementations must embed UnimplementedInferenceServiceServer
+// for forward compatibility
+type InferenceServiceServer interface {
+	CreateInferenceService(context.Context, *CreateInferenceServiceRequest) (*GetInferenceServiceResponse, error)
+	GetInferenceService(context.Context, *InferenceServiceIdentifier) (*GetInferenceServiceResponse, error)
+	DeleteInferenceService(context.Context, *InferenceServiceIdentifier) (*emptypb.Empty, error)
+	mustEmbedUnimplementedInferenceServiceServer()
+}
+
+// UnimplementedInferenceServiceServer must be embedded to have forward compatible implementations.
+type UnimplementedInferenceServiceServer struct {
+}
+
+func (UnimplementedInferenceServiceServer) CreateInferenceService(context.Context, *CreateInferenceServiceRequest) (*GetInferenceServiceResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method CreateInferenceService not implemented")
+}
+func (UnimplementedInferenceServiceServer) GetInferenceService(context.Context, *InferenceServiceIdentifier) (*GetInferenceServiceResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method GetInferenceService not implemented")
+}
+func (UnimplementedInferenceServiceServer) DeleteInferenceService(context.Context, *InferenceServiceIdentifier) (*emptypb.Empty, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method DeleteInferenceService not implemented")
+}
+func (UnimplementedInferenceServiceServer) mustEmbedUnimplementedInferenceServiceServer() {}
+
+// UnsafeInferenceServiceServer may be embedded to opt out of forward compatibility for this service.
+// Use of this interface is not recommended, as added methods to InferenceServiceServer will
+// result in compilation errors.
+type UnsafeInferenceServiceServer interface {
+	mustEmbedUnimplementedInferenceServiceServer()
+}
+
+func RegisterInferenceServiceServer(s grpc.ServiceRegistrar, srv InferenceServiceServer) {
+	s.RegisterService(&_InferenceService_serviceDesc, srv)
+}
+
+func _InferenceService_CreateInferenceService_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(CreateInferenceServiceRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(InferenceServiceServer).CreateInferenceService(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/api.InferenceService/CreateInferenceService",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(InferenceServiceServer).CreateInferenceService(ctx, req.(*CreateInferenceServiceRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _InferenceService_GetInferenceService_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(InferenceServiceIdentifier)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(InferenceServiceServer).GetInferenceService(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/api.InferenceService/GetInferenceService",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(InferenceServiceServer).GetInferenceService(ctx, req.(*InferenceServiceIdentifier))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _InferenceService_DeleteInferenceService_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(InferenceServiceIdentifier)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(InferenceServiceServer).DeleteInferenceService(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/api.InferenceService/DeleteInferenceService",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(InferenceServiceServer).DeleteInferenceService(ctx, req.(*InferenceServiceIdentifier))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+var _InferenceService_serviceDesc = grpc.ServiceDesc{
+	ServiceName: "api.InferenceService",
+	HandlerType: (*InferenceServiceServer)(nil),
+	Methods: []grpc.MethodDesc{
+		{
+			MethodName: "CreateInferenceService",
+			Handler:    _InferenceService_CreateInferenceService_Handler,
+		},
+		{
+			MethodName: "GetInferenceService",
+			Handler:    _InferenceService_GetInferenceService_Handler,
+		},
+		{
+			MethodName: "DeleteInferenceService",
+			Handler:    _InferenceService_DeleteInferenceService_Handler,
+		},
+	},
+	Streams:  []grpc.StreamDesc{},
+	Metadata: "inference_service.proto",
+}

api/gen/namespace.pb.go

@@ -220,7 +220,8 @@ type Namespace struct {
 	sizeCache     protoimpl.SizeCache
 	unknownFields protoimpl.UnknownFields
 
-	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
+	Name       string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
+	SourceName string `protobuf:"bytes,2,opt,name=sourceName,proto3" json:"sourceName,omitempty"`
 }
 
 func (x *Namespace) Reset() {
@@ -262,6 +263,13 @@ func (x *Namespace) GetName() string {
 	return ""
 }
 
+func (x *Namespace) GetSourceName() string {
+	if x != nil {
+		return x.SourceName
+	}
+	return ""
+}
+
 var File_namespace_proto protoreflect.FileDescriptor
 
 var file_namespace_proto_rawDesc = []byte{
@@ -289,9 +297,11 @@ var file_namespace_proto_rawDesc = []byte{
 	0x65, 0x52, 0x65, 0x71, 0x75, 0x65, 0x73, 0x74, 0x12, 0x2c, 0x0a, 0x09, 0x6e, 0x61, 0x6d, 0x65,
 	0x73, 0x70, 0x61, 0x63, 0x65, 0x18, 0x01, 0x20, 0x01, 0x28, 0x0b, 0x32, 0x0e, 0x2e, 0x61, 0x70,
 	0x69, 0x2e, 0x4e, 0x61, 0x6d, 0x65, 0x73, 0x70, 0x61, 0x63, 0x65, 0x52, 0x09, 0x6e, 0x61, 0x6d,
-	0x65, 0x73, 0x70, 0x61, 0x63, 0x65, 0x22, 0x1f, 0x0a, 0x09, 0x4e, 0x61, 0x6d, 0x65, 0x73, 0x70,
+	0x65, 0x73, 0x70, 0x61, 0x63, 0x65, 0x22, 0x3f, 0x0a, 0x09, 0x4e, 0x61, 0x6d, 0x65, 0x73, 0x70,
 	0x61, 0x63, 0x65, 0x12, 0x12, 0x0a, 0x04, 0x6e, 0x61, 0x6d, 0x65, 0x18, 0x01, 0x20, 0x01, 0x28,
-	0x09, 0x52, 0x04, 0x6e, 0x61, 0x6d, 0x65, 0x32, 0xec, 0x01, 0x0a, 0x10, 0x4e, 0x61, 0x6d, 0x65,
+	0x09, 0x52, 0x04, 0x6e, 0x61, 0x6d, 0x65, 0x12, 0x1e, 0x0a, 0x0a, 0x73, 0x6f, 0x75, 0x72, 0x63,
+	0x65, 0x4e, 0x61, 0x6d, 0x65, 0x18, 0x02, 0x20, 0x01, 0x28, 0x09, 0x52, 0x0a, 0x73, 0x6f, 0x75,
+	0x72, 0x63, 0x65, 0x4e, 0x61, 0x6d, 0x65, 0x32, 0xec, 0x01, 0x0a, 0x10, 0x4e, 0x61, 0x6d, 0x65,
 	0x73, 0x70, 0x61, 0x63, 0x65, 0x53, 0x65, 0x72, 0x76, 0x69, 0x63, 0x65, 0x12, 0x6b, 0x0a, 0x0e,
 	0x4c, 0x69, 0x73, 0x74, 0x4e, 0x61, 0x6d, 0x65, 0x73, 0x70, 0x61, 0x63, 0x65, 0x73, 0x12, 0x1a,
 	0x2e, 0x61, 0x70, 0x69, 0x2e, 0x4c, 0x69, 0x73, 0x74, 0x4e, 0x61, 0x6d, 0x65, 0x73, 0x70, 0x61,

api/gen/workflow.pb.gw.go

@@ -709,208 +709,6 @@ func local_request_WorkflowService_TerminateWorkflowExecution_0(ctx context.Cont
 
 }
 
-func request_WorkflowService_GetArtifact_0(ctx context.Context, marshaler runtime.Marshaler, client WorkflowServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
-	var protoReq GetArtifactRequest
-	var metadata runtime.ServerMetadata
-
-	var (
-		val string
-		ok  bool
-		err error
-		_   = err
-	)
-
-	val, ok = pathParams["namespace"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
-	}
-
-	protoReq.Namespace, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
-	}
-
-	val, ok = pathParams["uid"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
-	}
-
-	protoReq.Uid, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
-	}
-
-	val, ok = pathParams["key"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "key")
-	}
-
-	protoReq.Key, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "key", err)
-	}
-
-	msg, err := client.GetArtifact(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
-	return msg, metadata, err
-
-}
-
-func local_request_WorkflowService_GetArtifact_0(ctx context.Context, marshaler runtime.Marshaler, server WorkflowServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
-	var protoReq GetArtifactRequest
-	var metadata runtime.ServerMetadata
-
-	var (
-		val string
-		ok  bool
-		err error
-		_   = err
-	)
-
-	val, ok = pathParams["namespace"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
-	}
-
-	protoReq.Namespace, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
-	}
-
-	val, ok = pathParams["uid"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
-	}
-
-	protoReq.Uid, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
-	}
-
-	val, ok = pathParams["key"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "key")
-	}
-
-	protoReq.Key, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "key", err)
-	}
-
-	msg, err := server.GetArtifact(ctx, &protoReq)
-	return msg, metadata, err
-
-}
-
-var (
-	filter_WorkflowService_ListFiles_0 = &utilities.DoubleArray{Encoding: map[string]int{"namespace": 0, "uid": 1, "path": 2}, Base: []int{1, 1, 2, 3, 0, 0, 0}, Check: []int{0, 1, 1, 1, 2, 3, 4}}
-)
-
-func request_WorkflowService_ListFiles_0(ctx context.Context, marshaler runtime.Marshaler, client WorkflowServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
-	var protoReq ListFilesRequest
-	var metadata runtime.ServerMetadata
-
-	var (
-		val string
-		ok  bool
-		err error
-		_   = err
-	)
-
-	val, ok = pathParams["namespace"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
-	}
-
-	protoReq.Namespace, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
-	}
-
-	val, ok = pathParams["uid"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
-	}
-
-	protoReq.Uid, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
-	}
-
-	val, ok = pathParams["path"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "path")
-	}
-
-	protoReq.Path, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "path", err)
-	}
-
-	if err := req.ParseForm(); err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
-	}
-	if err := runtime.PopulateQueryParameters(&protoReq, req.Form, filter_WorkflowService_ListFiles_0); err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
-	}
-
-	msg, err := client.ListFiles(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
-	return msg, metadata, err
-
-}
-
-func local_request_WorkflowService_ListFiles_0(ctx context.Context, marshaler runtime.Marshaler, server WorkflowServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
-	var protoReq ListFilesRequest
-	var metadata runtime.ServerMetadata
-
-	var (
-		val string
-		ok  bool
-		err error
-		_   = err
-	)
-
-	val, ok = pathParams["namespace"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
-	}
-
-	protoReq.Namespace, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
-	}
-
-	val, ok = pathParams["uid"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
-	}
-
-	protoReq.Uid, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
-	}
-
-	val, ok = pathParams["path"]
-	if !ok {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "path")
-	}
-
-	protoReq.Path, err = runtime.String(val)
-	if err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "path", err)
-	}
-
-	if err := req.ParseForm(); err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
-	}
-	if err := runtime.PopulateQueryParameters(&protoReq, req.Form, filter_WorkflowService_ListFiles_0); err != nil {
-		return nil, metadata, status.Errorf(codes.InvalidArgument, "%v", err)
-	}
-
-	msg, err := server.ListFiles(ctx, &protoReq)
-	return msg, metadata, err
-
-}
-
 func request_WorkflowService_AddWorkflowExecutionStatistics_0(ctx context.Context, marshaler runtime.Marshaler, client WorkflowServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
 	var protoReq AddWorkflowExecutionStatisticRequest
 	var metadata runtime.ServerMetadata
@@ -1627,52 +1425,6 @@ func RegisterWorkflowServiceHandlerServer(ctx context.Context, mux *runtime.Serv
 
 	})
 
-	mux.Handle("GET", pattern_WorkflowService_GetArtifact_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
-		ctx, cancel := context.WithCancel(req.Context())
-		defer cancel()
-		var stream runtime.ServerTransportStream
-		ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
-		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
-		rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.WorkflowService/GetArtifact")
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-		resp, md, err := local_request_WorkflowService_GetArtifact_0(rctx, inboundMarshaler, server, req, pathParams)
-		md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
-		ctx = runtime.NewServerMetadataContext(ctx, md)
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-
-		forward_WorkflowService_GetArtifact_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
-
-	})
-
-	mux.Handle("GET", pattern_WorkflowService_ListFiles_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
-		ctx, cancel := context.WithCancel(req.Context())
-		defer cancel()
-		var stream runtime.ServerTransportStream
-		ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
-		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
-		rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.WorkflowService/ListFiles")
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-		resp, md, err := local_request_WorkflowService_ListFiles_0(rctx, inboundMarshaler, server, req, pathParams)
-		md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
-		ctx = runtime.NewServerMetadataContext(ctx, md)
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-
-		forward_WorkflowService_ListFiles_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
-
-	})
-
 	mux.Handle("POST", pattern_WorkflowService_AddWorkflowExecutionStatistics_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
 		ctx, cancel := context.WithCancel(req.Context())
 		defer cancel()
@@ -2052,46 +1804,6 @@ func RegisterWorkflowServiceHandlerClient(ctx context.Context, mux *runtime.Serv
 
 	})
 
-	mux.Handle("GET", pattern_WorkflowService_GetArtifact_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
-		ctx, cancel := context.WithCancel(req.Context())
-		defer cancel()
-		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
-		rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.WorkflowService/GetArtifact")
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-		resp, md, err := request_WorkflowService_GetArtifact_0(rctx, inboundMarshaler, client, req, pathParams)
-		ctx = runtime.NewServerMetadataContext(ctx, md)
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-
-		forward_WorkflowService_GetArtifact_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
-
-	})
-
-	mux.Handle("GET", pattern_WorkflowService_ListFiles_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
-		ctx, cancel := context.WithCancel(req.Context())
-		defer cancel()
-		inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
-		rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.WorkflowService/ListFiles")
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-		resp, md, err := request_WorkflowService_ListFiles_0(rctx, inboundMarshaler, client, req, pathParams)
-		ctx = runtime.NewServerMetadataContext(ctx, md)
-		if err != nil {
-			runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
-			return
-		}
-
-		forward_WorkflowService_ListFiles_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
-
-	})
-
 	mux.Handle("POST", pattern_WorkflowService_AddWorkflowExecutionStatistics_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
 		ctx, cancel := context.WithCancel(req.Context())
 		defer cancel()
@@ -2236,10 +1948,6 @@ var (
 
 	pattern_WorkflowService_TerminateWorkflowExecution_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "terminate"}, ""))
 
-	pattern_WorkflowService_GetArtifact_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5, 3, 0, 4, 1, 5, 6}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "artifacts", "key"}, ""))
-
-	pattern_WorkflowService_ListFiles_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5, 3, 0, 4, 1, 5, 6}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "files", "path"}, ""))
-
 	pattern_WorkflowService_AddWorkflowExecutionStatistics_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "statistics"}, ""))
 
 	pattern_WorkflowService_CronStartWorkflowExecutionStatistic_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "cron_start_statistics"}, ""))
@@ -2274,10 +1982,6 @@ var (
 
 	forward_WorkflowService_TerminateWorkflowExecution_0 = runtime.ForwardResponseMessage
 
-	forward_WorkflowService_GetArtifact_0 = runtime.ForwardResponseMessage
-
-	forward_WorkflowService_ListFiles_0 = runtime.ForwardResponseMessage
-
 	forward_WorkflowService_AddWorkflowExecutionStatistics_0 = runtime.ForwardResponseMessage
 
 	forward_WorkflowService_CronStartWorkflowExecutionStatistic_0 = runtime.ForwardResponseMessage

api/gen/workflow_grpc.pb.go

@@ -30,8 +30,6 @@ type WorkflowServiceClient interface {
 	GetWorkflowExecutionMetrics(ctx context.Context, in *GetWorkflowExecutionMetricsRequest, opts ...grpc.CallOption) (*GetWorkflowExecutionMetricsResponse, error)
 	ResubmitWorkflowExecution(ctx context.Context, in *ResubmitWorkflowExecutionRequest, opts ...grpc.CallOption) (*WorkflowExecution, error)
 	TerminateWorkflowExecution(ctx context.Context, in *TerminateWorkflowExecutionRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
-	GetArtifact(ctx context.Context, in *GetArtifactRequest, opts ...grpc.CallOption) (*ArtifactResponse, error)
-	ListFiles(ctx context.Context, in *ListFilesRequest, opts ...grpc.CallOption) (*ListFilesResponse, error)
 	AddWorkflowExecutionStatistics(ctx context.Context, in *AddWorkflowExecutionStatisticRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
 	CronStartWorkflowExecutionStatistic(ctx context.Context, in *CronStartWorkflowExecutionStatisticRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
 	UpdateWorkflowExecutionStatus(ctx context.Context, in *UpdateWorkflowExecutionStatusRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
@@ -184,24 +182,6 @@ func (c *workflowServiceClient) TerminateWorkflowExecution(ctx context.Context,
 	return out, nil
 }
 
-func (c *workflowServiceClient) GetArtifact(ctx context.Context, in *GetArtifactRequest, opts ...grpc.CallOption) (*ArtifactResponse, error) {
-	out := new(ArtifactResponse)
-	err := c.cc.Invoke(ctx, "/api.WorkflowService/GetArtifact", in, out, opts...)
-	if err != nil {
-		return nil, err
-	}
-	return out, nil
-}
-
-func (c *workflowServiceClient) ListFiles(ctx context.Context, in *ListFilesRequest, opts ...grpc.CallOption) (*ListFilesResponse, error) {
-	out := new(ListFilesResponse)
-	err := c.cc.Invoke(ctx, "/api.WorkflowService/ListFiles", in, out, opts...)
-	if err != nil {
-		return nil, err
-	}
-	return out, nil
-}
-
 func (c *workflowServiceClient) AddWorkflowExecutionStatistics(ctx context.Context, in *AddWorkflowExecutionStatisticRequest, opts ...grpc.CallOption) (*emptypb.Empty, error) {
 	out := new(emptypb.Empty)
 	err := c.cc.Invoke(ctx, "/api.WorkflowService/AddWorkflowExecutionStatistics", in, out, opts...)
@@ -272,8 +252,6 @@ type WorkflowServiceServer interface {
 	GetWorkflowExecutionMetrics(context.Context, *GetWorkflowExecutionMetricsRequest) (*GetWorkflowExecutionMetricsResponse, error)
 	ResubmitWorkflowExecution(context.Context, *ResubmitWorkflowExecutionRequest) (*WorkflowExecution, error)
 	TerminateWorkflowExecution(context.Context, *TerminateWorkflowExecutionRequest) (*emptypb.Empty, error)
-	GetArtifact(context.Context, *GetArtifactRequest) (*ArtifactResponse, error)
-	ListFiles(context.Context, *ListFilesRequest) (*ListFilesResponse, error)
 	AddWorkflowExecutionStatistics(context.Context, *AddWorkflowExecutionStatisticRequest) (*emptypb.Empty, error)
 	CronStartWorkflowExecutionStatistic(context.Context, *CronStartWorkflowExecutionStatisticRequest) (*emptypb.Empty, error)
 	UpdateWorkflowExecutionStatus(context.Context, *UpdateWorkflowExecutionStatusRequest) (*emptypb.Empty, error)
@@ -317,12 +295,6 @@ func (UnimplementedWorkflowServiceServer) ResubmitWorkflowExecution(context.Cont
 func (UnimplementedWorkflowServiceServer) TerminateWorkflowExecution(context.Context, *TerminateWorkflowExecutionRequest) (*emptypb.Empty, error) {
 	return nil, status.Errorf(codes.Unimplemented, "method TerminateWorkflowExecution not implemented")
 }
-func (UnimplementedWorkflowServiceServer) GetArtifact(context.Context, *GetArtifactRequest) (*ArtifactResponse, error) {
-	return nil, status.Errorf(codes.Unimplemented, "method GetArtifact not implemented")
-}
-func (UnimplementedWorkflowServiceServer) ListFiles(context.Context, *ListFilesRequest) (*ListFilesResponse, error) {
-	return nil, status.Errorf(codes.Unimplemented, "method ListFiles not implemented")
-}
 func (UnimplementedWorkflowServiceServer) AddWorkflowExecutionStatistics(context.Context, *AddWorkflowExecutionStatisticRequest) (*emptypb.Empty, error) {
 	return nil, status.Errorf(codes.Unimplemented, "method AddWorkflowExecutionStatistics not implemented")
 }
@@ -540,42 +512,6 @@ func _WorkflowService_TerminateWorkflowExecution_Handler(srv interface{}, ctx co
 	return interceptor(ctx, in, info, handler)
 }
 
-func _WorkflowService_GetArtifact_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
-	in := new(GetArtifactRequest)
-	if err := dec(in); err != nil {
-		return nil, err
-	}
-	if interceptor == nil {
-		return srv.(WorkflowServiceServer).GetArtifact(ctx, in)
-	}
-	info := &grpc.UnaryServerInfo{
-		Server:     srv,
-		FullMethod: "/api.WorkflowService/GetArtifact",
-	}
-	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
-		return srv.(WorkflowServiceServer).GetArtifact(ctx, req.(*GetArtifactRequest))
-	}
-	return interceptor(ctx, in, info, handler)
-}
-
-func _WorkflowService_ListFiles_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
-	in := new(ListFilesRequest)
-	if err := dec(in); err != nil {
-		return nil, err
-	}
-	if interceptor == nil {
-		return srv.(WorkflowServiceServer).ListFiles(ctx, in)
-	}
-	info := &grpc.UnaryServerInfo{
-		Server:     srv,
-		FullMethod: "/api.WorkflowService/ListFiles",
-	}
-	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
-		return srv.(WorkflowServiceServer).ListFiles(ctx, req.(*ListFilesRequest))
-	}
-	return interceptor(ctx, in, info, handler)
-}
-
 func _WorkflowService_AddWorkflowExecutionStatistics_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
 	in := new(AddWorkflowExecutionStatisticRequest)
 	if err := dec(in); err != nil {
@@ -720,14 +656,6 @@ var _WorkflowService_serviceDesc = grpc.ServiceDesc{
 			MethodName: "TerminateWorkflowExecution",
 			Handler:    _WorkflowService_TerminateWorkflowExecution_Handler,
 		},
-		{
-			MethodName: "GetArtifact",
-			Handler:    _WorkflowService_GetArtifact_Handler,
-		},
-		{
-			MethodName: "ListFiles",
-			Handler:    _WorkflowService_ListFiles_Handler,
-		},
 		{
 			MethodName: "AddWorkflowExecutionStatistics",
 			Handler:    _WorkflowService_AddWorkflowExecutionStatistics_Handler,

api/gen/workspace.pb.go

@@ -297,6 +297,7 @@ type CreateWorkspaceBody struct {
 	WorkspaceTemplateVersion int64        `protobuf:"varint,2,opt,name=workspaceTemplateVersion,proto3" json:"workspaceTemplateVersion,omitempty"`
 	Parameters               []*Parameter `protobuf:"bytes,3,rep,name=parameters,proto3" json:"parameters,omitempty"`
 	Labels                   []*KeyValue  `protobuf:"bytes,4,rep,name=labels,proto3" json:"labels,omitempty"`
+	CaptureNode              bool         `protobuf:"varint,5,opt,name=captureNode,proto3" json:"captureNode,omitempty"`
 }
 
 func (x *CreateWorkspaceBody) Reset() {
@@ -359,6 +360,13 @@ func (x *CreateWorkspaceBody) GetLabels() []*KeyValue {
 	return nil
 }
 
+func (x *CreateWorkspaceBody) GetCaptureNode() bool {
+	if x != nil {
+		return x.CaptureNode
+	}
+	return false
+}
+
 type CreateWorkspaceRequest struct {
 	state         protoimpl.MessageState
 	sizeCache     protoimpl.SizeCache
@@ -1534,7 +1542,7 @@ var file_workspace_proto_rawDesc = []byte{
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@@ -1548,257 +1556,259 @@ var file_workspace_proto_rawDesc = []byte{
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 }
 
 var (

api/proto/files.proto

@@ -0,0 +1,56 @@
+syntax = "proto3";
+
+package api;
+option go_package = "github.com/onepanelio/core/api/gen";
+
+import "google/api/annotations.proto";
+
+service FileService {
+  rpc GetObjectDownloadPresignedURL (GetObjectPresignedUrlRequest) returns (GetPresignedUrlResponse) {
+    option (google.api.http) = {
+      get: "/apis/v1beta1/{namespace}/files/presigned-url/{key=**}"
+    };
+  }
+
+  rpc ListFiles (ListFilesRequest) returns (ListFilesResponse) {
+    option (google.api.http) = {
+      get: "/apis/v1beta1/{namespace}/files/list/{path=**}"
+    };
+  }
+}
+
+message File {
+  string path = 1;
+  string name = 2;
+  string extension = 3;
+  int64 size = 4;
+  string contentType = 5;
+  string lastModified = 6;
+  bool directory = 7;
+}
+
+message ListFilesRequest {
+  string namespace = 1;
+  string path = 2;
+  int32 page = 3;
+  int32 perPage = 4;
+}
+
+message ListFilesResponse {
+  int32 count = 1;
+  int32 totalCount = 2;
+  int32 page = 3;
+  int32 pages = 4;
+  repeated File files = 5;
+  string parentPath = 6;
+}
+
+message GetObjectPresignedUrlRequest {
+  string namespace = 1;
+  string key = 2;
+}
+
+message GetPresignedUrlResponse {
+  string url = 1;
+  int64 size = 2;
+}

api/proto/inference_service.proto

@@ -0,0 +1,92 @@
+syntax = "proto3";
+
+package api;
+option go_package = "github.com/onepanelio/core/api/gen";
+
+import "google/api/annotations.proto";
+import "google/protobuf/empty.proto";
+
+service InferenceService {
+  rpc CreateInferenceService (CreateInferenceServiceRequest) returns (GetInferenceServiceResponse) {
+    option (google.api.http) = {
+      post: "/apis/v1beta1/{namespace}/inferenceservice"
+      body: "*"
+    };
+  }
+
+  rpc GetInferenceService(InferenceServiceIdentifier) returns (GetInferenceServiceResponse) {
+    option (google.api.http) = {
+      get: "/apis/v1beta1/{namespace}/inferenceservice/{name}"
+    };
+  }
+
+  rpc DeleteInferenceService (InferenceServiceIdentifier) returns (google.protobuf.Empty) {
+    option (google.api.http) = {
+      delete: "/apis/v1beta1/{namespace}/inferenceservice/{name}"
+    };
+  }
+}
+
+message InferenceServiceIdentifier {
+  string namespace = 1;
+  string name = 2;
+}
+
+message Env {
+    string name = 1;
+    string value = 2;
+}
+
+message Container {
+    string image = 1;
+    string name = 2;
+    repeated Env env = 3;
+}
+
+message InferenceServiceTransformer {
+  repeated Container containers = 1;
+  string minCpu = 2;
+  string minMemory = 3;
+  string maxCpu = 4;
+  string maxMemory = 5;
+}
+
+message InferenceServicePredictor {
+  string name = 1;
+  string runtimeVersion = 2;
+  string storageUri = 3;
+  string nodeSelector = 4;
+  string minCpu = 5;
+  string minMemory = 6;
+  string maxCpu = 7;
+  string maxMemory = 8;
+}
+
+message CreateInferenceServiceRequest {
+  string namespace = 1;
+  string name = 2;
+  string defaultTransformerImage = 3;
+
+  InferenceServicePredictor predictor = 4;
+  InferenceServiceTransformer transformer = 5;
+}
+
+message DeployModelResponse {
+  string status = 1;
+}
+
+message InferenceServiceCondition {
+  string lastTransitionTime = 1;
+  string status = 2;
+  string type = 3;
+}
+
+message GetInferenceServiceResponse {
+    bool ready = 1;
+    repeated InferenceServiceCondition conditions = 2;
+    string predictUrl = 3;
+}
+
+message InferenceServiceEndpoints {
+  string predict = 1;
+}

api/proto/namespace.proto

@@ -40,4 +40,5 @@ message CreateNamespaceRequest {
 
 message Namespace {
     string name = 1;
+    string sourceName = 2;
 }

api/proto/workflow.proto

@@ -74,18 +74,6 @@ service WorkflowService {
         };
     }
 
-    rpc GetArtifact (GetArtifactRequest) returns (ArtifactResponse) {
-        option (google.api.http) = {
-            get: "/apis/v1beta1/{namespace}/workflow_executions/{uid}/artifacts/{key=**}"
-        };
-    }
-
-    rpc ListFiles (ListFilesRequest) returns (ListFilesResponse) {
-        option (google.api.http) = {
-            get: "/apis/v1beta1/{namespace}/workflow_executions/{uid}/files/{path=**}"
-        };
-    }
-
     rpc AddWorkflowExecutionStatistics (AddWorkflowExecutionStatisticRequest) returns (google.protobuf.Empty) {
         option (google.api.http) = {
             post: "/apis/v1beta1/{namespace}/workflow_executions/{uid}/statistics"
@@ -235,37 +223,6 @@ message WorkflowExecution {
     repeated Metric metrics = 12;
 }
 
-message ArtifactResponse {
-    bytes data = 1;
-}
-
-message File {
-    string path = 1;
-    string name = 2;
-    string extension = 3;
-    int64 size = 4;
-    string contentType = 5;
-    string lastModified = 6;
-    bool directory = 7;
-}
-
-message ListFilesRequest {
-    string namespace = 1;
-    string uid = 2;
-    string path = 3;
-    int32 page = 4;
-    int32 perPage = 5;
-}
-
-message ListFilesResponse {
-    int32 count = 1;
-    int32 totalCount = 2;
-    int32 page = 3;
-    int32 pages = 4;
-    repeated File files = 5;
-    string parentPath = 6;
-}
-
 message Statistics {
     string workflowStatus = 1;
     int64 workflowTemplateId = 2;

api/proto/workspace.proto

@@ -121,6 +121,7 @@ message CreateWorkspaceBody {
 
 	repeated Parameter parameters = 3;
 	repeated KeyValue labels = 4;
+	bool captureNode = 5;
 }
 
 message CreateWorkspaceRequest {

db/go/20211028205201_cvat_1_6.go

@@ -0,0 +1,28 @@
+package migration
+
+import (
+	"database/sql"
+	"github.com/pressly/goose"
+	"path/filepath"
+)
+
+func initialize20211028205201() {
+	if _, ok := initializedMigrations[20211028205201]; !ok {
+		goose.AddMigration(Up20211028205201, Down20211028205201)
+		initializedMigrations[20211028205201] = true
+	}
+}
+
+// Up20211028205201 creates the new cvat 1.6.0 workspace template
+func Up20211028205201(tx *sql.Tx) error {
+	// This code is executed when the migration is applied.
+	return createWorkspaceTemplate(
+		filepath.Join("workspaces", "cvat_1_6_0", "20211028205201.yaml"),
+		"CVAT_1.6.0",
+		"Powerful and efficient Computer Vision Annotation Tool (CVAT)")
+}
+
+// Down20211028205201 archives the new cvat 1.6.0 workspace template
+func Down20211028205201(tx *sql.Tx) error {
+	return archiveWorkspaceTemplate("CVAT_1.6.0")
+}

db/go/db.go

@@ -96,6 +96,7 @@ func Initialize() {
 	initialize20210329194731()
 	initialize20210414165510()
 	initialize20210719190719()
+	initialize20211028205201()
 
 	if err := client.DB.Close(); err != nil {
 		log.Printf("[error] closing db %v", err)

db/go/util.go

@@ -3,7 +3,9 @@ package migration
 import (
 	"fmt"
 	v1 "github.com/onepanelio/core/pkg"
+	"github.com/onepanelio/core/pkg/util/data"
 	uid2 "github.com/onepanelio/core/pkg/util/uid"
+	"path/filepath"
 )
 
 // createWorkspaceTemplate will create the workspace template given by {{templateName}} with the contents
@@ -21,7 +23,13 @@ func createWorkspaceTemplate(filename, templateName, description string) error {
 		return err
 	}
 
-	newManifest, err := readDataFile(filename)
+	filename = filepath.Join("db", "yaml", filename)
+	manifestFile, err := data.ManifestFileFromFile(filename)
+	if err != nil {
+		return err
+	}
+
+	newManifest, err := manifestFile.SpecString()
 	if err != nil {
 		return err
 	}
@@ -97,12 +105,19 @@ func updateWorkspaceTemplateManifest(filename, templateName string) error {
 	}
 	defer client.DB.Close()
 
+	filename = filepath.Join("db", "yaml", filename)
+
 	namespaces, err := client.ListOnepanelEnabledNamespaces()
 	if err != nil {
 		return err
 	}
 
-	newManifest, err := readDataFile(filename)
+	manifest, err := data.ManifestFileFromFile(filename)
+	if err != nil {
+		return err
+	}
+
+	newManifest, err := manifest.SpecString()
 	if err != nil {
 		return err
 	}
@@ -145,7 +160,14 @@ func createWorkflowTemplate(filename, templateName string, labels map[string]str
 		return err
 	}
 
-	manifest, err := readDataFile(filename)
+	filename = filepath.Join("db", "yaml", filename)
+
+	manifestFile, err := data.ManifestFileFromFile(filename)
+	if err != nil {
+		return err
+	}
+
+	manifest, err := manifestFile.SpecString()
 	if err != nil {
 		return err
 	}
@@ -190,7 +212,14 @@ func updateWorkflowTemplateManifest(filename, templateName string, labels map[st
 		return err
 	}
 
-	newManifest, err := readDataFile(filename)
+	filename = filepath.Join("db", "yaml", filename)
+
+	manifestFile, err := data.ManifestFileFromFile(filename)
+	if err != nil {
+		return err
+	}
+
+	newManifest, err := manifestFile.SpecString()
 	if err != nil {
 		return err
 	}

db/sql/20210802222820_configurable_capture_workspace_node.sql

@@ -0,0 +1,7 @@
+-- +goose Up
+-- SQL in this section is executed when the migration is applied.
+ALTER TABLE workspaces ADD COLUMN capture_node boolean;
+UPDATE workspaces SET capture_node = false;
+
+-- +goose Down
+ALTER TABLE workspaces DROP COLUMN capture_node;

db/yaml/workflows/hyperparameter-tuning/20201225172926.yaml

@@ -1,183 +1,194 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/nni-hyperparameter-tuning/mnist/
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/onepanelio/templates
-    - name: revision
-      value: master
-    - name: config
-      displayName: Configuration
-      required: true
-      hint: NNI configuration
-      type: textarea.textarea
-      value: |-
-        authorName: Onepanel, Inc.
-        experimentName: MNIST TF v2.x
-        trialConcurrency: 1
-        maxExecDuration: 1h
-        maxTrialNum: 10
-        trainingServicePlatform: local
-        searchSpacePath: search_space.json
-        useAnnotation: false
-        tuner:
-          # gpuIndices: '0'           # uncomment and update to the GPU indices to assign this tuner
-          builtinTunerName: TPE       # choices: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
-          classArgs:
-            optimize_mode: maximize   # choices: maximize, minimize
-        trial:
-          command: python main.py --output /mnt/output
-          codeDir: .
-          # gpuNum: 1                 # uncomment and update to number of GPUs
-    - name: search-space
-      displayName: Search space configuration
-      required: true
-      type: textarea.textarea
-      value: |-
-        {
-          "dropout_rate": { "_type": "uniform", "_value": [0.5, 0.9] },
-          "conv_size": { "_type": "choice", "_value": [2, 3, 5, 7] },
-          "hidden_size": { "_type": "choice", "_value": [124, 512, 1024] },
-          "batch_size": { "_type": "choice", "_value": [16, 32] },
-          "learning_rate": { "_type": "choice", "_value": [0.0001, 0.001, 0.01, 0.1] },
-          "epochs": { "_type": "choice", "_value": [10] }
-        }
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      required: true
+metadata:
+  name: "Hyperparameter Tuning Example"
+  kind: Workflow
+  version: 20201225172926
+  action: create
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/nni-hyperparameter-tuning/mnist/"
+  deprecated: true
+  labels:
+    framework: tensorflow
+    tuner: TPE
+    "created-by": system
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/onepanelio/templates
+      - name: revision
+        value: master
+      - name: config
+        displayName: Configuration
+        required: true
+        hint: NNI configuration
+        type: textarea.textarea
+        value: |-
+          authorName: Onepanel, Inc.
+          experimentName: MNIST TF v2.x
+          trialConcurrency: 1
+          maxExecDuration: 1h
+          maxTrialNum: 10
+          trainingServicePlatform: local
+          searchSpacePath: search_space.json
+          useAnnotation: false
+          tuner:
+            # gpuIndices: '0'           # uncomment and update to the GPU indices to assign this tuner
+            builtinTunerName: TPE       # choices: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
+            classArgs:
+              optimize_mode: maximize   # choices: maximize, minimize
+          trial:
+            command: python main.py --output /mnt/output
+            codeDir: .
+            # gpuNum: 1                 # uncomment and update to number of GPUs
+      - name: search-space
+        displayName: Search space configuration
+        required: true
+        type: textarea.textarea
+        value: |-
+          {
+            "dropout_rate": { "_type": "uniform", "_value": [0.5, 0.9] },
+            "conv_size": { "_type": "choice", "_value": [2, 3, 5, 7] },
+            "hidden_size": { "_type": "choice", "_value": [124, 512, 1024] },
+            "batch_size": { "_type": "choice", "_value": [16, 32] },
+            "learning_rate": { "_type": "choice", "_value": [0.0001, 0.001, 0.01, 0.1] },
+            "epochs": { "_type": "choice", "_value": [10] }
+          }
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        required: true
 
-volumeClaimTemplates:
-  - metadata:
-      name: hyperparamtuning-data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 20Gi
-  - metadata:
-      name: hyperparamtuning-output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 20Gi
+  volumeClaimTemplates:
+    - metadata:
+        name: hyperparamtuning-data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 20Gi
+    - metadata:
+        name: hyperparamtuning-output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 20Gi
 
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: hyperparameter-tuning
-          template: hyperparameter-tuning
-        - name: workflow-metrics-writer
-          template: workflow-metrics-writer
-          dependencies: [hyperparameter-tuning]
-          arguments:
-            # Use sys-metrics artifact output from hyperparameter-tuning Task
-            artifacts:
-              - name: best-metrics
-                from: "{{tasks.hyperparameter-tuning.outputs.artifacts.sys-metrics}}"
-  - name: hyperparameter-tuning
-    inputs:
-      artifacts:
-        - name: src
-          git:
-            repo: '{{workflow.parameters.source}}'
-            revision: '{{workflow.parameters.revision}}'
-          path: /mnt/data/src
-        - name: config
-          path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
-          raw:
-            data: '{{workflow.parameters.config}}'
-        - name: search-space
-          path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/search_space.json
-          raw:
-            data: '{{workflow.parameters.search-space}}'
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    container:
-      image: onepanel/dl:0.17.0
-      args:
-        - --config
-        - /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
-      workingDir: /mnt
-      volumeMounts:
-        - name: hyperparamtuning-data
-          mountPath: /mnt/data
-        - name: hyperparamtuning-output
-          mountPath: /mnt/output
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: nni-web-ui
-        image: 'onepanel/nni-web-ui:0.17.0'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        ports:
-          - containerPort: 9000
-            name: nni
-      - name: tensorboard
-        image: 'tensorflow/tensorflow:2.3.0'
-        command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: hyperparameter-tuning
+            template: hyperparameter-tuning
+          - name: workflow-metrics-writer
+            template: workflow-metrics-writer
+            dependencies: [hyperparameter-tuning]
+            arguments:
+              # Use sys-metrics artifact output from hyperparameter-tuning Task
+              artifacts:
+                - name: best-metrics
+                  from: "{{tasks.hyperparameter-tuning.outputs.artifacts.sys-metrics}}"
+    - name: hyperparameter-tuning
+      inputs:
+        artifacts:
+          - name: src
+            git:
+              repo: '{{workflow.parameters.source}}'
+              revision: '{{workflow.parameters.revision}}'
+            path: /mnt/data/src
+          - name: config
+            path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
+            raw:
+              data: '{{workflow.parameters.config}}'
+          - name: search-space
+            path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/search_space.json
+            raw:
+              data: '{{workflow.parameters.search-space}}'
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      container:
+        image: onepanel/dl:0.17.0
         args:
-          # Read logs from /mnt/output/tensorboard - /mnt/output is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-  - name: workflow-metrics-writer
-    inputs:
-      artifacts:
-        - name: best-metrics
-          path: /tmp/sys-metrics.json
-    script:
-      image: onepanel/python-sdk:v0.16.0
-      command: [python, '-u']
-      source: |
-        import os
-        import json
+          - --config
+          - /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
+        workingDir: /mnt
+        volumeMounts:
+          - name: hyperparamtuning-data
+            mountPath: /mnt/data
+          - name: hyperparamtuning-output
+            mountPath: /mnt/output
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: nni-web-ui
+          image: 'onepanel/nni-web-ui:0.17.0'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          ports:
+            - containerPort: 9000
+              name: nni
+        - name: tensorboard
+          image: 'tensorflow/tensorflow:2.3.0'
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output/tensorboard - /mnt/output is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+    - name: workflow-metrics-writer
+      inputs:
+        artifacts:
+          - name: best-metrics
+            path: /tmp/sys-metrics.json
+      script:
+        image: onepanel/python-sdk:v0.16.0
+        command: [python, '-u']
+        source: |
+          import os
+          import json
 
-        import onepanel.core.api
-        from onepanel.core.api.models.metric import Metric
-        from onepanel.core.api.rest import ApiException
-        from onepanel.core.api.models import Parameter
+          import onepanel.core.api
+          from onepanel.core.api.models.metric import Metric
+          from onepanel.core.api.rest import ApiException
+          from onepanel.core.api.models import Parameter
 
-        # Load Task A metrics
-        with open('/tmp/sys-metrics.json') as f:
-            metrics = json.load(f)
+          # Load Task A metrics
+          with open('/tmp/sys-metrics.json') as f:
+              metrics = json.load(f)
 
-        with open('/var/run/secrets/kubernetes.io/serviceaccount/token') as f:
-            token = f.read()
+          with open('/var/run/secrets/kubernetes.io/serviceaccount/token') as f:
+              token = f.read()
 
-        # Configure API authorization
-        configuration = onepanel.core.api.Configuration(
-            host = os.getenv('ONEPANEL_API_URL'),
-            api_key = {
-                'authorization': token
-            }
-        )
-        configuration.api_key_prefix['authorization'] = 'Bearer'
+          # Configure API authorization
+          configuration = onepanel.core.api.Configuration(
+              host = os.getenv('ONEPANEL_API_URL'),
+              api_key = {
+                  'authorization': token
+              }
+          )
+          configuration.api_key_prefix['authorization'] = 'Bearer'
 
-        # Call SDK method to save metrics
-        with onepanel.core.api.ApiClient(configuration) as api_client:
-            api_instance = onepanel.core.api.WorkflowServiceApi(api_client)
-            namespace = '{{workflow.namespace}}'
-            uid = '{{workflow.name}}'
-            body = onepanel.core.api.AddWorkflowExecutionsMetricsRequest()
-            body.metrics = metrics
-            try:
-                api_response = api_instance.add_workflow_execution_metrics(namespace, uid, body)
-                print('Metrics added.')
-            except ApiException as e:
-                print("Exception when calling WorkflowServiceApi->add_workflow_execution_metrics: %s\n" % e)
+          # Call SDK method to save metrics
+          with onepanel.core.api.ApiClient(configuration) as api_client:
+              api_instance = onepanel.core.api.WorkflowServiceApi(api_client)
+              namespace = '{{workflow.namespace}}'
+              uid = '{{workflow.name}}'
+              body = onepanel.core.api.AddWorkflowExecutionsMetricsRequest()
+              body.metrics = metrics
+              try:
+                  api_response = api_instance.add_workflow_execution_metrics(namespace, uid, body)
+                  print('Metrics added.')
+              except ApiException as e:
+                  print("Exception when calling WorkflowServiceApi->add_workflow_execution_metrics: %s\n" % e)

db/yaml/workflows/hyperparameter-tuning/20210118175809.yaml

@@ -1,194 +1,205 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/nni-hyperparameter-tuning/mnist/
-# Workflow Template example for hyperparameter tuning
-# Documentation: https://docs.onepanel.ai/docs/reference/workflows/hyperparameter-tuning
-#
-# Only change the fields marked with [CHANGE]
-entrypoint: main
-arguments:
-  parameters:
+metadata:
+  name: "Hyperparameter Tuning Example"
+  kind: Workflow
+  version: 20210118175809
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/nni-hyperparameter-tuning/mnist/"
+  deprecated: true
+  labels:
+    framework: tensorflow
+    tuner: TPE
+    "created-by": system
+spec:
+  # Workflow Template example for hyperparameter tuning
+  # Documentation: https://docs.onepanel.ai/docs/reference/workflows/hyperparameter-tuning
+  #
+  # Only change the fields marked with [CHANGE]
+  entrypoint: main
+  arguments:
+    parameters:
 
-    # [CHANGE] Path to your training/model architecture code repository
-    # Change this value and revision value to your code repository and branch respectively
-    - name: source
-      value: https://github.com/onepanelio/templates
+      # [CHANGE] Path to your training/model architecture code repository
+      # Change this value and revision value to your code repository and branch respectively
+      - name: source
+        value: https://github.com/onepanelio/templates
 
-    # [CHANGE] Revision is the branch or tag that you want to use
-    # You can change this to any tag or branch name in your repository
-    - name: revision
-      value: v0.18.0
+      # [CHANGE] Revision is the branch or tag that you want to use
+      # You can change this to any tag or branch name in your repository
+      - name: revision
+        value: v0.18.0
 
-    # [CHANGE] Default configuration for the NNI tuner
-    # See https://docs.onepanel.ai/docs/reference/workflows/hyperparameter-tuning#understanding-the-configurations
-    - name: config
-      displayName: Configuration
-      required: true
-      hint: NNI configuration
-      type: textarea.textarea
-      value: |-
-        authorName: Onepanel, Inc.
-        experimentName: MNIST TF v2.x
-        trialConcurrency: 1
-        maxExecDuration: 1h
-        maxTrialNum: 10
-        trainingServicePlatform: local
-        searchSpacePath: search_space.json
-        useAnnotation: false
-        tuner:
-          # gpuIndices: '0'           # uncomment and update to the GPU indices to assign this tuner
-          builtinTunerName: TPE       # choices: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
-          classArgs:
-            optimize_mode: maximize   # choices: maximize, minimize
-        trial:
-          command: python main.py --output /mnt/output
-          codeDir: .
-          # gpuNum: 1                 # uncomment and update to number of GPUs
+      # [CHANGE] Default configuration for the NNI tuner
+      # See https://docs.onepanel.ai/docs/reference/workflows/hyperparameter-tuning#understanding-the-configurations
+      - name: config
+        displayName: Configuration
+        required: true
+        hint: NNI configuration
+        type: textarea.textarea
+        value: |-
+          authorName: Onepanel, Inc.
+          experimentName: MNIST TF v2.x
+          trialConcurrency: 1
+          maxExecDuration: 1h
+          maxTrialNum: 10
+          trainingServicePlatform: local
+          searchSpacePath: search_space.json
+          useAnnotation: false
+          tuner:
+            # gpuIndices: '0'           # uncomment and update to the GPU indices to assign this tuner
+            builtinTunerName: TPE       # choices: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
+            classArgs:
+              optimize_mode: maximize   # choices: maximize, minimize
+          trial:
+            command: python main.py --output /mnt/output
+            codeDir: .
+            # gpuNum: 1                 # uncomment and update to number of GPUs
 
-    # [CHANGE] Search space configuration
-    # Change according to your hyperparameters and ranges
-    - name: search-space
-      displayName: Search space configuration
-      required: true
-      type: textarea.textarea
-      value: |-
-        {
-          "dropout_rate": { "_type": "uniform", "_value": [0.5, 0.9] },
-          "conv_size": { "_type": "choice", "_value": [2, 3, 5, 7] },
-          "hidden_size": { "_type": "choice", "_value": [124, 512, 1024] },
-          "batch_size": { "_type": "choice", "_value": [16, 32] },
-          "learning_rate": { "_type": "choice", "_value": [0.0001, 0.001, 0.01, 0.1] },
-          "epochs": { "_type": "choice", "_value": [10] }
-        }
+      # [CHANGE] Search space configuration
+      # Change according to your hyperparameters and ranges
+      - name: search-space
+        displayName: Search space configuration
+        required: true
+        type: textarea.textarea
+        value: |-
+          {
+            "dropout_rate": { "_type": "uniform", "_value": [0.5, 0.9] },
+            "conv_size": { "_type": "choice", "_value": [2, 3, 5, 7] },
+            "hidden_size": { "_type": "choice", "_value": [124, 512, 1024] },
+            "batch_size": { "_type": "choice", "_value": [16, 32] },
+            "learning_rate": { "_type": "choice", "_value": [0.0001, 0.001, 0.01, 0.1] },
+            "epochs": { "_type": "choice", "_value": [10] }
+          }
 
-    # Node pool dropdown (Node group in EKS)
-    # You can add more of these if you have additional tasks that can run on different node pools
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      required: true
+      # Node pool dropdown (Node group in EKS)
+      # You can add more of these if you have additional tasks that can run on different node pools
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        required: true
 
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: hyperparameter-tuning
-          template: hyperparameter-tuning
-        - name: metrics-writer
-          template: metrics-writer
-          dependencies: [hyperparameter-tuning]
-          arguments:
-            # Use sys-metrics artifact output from hyperparameter-tuning Task
-            # This writes the best metrics to the Workflow
-            artifacts:
-              - name: sys-metrics
-                from: "{{tasks.hyperparameter-tuning.outputs.artifacts.sys-metrics}}"
-  - name: hyperparameter-tuning
-    inputs:
-      artifacts:
-        - name: src
-          # Clone the above repository into '/mnt/data/src'
-          # See https://docs.onepanel.ai/docs/reference/workflows/artifacts#git for private repositories
-          git:
-            repo: '{{workflow.parameters.source}}'
-            revision: '{{workflow.parameters.revision}}'
-          path: /mnt/data/src
-        # [CHANGE] Path where config.yaml will be generated or already exists
-        # Update the path below so that config.yaml is written to the same directory as your main.py file
-        # Note that your source code is cloned to /mnt/data/src
-        - name: config
-          path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
-          raw:
-            data: '{{workflow.parameters.config}}'
-        # [CHANGE] Path where search_space.json will be generated or already exists
-        # Update the path below so that search_space.json is written to the same directory as your main.py file
-        # Note that your source code is cloned to /mnt/data/src
-        - name: search-space
-          path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/search_space.json
-          raw:
-            data: '{{workflow.parameters.search-space}}'
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    container:
-      image: onepanel/dl:0.17.0
-      command:
-        - sh
-        - -c
-      args:
-        # [CHANGE] Update the config path below to point to config.yaml path as described above
-        # Note that you can `pip install` additional tools here if necessary
-        - |
-          python -u /opt/onepanel/nni/start.py \
-            --config /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
-      workingDir: /mnt
-      volumeMounts:
-        - name: hyperparamtuning-data
-          mountPath: /mnt/data
-        - name: hyperparamtuning-output
-          mountPath: /mnt/output
-    nodeSelector:
-      {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: nni-web-ui
-        image: onepanel/nni-web-ui:0.17.0
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        ports:
-          - containerPort: 9000
-            name: nni
-      - name: tensorboard
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: hyperparameter-tuning
+            template: hyperparameter-tuning
+          - name: metrics-writer
+            template: metrics-writer
+            dependencies: [hyperparameter-tuning]
+            arguments:
+              # Use sys-metrics artifact output from hyperparameter-tuning Task
+              # This writes the best metrics to the Workflow
+              artifacts:
+                - name: sys-metrics
+                  from: "{{tasks.hyperparameter-tuning.outputs.artifacts.sys-metrics}}"
+    - name: hyperparameter-tuning
+      inputs:
+        artifacts:
+          - name: src
+            # Clone the above repository into '/mnt/data/src'
+            # See https://docs.onepanel.ai/docs/reference/workflows/artifacts#git for private repositories
+            git:
+              repo: '{{workflow.parameters.source}}'
+              revision: '{{workflow.parameters.revision}}'
+            path: /mnt/data/src
+          # [CHANGE] Path where config.yaml will be generated or already exists
+          # Update the path below so that config.yaml is written to the same directory as your main.py file
+          # Note that your source code is cloned to /mnt/data/src
+          - name: config
+            path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
+            raw:
+              data: '{{workflow.parameters.config}}'
+          # [CHANGE] Path where search_space.json will be generated or already exists
+          # Update the path below so that search_space.json is written to the same directory as your main.py file
+          # Note that your source code is cloned to /mnt/data/src
+          - name: search-space
+            path: /mnt/data/src/workflows/hyperparameter-tuning/mnist/search_space.json
+            raw:
+              data: '{{workflow.parameters.search-space}}'
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      container:
         image: onepanel/dl:0.17.0
         command:
           - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
+          - -c
         args:
-          # Read logs from /mnt/output/tensorboard - /mnt/output is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-  # Use the metrics-writer tasks to write best metrics to Workflow
-  - name: metrics-writer
-    inputs:
-      artifacts:
-        - name: sys-metrics
-          path: /tmp/sys-metrics.json
-        - git:
-            repo: https://github.com/onepanelio/templates.git
-            revision: v0.18.0
-          name: src
-          path: /mnt/src
-    container:
-      image: onepanel/python-sdk:v0.16.0
-      command:
-        - python
-        - -u
-      args:
-        - /mnt/src/tasks/metrics-writer/main.py
-        - --from_file=/tmp/sys-metrics.json
+          # [CHANGE] Update the config path below to point to config.yaml path as described above
+          # Note that you can `pip install` additional tools here if necessary
+          - |
+            python -u /opt/onepanel/nni/start.py \
+              --config /mnt/data/src/workflows/hyperparameter-tuning/mnist/config.yaml
+        workingDir: /mnt
+        volumeMounts:
+          - name: hyperparamtuning-data
+            mountPath: /mnt/data
+          - name: hyperparamtuning-output
+            mountPath: /mnt/output
+      nodeSelector:
+        "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: nni-web-ui
+          image: onepanel/nni-web-ui:0.17.0
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          ports:
+            - containerPort: 9000
+              name: nni
+        - name: tensorboard
+          image: onepanel/dl:0.17.0
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output/tensorboard - /mnt/output is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+    # Use the metrics-writer tasks to write best metrics to Workflow
+    - name: metrics-writer
+      inputs:
+        artifacts:
+          - name: sys-metrics
+            path: /tmp/sys-metrics.json
+          - git:
+              repo: https://github.com/onepanelio/templates.git
+              revision: v0.18.0
+            name: src
+            path: /mnt/src
+      container:
+        image: onepanel/python-sdk:v0.16.0
+        command:
+          - python
+          - -u
+        args:
+          - /mnt/src/tasks/metrics-writer/main.py
+          - --from_file=/tmp/sys-metrics.json
 
-# [CHANGE] Volumes that will mount to /mnt/data (annotated data) and /mnt/output (models, checkpoints, logs)
-# Update this depending on your annotation data, model, checkpoint, logs, etc. sizes
-# Example values: 250Mi, 500Gi, 1Ti
-volumeClaimTemplates:
-  - metadata:
-      name: hyperparamtuning-data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 20Gi
-  - metadata:
-      name: hyperparamtuning-output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 20Gi
+  # [CHANGE] Volumes that will mount to /mnt/data (annotated data) and /mnt/output (models, checkpoints, logs)
+  # Update this depending on your annotation data, model, checkpoint, logs, etc. sizes
+  # Example values: 250Mi, 500Gi, 1Ti
+  volumeClaimTemplates:
+    - metadata:
+        name: hyperparamtuning-data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 20Gi
+    - metadata:
+        name: hyperparamtuning-output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 20Gi

db/yaml/workflows/maskrcnn-training/20200812104328.yaml

@@ -0,0 +1,197 @@
+metadata:
+  name: "MaskRCNN Training"
+  kind: Workflow
+  version: 20200812104328
+  action: create
+  labels:
+    "used-by": "cvat"
+    "created-by": "system"
+spec:
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/onepanelio/Mask_RCNN.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
+
+      - name: sys-annotation-path
+        value: annotation-dump/sample_dataset
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        displayName: Dataset path
+        visibility: private
+
+      - name: sys-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
+
+      - name: sys-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
+
+      - name: sys-num-classes
+        displayName: Number of classes
+        hint: Number of classes (i.e in CVAT taks) + 1 for background
+        value: '81'
+        visibility: private
+
+      - name: extras
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        value: |-
+          stage-1-epochs=1    #  Epochs for network heads
+          stage-2-epochs=2    #  Epochs for finetune layers
+          stage-3-epochs=3    #  Epochs for all layers
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters."
+
+      - name: dump-format
+        type: select.select
+        value: cvat_coco
+        displayName: CVAT dump format
+        visibility: public
+        options:
+          - name: 'MS COCO'
+            value: 'cvat_coco'
+          - name: 'TF Detection API'
+            value: 'cvat_tfrecord'
+
+      - name: tf-image
+        visibility: public
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        visibility: public
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+      name: main
+    - container:
+        args:
+          - |
+            apt-get update \
+            && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
+            && pip install -r requirements.txt \
+            && pip install boto3 pyyaml google-cloud-storage \
+            && git clone https://github.com/waleedka/coco \
+            && cd coco/PythonAPI \
+            && python setup.py build_ext install \
+            && rm -rf build \
+            && cd ../../ \
+            && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
+            && python setup.py install && ls \
+            && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
+              --model=workflow_maskrcnn \
+              --extras="{{workflow.parameters.extras}}"  \
+              --ref_model_path="{{workflow.parameters.sys-finetune-checkpoint}}"  \
+              --num_classes="{{workflow.parameters.sys-num-classes}}" \
+            && cd /mnt/src/ \
+            && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.sys-annotation-path}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: "no-boto"
+            name: src
+            path: /mnt/src
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.sys-output-path}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/maskrcnn-training/20200824095513.yaml

@@ -0,0 +1,191 @@
+metadata:
+  name: "MaskRCNN Training"
+  kind: Workflow
+  version: 20200824095513
+  action: update
+  labels:
+    "used-by": "cvat"
+    "created-by": "system"
+spec:
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/onepanelio/Mask_RCNN.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
+
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        displayName: Dataset path
+        visibility: private
+
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
+
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
+
+      - name: cvat-num-classes
+        displayName: Number of classes
+        hint: Number of classes (i.e in CVAT taks) + 1 for background
+        value: '81'
+        visibility: private
+
+      - name: hyperparameters
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        value: |-
+          stage-1-epochs=1    #  Epochs for network heads
+          stage-2-epochs=2    #  Epochs for finetune layers
+          stage-3-epochs=3    #  Epochs for all layers
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+
+      - name: dump-format
+        value: cvat_coco
+        displayName: CVAT dump format
+        visibility: public
+
+      - name: tf-image
+        visibility: public
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        visibility: public
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+      name: main
+    - container:
+        args:
+          - |
+            apt-get update \
+            && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
+            && pip install -r requirements.txt \
+            && pip install boto3 pyyaml google-cloud-storage \
+            && git clone https://github.com/waleedka/coco \
+            && cd coco/PythonAPI \
+            && python setup.py build_ext install \
+            && rm -rf build \
+            && cd ../../ \
+            && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
+            && python setup.py install && ls \
+            && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
+              --model=workflow_maskrcnn \
+              --extras="{{workflow.parameters.hyperparameters}}"  \
+              --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+            && cd /mnt/src/ \
+            && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: "no-boto"
+            name: src
+            path: /mnt/src
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/maskrcnn-training/20201115145814.yaml

@@ -1,190 +1,199 @@
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/onepanelio/Mask_RCNN.git
-      displayName: Model source code
-      type: hidden
-      visibility: private
+metadata:
+  name: "MaskRCNN Training"
+  kind: Workflow
+  version: 20201115145814
+  action: update
+  labels:
+    "used-by": "cvat"
+    "created-by": "system"
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/onepanelio/Mask_RCNN.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
 
-    - name: cvat-annotation-path
-      value: annotation-dump/sample_dataset
-      hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
-      displayName: Dataset path
-      visibility: private
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        displayName: Dataset path
+        visibility: private
 
-    - name: cvat-output-path
-      value: workflow-data/output/sample_output
-      hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
-      displayName: Workflow output path
-      visibility: private
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: cvat-num-classes
-      displayName: Number of classes
-      hint: Number of classes (i.e in CVAT taks) + 1 for background
-      value: '81'
-      visibility: private
+      - name: cvat-num-classes
+        displayName: Number of classes
+        hint: Number of classes (i.e in CVAT taks) + 1 for background
+        value: '81'
+        visibility: private
 
-    - name: hyperparameters
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      value: |-
-        stage-1-epochs=1    #  Epochs for network heads
-        stage-2-epochs=2    #  Epochs for finetune layers
-        stage-3-epochs=3    #  Epochs for all layers
-      hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+      - name: hyperparameters
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        value: |-
+          stage-1-epochs=1    #  Epochs for network heads
+          stage-2-epochs=2    #  Epochs for finetune layers
+          stage-3-epochs=3    #  Epochs for all layers
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
 
-    - name: dump-format
-      value: cvat_coco
-      displayName: CVAT dump format
-      visibility: public
+      - name: dump-format
+        value: cvat_coco
+        displayName: CVAT dump format
+        visibility: public
 
-    - name: tf-image
-      visibility: public
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        visibility: public
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.select
-      visibility: public
-      name: sys-node-pool
-      value: Standard_D4s_v3
-      required: true
-      options:
-        - name: 'CPU: 2, RAM: 8GB'
-          value: Standard_D2s_v3
-        - name: 'CPU: 4, RAM: 16GB'
-          value: Standard_D4s_v3
-        - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
-          value: Standard_NC6
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: tensorflow
-    # Uncomment the lines below if you want to send Slack notifications
-    #    - arguments:
-    #        artifacts:
-    #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
-    #          name: metrics
-    #        parameters:
-    #        - name: status
-    #          value: '{{tasks.train-model.status}}'
-    #      dependencies:
-    #      - train-model
-    #      name: notify-in-slack
-    #      template: slack-notify-success
-  - name: tensorflow
-    container:
-      args:
-        - |
-          apt-get update \
-          && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
-          && pip install -r requirements.txt \
-          && pip install boto3 pyyaml google-cloud-storage \
-          && git clone https://github.com/waleedka/coco \
-          && cd coco/PythonAPI \
-          && python setup.py build_ext install \
-          && rm -rf build \
-          && cd ../../ \
-          && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
-          && python setup.py install && ls \
-          && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
-            --model=workflow_maskrcnn \
-            --extras="{{workflow.parameters.hyperparameters}}"  \
-            --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-          && cd /mnt/src/ \
-          && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
-        command: [sh, -c]
-        tty: true
-        args: ["tensorboard --logdir /mnt/output/"]
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
-        - git:
-            repo: '{{workflow.parameters.source}}'
-            revision: "no-boto"
-          name: src
-          path: /mnt/src
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
-# Uncomment the lines below if you want to send Slack notifications
-#- container:
-#    args:
-#    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
-#      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
-#      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
-#    command:
-#    - sh
-#    - -c
-#    image: technosophos/slack-notify
-#  inputs:
-#    artifacts:
-#    - name: metrics
-#      optional: true
-#      path: /tmp/metrics.json
-#    parameters:
-#    - name: status
-#  name: slack-notify-success
-volumeClaimTemplates:
-  - metadata:
-      creationTimestamp: null
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      creationTimestamp: null
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        visibility: public
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+    - name: tensorflow
+      container:
+        args:
+          - |
+            apt-get update \
+            && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
+            && pip install -r requirements.txt \
+            && pip install boto3 pyyaml google-cloud-storage \
+            && git clone https://github.com/waleedka/coco \
+            && cd coco/PythonAPI \
+            && python setup.py build_ext install \
+            && rm -rf build \
+            && cd ../../ \
+            && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
+            && python setup.py install && ls \
+            && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
+              --model=workflow_maskrcnn \
+              --extras="{{workflow.parameters.hyperparameters}}"  \
+              --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+            && cd /mnt/src/ \
+            && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command: [sh, -c]
+          tty: true
+          args: ["tensorboard --logdir /mnt/output/"]
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: "no-boto"
+            name: src
+            path: /mnt/src
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/maskrcnn-training/20201208155115.yaml

@@ -1,192 +1,201 @@
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/onepanelio/Mask_RCNN.git
-      displayName: Model source code
-      type: hidden
-      visibility: private
+metadata:
+  name: "MaskRCNN Training"
+  kind: Workflow
+  version: 20201208155115
+  action: update
+  labels:
+    "used-by": "cvat"
+    "created-by": "system"
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/onepanelio/Mask_RCNN.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
 
-    - name: cvat-annotation-path
-      value: annotation-dump/sample_dataset
-      hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
-      displayName: Dataset path
-      visibility: private
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        displayName: Dataset path
+        visibility: private
 
-    - name: cvat-output-path
-      value: workflow-data/output/sample_output
-      hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
-      displayName: Workflow output path
-      visibility: private
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: cvat-num-classes
-      displayName: Number of classes
-      hint: Number of classes (i.e in CVAT taks) + 1 for background
-      value: '81'
-      visibility: private
+      - name: cvat-num-classes
+        displayName: Number of classes
+        hint: Number of classes (i.e in CVAT taks) + 1 for background
+        value: '81'
+        visibility: private
 
-    - name: hyperparameters
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      value: |-
-        stage-1-epochs=1    #  Epochs for network heads
-        stage-2-epochs=2    #  Epochs for finetune layers
-        stage-3-epochs=3    #  Epochs for all layers
-      hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+      - name: hyperparameters
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        value: |-
+          stage-1-epochs=1    #  Epochs for network heads
+          stage-2-epochs=2    #  Epochs for finetune layers
+          stage-3-epochs=3    #  Epochs for all layers
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
 
-    - name: dump-format
-      value: cvat_coco
-      displayName: CVAT dump format
-      visibility: public
+      - name: dump-format
+        value: cvat_coco
+        displayName: CVAT dump format
+        visibility: public
 
-    - name: tf-image
-      visibility: public
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        visibility: public
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.select
-      visibility: public
-      name: sys-node-pool
-      value: Standard_D4s_v3
-      required: true
-      options:
-        - name: 'CPU: 2, RAM: 8GB'
-          value: Standard_D2s_v3
-        - name: 'CPU: 4, RAM: 16GB'
-          value: Standard_D4s_v3
-        - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
-          value: Standard_NC6
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: tensorflow
-    # Uncomment the lines below if you want to send Slack notifications
-    #    - arguments:
-    #        artifacts:
-    #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
-    #          name: metrics
-    #        parameters:
-    #        - name: status
-    #          value: '{{tasks.train-model.status}}'
-    #      dependencies:
-    #      - train-model
-    #      name: notify-in-slack
-    #      template: slack-notify-success
-  - name: tensorflow
-    container:
-      args:
-        - |
-          apt-get update \
-          && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
-          && pip install -r requirements.txt \
-          && pip install boto3 pyyaml google-cloud-storage \
-          && git clone https://github.com/waleedka/coco \
-          && cd coco/PythonAPI \
-          && python setup.py build_ext install \
-          && rm -rf build \
-          && cd ../../ \
-          && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
-          && python setup.py install && ls \
-          && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
-            --model=workflow_maskrcnn \
-            --extras="{{workflow.parameters.hyperparameters}}"  \
-            --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-          && cd /mnt/src/ \
-          && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
-        command: [sh, -c]
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args: ["tensorboard --logdir /mnt/output/"]
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
-        - git:
-            repo: '{{workflow.parameters.source}}'
-            revision: "no-boto"
-          name: src
-          path: /mnt/src
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
-# Uncomment the lines below if you want to send Slack notifications
-#- container:
-#    args:
-#    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
-#      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
-#      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
-#    command:
-#    - sh
-#    - -c
-#    image: technosophos/slack-notify
-#  inputs:
-#    artifacts:
-#    - name: metrics
-#      optional: true
-#      path: /tmp/metrics.json
-#    parameters:
-#    - name: status
-#  name: slack-notify-success
-volumeClaimTemplates:
-  - metadata:
-      creationTimestamp: null
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      creationTimestamp: null
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        visibility: public
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+    - name: tensorflow
+      container:
+        args:
+          - |
+            apt-get update \
+            && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
+            && pip install -r requirements.txt \
+            && pip install boto3 pyyaml google-cloud-storage \
+            && git clone https://github.com/waleedka/coco \
+            && cd coco/PythonAPI \
+            && python setup.py build_ext install \
+            && rm -rf build \
+            && cd ../../ \
+            && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
+            && python setup.py install && ls \
+            && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
+              --model=workflow_maskrcnn \
+              --extras="{{workflow.parameters.hyperparameters}}"  \
+              --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+            && cd /mnt/src/ \
+            && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command: [sh, -c]
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args: ["tensorboard --logdir /mnt/output/"]
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: "no-boto"
+            name: src
+            path: /mnt/src
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/maskrcnn-training/20201221195937.yaml

@@ -1,149 +1,158 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/maskrcnn-training/
-arguments:
-  parameters:
-    - name: cvat-annotation-path
-      value: annotation-dump/sample_dataset
-      hint: Path to annotated data in default object storage. In CVAT, this parameter will be pre-populated.
-      displayName: Dataset path
-      visibility: internal
+metadata:
+  name: "MaskRCNN Training"
+  kind: Workflow
+  version: 20201221195937
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/maskrcnn-training/"
+  labels:
+    "used-by": "cvat"
+    "created-by": "system"
+spec:
+  arguments:
+    parameters:
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        hint: Path to annotated data in default object storage. In CVAT, this parameter will be pre-populated.
+        displayName: Dataset path
+        visibility: internal
 
-    - name: cvat-output-path
-      value: workflow-data/output/sample_output
-      hint: Path to store output artifacts in default object storage. In CVAT, this parameter will be pre-populated.
-      displayName: Workflow output path
-      visibility: internal
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage. In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: internal
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: cvat-num-classes
-      displayName: Number of classes
-      hint: Number of classes + 1 for background. In CVAT, this parameter will be pre-populated.
-      value: '11'
-      visibility: internal
+      - name: cvat-num-classes
+        displayName: Number of classes
+        hint: Number of classes + 1 for background. In CVAT, this parameter will be pre-populated.
+        value: '11'
+        visibility: internal
 
-    - name: hyperparameters
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      value: |-
-        stage-1-epochs=1    #  Epochs for network heads
-        stage-2-epochs=2    #  Epochs for finetune layers
-        stage-3-epochs=3    #  Epochs for all layers
-      hint: "See <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#maskrcnn-hyperparameters' target='_blank'>documentation</a> for more information on parameters."
+      - name: hyperparameters
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        value: |-
+          stage-1-epochs=1    #  Epochs for network heads
+          stage-2-epochs=2    #  Epochs for finetune layers
+          stage-3-epochs=3    #  Epochs for all layers
+        hint: "See <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#maskrcnn-hyperparameters' target='_blank'>documentation</a> for more information on parameters."
 
-    - name: dump-format
-      value: cvat_coco
-      displayName: CVAT dump format
-      visibility: public
+      - name: dump-format
+        value: cvat_coco
+        displayName: CVAT dump format
+        visibility: public
 
-    - name: tf-image
-      visibility: public
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        visibility: public
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      visibility: public
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      required: true
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        visibility: public
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        required: true
 
-entrypoint: main
-templates:
-  - dag:
-      tasks:
-        - name: train-model
-          template: tensorflow
-    name: main
-  - container:
-      args:
-        - |
-          apt-get update \
-          && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
-          && pip install -r requirements.txt \
-          && pip install boto3 pyyaml google-cloud-storage \
-          && git clone https://github.com/waleedka/coco \
-          && cd coco/PythonAPI \
-          && python setup.py build_ext install \
-          && rm -rf build \
-          && cd ../../ \
-          && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
-          && python setup.py install && ls \
-          && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
-            --model=workflow_maskrcnn \
-            --extras="{{workflow.parameters.hyperparameters}}"  \
-            --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-          && cd /mnt/src/ \
-          && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
-        command: [ sh, -c ]
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args: [ "tensorboard --logdir /mnt/output/" ]
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          s3:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
-        - git:
-            repo: 'https://github.com/onepanelio/Mask_RCNN.git'
-            revision: 'no-boto'
-          name: src
-          path: /mnt/src
-    name: tensorflow
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-          s3:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
-volumeClaimTemplates:
-  - metadata:
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      name: main
+    - container:
+        args:
+          - |
+            apt-get update \
+            && apt-get install -y git wget libglib2.0-0 libsm6 libxext6 libxrender-dev \
+            && pip install -r requirements.txt \
+            && pip install boto3 pyyaml google-cloud-storage \
+            && git clone https://github.com/waleedka/coco \
+            && cd coco/PythonAPI \
+            && python setup.py build_ext install \
+            && rm -rf build \
+            && cd ../../ \
+            && wget https://github.com/matterport/Mask_RCNN/releases/download/v2.0/mask_rcnn_coco.h5 \
+            && python setup.py install && ls \
+            && python samples/coco/cvat.py train --dataset=/mnt/data/datasets \
+              --model=workflow_maskrcnn \
+              --extras="{{workflow.parameters.hyperparameters}}"  \
+              --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+            && cd /mnt/src/ \
+            && python prepare_dataset.py /mnt/data/datasets/annotations/instances_default.json
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command: [ sh, -c ]
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args: [ "tensorboard --logdir /mnt/output/" ]
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            s3:
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - git:
+              repo: 'https://github.com/onepanelio/Mask_RCNN.git'
+              revision: 'no-boto'
+            name: src
+            path: /mnt/src
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            s3:
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  volumeClaimTemplates:
+    - metadata:
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/maskrcnn-training/20210118175809.yaml

@@ -1,208 +1,217 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/maskrcnn-training/
-arguments:
-  parameters:
-    - name: cvat-annotation-path
-      value: 'artifacts/{{workflow.namespace}}/annotations/'
-      hint: Path to annotated data (COCO format) in default object storage. In CVAT, this parameter will be pre-populated.
-      displayName: Dataset path
-      visibility: internal
+metadata:
+  name: "MaskRCNN Training"
+  kind: Workflow
+  version: 20210118175809
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/maskrcnn-training/"
+  labels:
+    "used-by": "cvat"
+    "created-by": "system"
+spec:
+  arguments:
+    parameters:
+      - name: cvat-annotation-path
+        value: 'artifacts/{{workflow.namespace}}/annotations/'
+        hint: Path to annotated data (COCO format) in default object storage. In CVAT, this parameter will be pre-populated.
+        displayName: Dataset path
+        visibility: internal
 
-    - name: val-split
-      value: 10
-      displayName: Validation split size
-      type: input.number
-      visibility: public
-      hint: Enter validation set size in percentage of full dataset. (0 - 100)
+      - name: val-split
+        value: 10
+        displayName: Validation split size
+        type: input.number
+        visibility: public
+        hint: Enter validation set size in percentage of full dataset. (0 - 100)
 
-    - name: num-augmentation-cycles
-      value: 1
-      displayName: Number of augmentation cycles
-      type: input.number
-      visibility: public
-      hint: Number of augmentation cycles, zero means no data augmentation
+      - name: num-augmentation-cycles
+        value: 1
+        displayName: Number of augmentation cycles
+        type: input.number
+        visibility: public
+        hint: Number of augmentation cycles, zero means no data augmentation
 
-    - name: preprocessing-parameters
-      value: |-
-        RandomBrightnessContrast:
-            p: 0.2
-        GaussianBlur:
-            p: 0.3
-        GaussNoise:
-            p: 0.4
-        HorizontalFlip:
-            p: 0.5
-        VerticalFlip:
-            p: 0.3
-      displayName: Preprocessing parameters
-      visibility: public
-      type: textarea.textarea
-      hint: 'See <a href="https://albumentations.ai/docs/api_reference/augmentations/transforms/" target="_blank">documentation</a> for more information on parameters.'
+      - name: preprocessing-parameters
+        value: |-
+          RandomBrightnessContrast:
+              p: 0.2
+          GaussianBlur:
+              p: 0.3
+          GaussNoise:
+              p: 0.4
+          HorizontalFlip:
+              p: 0.5
+          VerticalFlip:
+              p: 0.3
+        displayName: Preprocessing parameters
+        visibility: public
+        type: textarea.textarea
+        hint: 'See <a href="https://albumentations.ai/docs/api_reference/augmentations/transforms/" target="_blank">documentation</a> for more information on parameters.'
 
-    - name: cvat-num-classes
-      displayName: Number of classes
-      hint: Number of classes. In CVAT, this parameter will be pre-populated.
-      value: '10'
-      visibility: internal
+      - name: cvat-num-classes
+        displayName: Number of classes
+        hint: Number of classes. In CVAT, this parameter will be pre-populated.
+        value: '10'
+        visibility: internal
 
-    - name: hyperparameters
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      value: |-
-        stage_1_epochs: 1    #  Epochs for network heads
-        stage_2_epochs: 1    #  Epochs for finetune layers
-        stage_3_epochs: 1    #  Epochs for all layers
-        num_steps: 1000     #  Num steps per epoch
-      hint: 'See <a href="https://docs.onepanel.ai/docs/reference/workflows/training#maskrcnn-hyperparameters" target="_blank">documentation</a> for more information on parameters.'
+      - name: hyperparameters
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        value: |-
+          stage_1_epochs: 1    #  Epochs for network heads
+          stage_2_epochs: 1    #  Epochs for finetune layers
+          stage_3_epochs: 1    #  Epochs for all layers
+          num_steps: 1000     #  Num steps per epoch
+        hint: 'See <a href="https://docs.onepanel.ai/docs/reference/workflows/training#maskrcnn-hyperparameters" target="_blank">documentation</a> for more information on parameters.'
 
-    - name: dump-format
-      value: cvat_coco
-      displayName: CVAT dump format
-      visibility: private
+      - name: dump-format
+        value: cvat_coco
+        displayName: CVAT dump format
+        visibility: private
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Path to the last fine-tune checkpoint for this model in default object storage. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Path to the last fine-tune checkpoint for this model in default object storage. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      visibility: public
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      required: true
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        visibility: public
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        required: true
 
-entrypoint: main
-templates:
-  - dag:
-      tasks:
-        - name: preprocessing
-          template: preprocessing
-        - name: train-model
-          template: tensorflow
-          dependencies: [preprocessing]
-          arguments:
-            artifacts:
-              - name: data
-                from: "{{tasks.preprocessing.outputs.artifacts.processed-data}}"
-    name: main
-  - container:
-      args:
-        - |
-          pip install pycocotools scikit-image==0.16.2 && \
-          cd /mnt/src/train/workflows/maskrcnn-training && \
-          python -u main.py train --dataset=/mnt/data/datasets/train_set/ \
-            --model=workflow_maskrcnn \
-            --extras="{{workflow.parameters.hyperparameters}}"  \
-            --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-            --val_dataset=/mnt/data/datasets/eval_set/ \
-            --use_validation=True
-      command:
-        - sh
-        - -c
-      image: onepanel/dl:v0.20.0
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: processed-data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    sidecars:
-      - name: tensorboard
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: preprocessing
+            template: preprocessing
+          - name: train-model
+            template: tensorflow
+            dependencies: [preprocessing]
+            arguments:
+              artifacts:
+                - name: data
+                  from: "{{tasks.preprocessing.outputs.artifacts.processed-data}}"
+      name: main
+    - container:
+        args:
+          - |
+            pip install pycocotools scikit-image==0.16.2 && \
+            cd /mnt/src/train/workflows/maskrcnn-training && \
+            python -u main.py train --dataset=/mnt/data/datasets/train_set/ \
+              --model=workflow_maskrcnn \
+              --extras="{{workflow.parameters.hyperparameters}}"  \
+              --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}"  \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+              --val_dataset=/mnt/data/datasets/eval_set/ \
+              --use_validation=True
+        command:
+          - sh
+          - -c
         image: onepanel/dl:v0.20.0
-        command: [ sh, -c ]
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args: [ "tensorboard --logdir /mnt/output/tensorboard" ]
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-    nodeSelector:
-        {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-        - name: models
-          path: /mnt/data/models/
-          optional: true
-          s3:
-            key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
-        - git:
-            repo: https://github.com/onepanelio/templates.git
-            revision: v0.18.0
-          name: src
-          path: /mnt/src/train
-    name: tensorflow
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-  - container:
-      args:
-        - |
-          pip install pycocotools && \
-          cd /mnt/src/preprocessing/workflows/albumentations-preprocessing && \
-          python -u main.py \
-            --data_aug_params="{{workflow.parameters.preprocessing-parameters}}" \
-            --val_split={{workflow.parameters.val-split}} \
-            --aug_steps={{workflow.parameters.num-augmentation-cycles}}
-      command:
-        - sh
-        - -c
-      image: onepanel/dl:v0.20.0
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: processed-data
-      workingDir: /mnt/src
-    nodeSelector:
-        {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          s3:
-            key: '{{workflow.parameters.cvat-annotation-path}}'
-        - git:
-            repo: https://github.com/onepanelio/templates.git
-            revision: v0.18.0
-          name: src
-          path: /mnt/src/preprocessing
-    name: preprocessing
-    outputs:
-      artifacts:
-        - name: processed-data
-          optional: true
-          path: /mnt/output
-volumeClaimTemplates:
-  - metadata:
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      name: processed-data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: processed-data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      sidecars:
+        - name: tensorboard
+          image: onepanel/dl:v0.20.0
+          command: [ sh, -c ]
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args: [ "tensorboard --logdir /mnt/output/tensorboard" ]
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+      nodeSelector:
+          "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            s3:
+              key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
+          - git:
+              repo: https://github.com/onepanelio/templates.git
+              revision: v0.18.0
+            name: src
+            path: /mnt/src/train
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+    - container:
+        args:
+          - |
+            pip install pycocotools && \
+            cd /mnt/src/preprocessing/workflows/albumentations-preprocessing && \
+            python -u main.py \
+              --data_aug_params="{{workflow.parameters.preprocessing-parameters}}" \
+              --val_split={{workflow.parameters.val-split}} \
+              --aug_steps={{workflow.parameters.num-augmentation-cycles}}
+        command:
+          - sh
+          - -c
+        image: onepanel/dl:v0.20.0
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: processed-data
+        workingDir: /mnt/src
+      nodeSelector:
+          "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            s3:
+              key: '{{workflow.parameters.cvat-annotation-path}}'
+          - git:
+              repo: https://github.com/onepanelio/templates.git
+              revision: v0.18.0
+            name: src
+            path: /mnt/src/preprocessing
+      name: preprocessing
+      outputs:
+        artifacts:
+          - name: processed-data
+            optional: true
+            path: /mnt/output
+  volumeClaimTemplates:
+    - metadata:
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        name: processed-data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/pytorch-mnist-training/20200605090509.yaml

@@ -1,75 +1,84 @@
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/onepanelio/pytorch-examples.git
-    - name: command
-      value: "python mnist/main.py --epochs=1"
-volumeClaimTemplates:
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: pytorch
-  # Uncomment section below to send metrics to Slack
-  #      - name: notify-in-slack
-  #        dependencies: [train-model]
-  #        template: slack-notify-success
-  #        arguments:
-  #          parameters:
-  #          - name: status
-  #            value: "{{tasks.train-model.status}}"
-  #          artifacts:
-  #          - name: metrics
-  #            from: "{{tasks.train-model.outputs.artifacts.sys-metrics}}"
-  - name: pytorch
-    inputs:
-      artifacts:
-        - name: src
-          path: /mnt/src
-          git:
-            repo: "{{workflow.parameters.source}}"
-    outputs:
-      artifacts:
-        - name: model
-          path: /mnt/output
-          optional: true
-          archive:
-            none: {}
-    container:
-      image: pytorch/pytorch:latest
-      command: [sh,-c]
-      args: ["{{workflow.parameters.command}}"]
-      workingDir: /mnt/src
-      volumeMounts:
-        - name: data
-          mountPath: /mnt/data
-        - name: output
-          mountPath: /mnt/output
-  - name: slack-notify-success
-    container:
-      image: technosophos/slack-notify
-      command: [sh,-c]
-      args: ['SLACK_USERNAME=Worker SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify']
-    inputs:
-      parameters:
-        - name: status
-      artifacts:
-        - name: metrics
-          path: /tmp/metrics.json
-          optional: true
+metadata:
+  name: "PyTorch Training"
+  kind: Workflow
+  version: 20200605090509
+  action: create
+  labels:
+    "created-by": "system"
+    framework: pytorch
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/onepanelio/pytorch-examples.git
+      - name: command
+        value: "python mnist/main.py --epochs=1"
+  volumeClaimTemplates:
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: pytorch
+    # Uncomment section below to send metrics to Slack
+    #      - name: notify-in-slack
+    #        dependencies: [train-model]
+    #        template: slack-notify-success
+    #        arguments:
+    #          parameters:
+    #          - name: status
+    #            value: "{{tasks.train-model.status}}"
+    #          artifacts:
+    #          - name: metrics
+    #            from: "{{tasks.train-model.outputs.artifacts.sys-metrics}}"
+    - name: pytorch
+      inputs:
+        artifacts:
+          - name: src
+            path: /mnt/src
+            git:
+              repo: "{{workflow.parameters.source}}"
+      outputs:
+        artifacts:
+          - name: model
+            path: /mnt/output
+            optional: true
+            archive:
+              none: {}
+      container:
+        image: pytorch/pytorch:latest
+        command: [sh,-c]
+        args: ["{{workflow.parameters.command}}"]
+        workingDir: /mnt/src
+        volumeMounts:
+          - name: data
+            mountPath: /mnt/data
+          - name: output
+            mountPath: /mnt/output
+    - name: slack-notify-success
+      container:
+        image: technosophos/slack-notify
+        command: [sh,-c]
+        args: ['SLACK_USERNAME=Worker SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify']
+      inputs:
+        parameters:
+          - name: status
+        artifacts:
+          - name: metrics
+            path: /tmp/metrics.json
+            optional: true

db/yaml/workflows/pytorch-mnist-training/20201221194344.yaml

@@ -1,207 +1,216 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/
-arguments:
-  parameters:
-    - name: epochs
-      value: '10'
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
-entrypoint: main
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: train-model
-  - name: train-model
-    # Indicates that we want to push files in /mnt/output to object storage
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    script:
-      image: onepanel/dl:0.17.0
-      command:
-        - python
-        - '-u'
-      source: |
-        import json
-        import torch
-        import torch.nn as nn
-        import torch.nn.functional as F
-        import torch.optim as optim
-        from torchvision import datasets, transforms
-        from torch.optim.lr_scheduler import StepLR
-        from torch.utils.tensorboard import SummaryWriter
-
-
-        class Net(nn.Module):
-            def __init__(self):
-                super(Net, self).__init__()
-                self.conv1 = nn.Conv2d(1, 32, 3, 1)
-                self.conv2 = nn.Conv2d(32, 64, 3, 1)
-                self.dropout1 = nn.Dropout(0.25)
-                self.dropout2 = nn.Dropout(0.5)
-                self.fc1 = nn.Linear(9216, 128)
-                self.fc2 = nn.Linear(128, 10)
-
-            def forward(self, x):
-                x = self.conv1(x)
-                x = F.relu(x)
-                x = self.conv2(x)
-                x = F.relu(x)
-                x = F.max_pool2d(x, 2)
-                x = self.dropout1(x)
-                x = torch.flatten(x, 1)
-                x = self.fc1(x)
-                x = F.relu(x)
-                x = self.dropout2(x)
-                x = self.fc2(x)
-                output = F.log_softmax(x, dim=1)
-                return output
-
-
-        def train(model, device, train_loader, optimizer, epoch, batch_size, writer):
-            model.train()
-            for batch_idx, (data, target) in enumerate(train_loader):
-                data, target = data.to(device), target.to(device)
-                optimizer.zero_grad()
-                output = model(data)
-                loss = F.nll_loss(output, target)
-                loss.backward()
-                optimizer.step()
-                if batch_idx % 10 == 0:
-                    print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
-                        epoch, batch_idx * len(data), len(train_loader.dataset),
-                        100. * batch_idx / len(train_loader), loss.item()))
-
-                    writer.add_scalar('training loss', loss.item(), epoch)
-
-
-        def test(model, device, test_loader, epoch, writer):
-            model.eval()
-            test_loss = 0
-            correct = 0
-            with torch.no_grad():
-                for data, target in test_loader:
-                    data, target = data.to(device), target.to(device)
-                    output = model(data)
-                    test_loss += F.nll_loss(output, target, reduction='sum').item()  # sum up batch loss
-                    pred = output.argmax(dim=1, keepdim=True)  # get the index of the max log-probability
-                    correct += pred.eq(target.view_as(pred)).sum().item()
-
-            loss = test_loss / len(test_loader.dataset)
-            accuracy = correct / len(test_loader.dataset)
-
-            print('\nTest set: Average loss: {}, Accuracy: {}\n'.format(
-                loss, accuracy))
-
-             # Store metrics for this task
-            metrics = [
-              {'name': 'accuracy', 'value': accuracy},
-              {'name': 'loss', 'value': loss}
-            ]
-            with open('/tmp/sys-metrics.json', 'w') as f:
-              json.dump(metrics, f)
-
-
-        def main(params):
-            writer = SummaryWriter(log_dir='/mnt/output/tensorboard')
-
-            use_cuda = torch.cuda.is_available()
-
-            torch.manual_seed(params['seed'])
-
-            device = torch.device('cuda' if use_cuda else 'cpu')
-
-            train_kwargs = {'batch_size': params['batch_size']}
-            test_kwargs = {'batch_size': params['test_batch_size']}
-            if use_cuda:
-                cuda_kwargs = {'num_workers': 1,
-                               'pin_memory': True,
-                               'shuffle': True}
-                train_kwargs.update(cuda_kwargs)
-                test_kwargs.update(cuda_kwargs)
-
-            transform=transforms.Compose([
-                transforms.ToTensor(),
-                transforms.Normalize((0.1307,), (0.3081,))
-            ])
-            dataset1 = datasets.MNIST('/mnt/data', train=True, download=True,
-                               transform=transform)
-            dataset2 = datasets.MNIST('/mnt/data', train=False,
-                               transform=transform)
-            train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
-            test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
-
-            model = Net().to(device)
-            optimizer = optim.Adadelta(model.parameters(), lr=params['lr'])
-
-            scheduler = StepLR(optimizer, step_size=1, gamma=params['gamma'])
-            for epoch in range(1, params['epochs'] + 1):
-                train(model, device, train_loader, optimizer, epoch, params['batch_size'], writer)
-                test(model, device, test_loader, epoch, writer)
-                scheduler.step()
-
-            # Save model
-            torch.save(model.state_dict(), '/mnt/output/model.pt')
-
-            writer.close()
-
-
-        if __name__ == '__main__':
-            params = {
-                'seed': 1,
-                'batch_size': 64,
-                'test_batch_size': 1000,
-                'epochs': {{workflow.parameters.epochs}},
-                'lr': 0.001,
-                'gamma': 0.7,
-            }
-            main(params)
-      volumeMounts:
-        # TensorBoard sidecar will automatically mount these volumes
-        # The `data` volume is mounted for saving datasets
-        # The `output` volume is mounted to save model output and share TensorBoard logs
-        - name: data
-          mountPath: /mnt/data
-        - name: output
-          mountPath: /mnt/output
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
+metadata:
+  name: "PyTorch Training"
+  kind: Workflow
+  version: 20201221194344
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/"
+  labels:
+    "created-by": "system"
+    framework: pytorch
+spec:
+  arguments:
+    parameters:
+      - name: epochs
+        value: '10'
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
+  entrypoint: main
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: train-model
+    - name: train-model
+      # Indicates that we want to push files in /mnt/output to object storage
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      script:
+        image: onepanel/dl:0.17.0
         command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-volumeClaimTemplates:
-  # Provision volumes for storing data and output
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
+          - python
+          - '-u'
+        source: |
+          import json
+          import torch
+          import torch.nn as nn
+          import torch.nn.functional as F
+          import torch.optim as optim
+          from torchvision import datasets, transforms
+          from torch.optim.lr_scheduler import StepLR
+          from torch.utils.tensorboard import SummaryWriter
+
+
+          class Net(nn.Module):
+              def __init__(self):
+                  super(Net, self).__init__()
+                  self.conv1 = nn.Conv2d(1, 32, 3, 1)
+                  self.conv2 = nn.Conv2d(32, 64, 3, 1)
+                  self.dropout1 = nn.Dropout(0.25)
+                  self.dropout2 = nn.Dropout(0.5)
+                  self.fc1 = nn.Linear(9216, 128)
+                  self.fc2 = nn.Linear(128, 10)
+
+              def forward(self, x):
+                  x = self.conv1(x)
+                  x = F.relu(x)
+                  x = self.conv2(x)
+                  x = F.relu(x)
+                  x = F.max_pool2d(x, 2)
+                  x = self.dropout1(x)
+                  x = torch.flatten(x, 1)
+                  x = self.fc1(x)
+                  x = F.relu(x)
+                  x = self.dropout2(x)
+                  x = self.fc2(x)
+                  output = F.log_softmax(x, dim=1)
+                  return output
+
+
+          def train(model, device, train_loader, optimizer, epoch, batch_size, writer):
+              model.train()
+              for batch_idx, (data, target) in enumerate(train_loader):
+                  data, target = data.to(device), target.to(device)
+                  optimizer.zero_grad()
+                  output = model(data)
+                  loss = F.nll_loss(output, target)
+                  loss.backward()
+                  optimizer.step()
+                  if batch_idx % 10 == 0:
+                      print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
+                          epoch, batch_idx * len(data), len(train_loader.dataset),
+                          100. * batch_idx / len(train_loader), loss.item()))
+
+                      writer.add_scalar('training loss', loss.item(), epoch)
+
+
+          def test(model, device, test_loader, epoch, writer):
+              model.eval()
+              test_loss = 0
+              correct = 0
+              with torch.no_grad():
+                  for data, target in test_loader:
+                      data, target = data.to(device), target.to(device)
+                      output = model(data)
+                      test_loss += F.nll_loss(output, target, reduction='sum').item()  # sum up batch loss
+                      pred = output.argmax(dim=1, keepdim=True)  # get the index of the max log-probability
+                      correct += pred.eq(target.view_as(pred)).sum().item()
+
+              loss = test_loss / len(test_loader.dataset)
+              accuracy = correct / len(test_loader.dataset)
+
+              print('\nTest set: Average loss: {}, Accuracy: {}\n'.format(
+                  loss, accuracy))
+
+               # Store metrics for this task
+              metrics = [
+                {'name': 'accuracy', 'value': accuracy},
+                {'name': 'loss', 'value': loss}
+              ]
+              with open('/tmp/sys-metrics.json', 'w') as f:
+                json.dump(metrics, f)
+
+
+          def main(params):
+              writer = SummaryWriter(log_dir='/mnt/output/tensorboard')
+
+              use_cuda = torch.cuda.is_available()
+
+              torch.manual_seed(params['seed'])
+
+              device = torch.device('cuda' if use_cuda else 'cpu')
+
+              train_kwargs = {'batch_size': params['batch_size']}
+              test_kwargs = {'batch_size': params['test_batch_size']}
+              if use_cuda:
+                  cuda_kwargs = {'num_workers': 1,
+                                 'pin_memory': True,
+                                 'shuffle': True}
+                  train_kwargs.update(cuda_kwargs)
+                  test_kwargs.update(cuda_kwargs)
+
+              transform=transforms.Compose([
+                  transforms.ToTensor(),
+                  transforms.Normalize((0.1307,), (0.3081,))
+              ])
+              dataset1 = datasets.MNIST('/mnt/data', train=True, download=True,
+                                 transform=transform)
+              dataset2 = datasets.MNIST('/mnt/data', train=False,
+                                 transform=transform)
+              train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
+              test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
+
+              model = Net().to(device)
+              optimizer = optim.Adadelta(model.parameters(), lr=params['lr'])
+
+              scheduler = StepLR(optimizer, step_size=1, gamma=params['gamma'])
+              for epoch in range(1, params['epochs'] + 1):
+                  train(model, device, train_loader, optimizer, epoch, params['batch_size'], writer)
+                  test(model, device, test_loader, epoch, writer)
+                  scheduler.step()
+
+              # Save model
+              torch.save(model.state_dict(), '/mnt/output/model.pt')
+
+              writer.close()
+
+
+          if __name__ == '__main__':
+              params = {
+                  'seed': 1,
+                  'batch_size': 64,
+                  'test_batch_size': 1000,
+                  'epochs': {{workflow.parameters.epochs}},
+                  'lr': 0.001,
+                  'gamma': 0.7,
+              }
+              main(params)
+        volumeMounts:
+          # TensorBoard sidecar will automatically mount these volumes
+          # The `data` volume is mounted for saving datasets
+          # The `output` volume is mounted to save model output and share TensorBoard logs
+          - name: data
+            mountPath: /mnt/data
+          - name: output
+            mountPath: /mnt/output
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+  volumeClaimTemplates:
+    # Provision volumes for storing data and output
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi

db/yaml/workflows/pytorch-mnist-training/20210118175809.yaml

@@ -1,207 +1,216 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/
-arguments:
-  parameters:
-    - name: epochs
-      value: '10'
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
-entrypoint: main
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: train-model
-  - name: train-model
-    # Indicates that we want to push files in /mnt/output to object storage
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    script:
-      image: onepanel/dl:0.17.0
-      command:
-        - python
-        - '-u'
-      source: |
-        import json
-        import torch
-        import torch.nn as nn
-        import torch.nn.functional as F
-        import torch.optim as optim
-        from torchvision import datasets, transforms
-        from torch.optim.lr_scheduler import StepLR
-        from torch.utils.tensorboard import SummaryWriter
-
-
-        class Net(nn.Module):
-            def __init__(self):
-                super(Net, self).__init__()
-                self.conv1 = nn.Conv2d(1, 32, 3, 1)
-                self.conv2 = nn.Conv2d(32, 64, 3, 1)
-                self.dropout1 = nn.Dropout(0.25)
-                self.dropout2 = nn.Dropout(0.5)
-                self.fc1 = nn.Linear(9216, 128)
-                self.fc2 = nn.Linear(128, 10)
-
-            def forward(self, x):
-                x = self.conv1(x)
-                x = F.relu(x)
-                x = self.conv2(x)
-                x = F.relu(x)
-                x = F.max_pool2d(x, 2)
-                x = self.dropout1(x)
-                x = torch.flatten(x, 1)
-                x = self.fc1(x)
-                x = F.relu(x)
-                x = self.dropout2(x)
-                x = self.fc2(x)
-                output = F.log_softmax(x, dim=1)
-                return output
-
-
-        def train(model, device, train_loader, optimizer, epoch, batch_size, writer):
-            model.train()
-            for batch_idx, (data, target) in enumerate(train_loader):
-                data, target = data.to(device), target.to(device)
-                optimizer.zero_grad()
-                output = model(data)
-                loss = F.nll_loss(output, target)
-                loss.backward()
-                optimizer.step()
-                if batch_idx % 10 == 0:
-                    print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
-                        epoch, batch_idx * len(data), len(train_loader.dataset),
-                        100. * batch_idx / len(train_loader), loss.item()))
-
-                    writer.add_scalar('training loss', loss.item(), epoch)
-
-
-        def test(model, device, test_loader, epoch, writer):
-            model.eval()
-            test_loss = 0
-            correct = 0
-            with torch.no_grad():
-                for data, target in test_loader:
-                    data, target = data.to(device), target.to(device)
-                    output = model(data)
-                    test_loss += F.nll_loss(output, target, reduction='sum').item()  # sum up batch loss
-                    pred = output.argmax(dim=1, keepdim=True)  # get the index of the max log-probability
-                    correct += pred.eq(target.view_as(pred)).sum().item()
-
-            loss = test_loss / len(test_loader.dataset)
-            accuracy = correct / len(test_loader.dataset)
-
-            print('\nTest set: Average loss: {}, Accuracy: {}\n'.format(
-                loss, accuracy))
-
-             # Store metrics for this task
-            metrics = [
-              {'name': 'accuracy', 'value': accuracy},
-              {'name': 'loss', 'value': loss}
-            ]
-            with open('/tmp/sys-metrics.json', 'w') as f:
-              json.dump(metrics, f)
-
-
-        def main(params):
-            writer = SummaryWriter(log_dir='/mnt/output/tensorboard')
-
-            use_cuda = torch.cuda.is_available()
-
-            torch.manual_seed(params['seed'])
-
-            device = torch.device('cuda' if use_cuda else 'cpu')
-
-            train_kwargs = {'batch_size': params['batch_size']}
-            test_kwargs = {'batch_size': params['test_batch_size']}
-            if use_cuda:
-                cuda_kwargs = {'num_workers': 1,
-                               'pin_memory': True,
-                               'shuffle': True}
-                train_kwargs.update(cuda_kwargs)
-                test_kwargs.update(cuda_kwargs)
-
-            transform=transforms.Compose([
-                transforms.ToTensor(),
-                transforms.Normalize((0.1307,), (0.3081,))
-            ])
-            dataset1 = datasets.MNIST('/mnt/data', train=True, download=True,
-                               transform=transform)
-            dataset2 = datasets.MNIST('/mnt/data', train=False,
-                               transform=transform)
-            train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
-            test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
-
-            model = Net().to(device)
-            optimizer = optim.Adadelta(model.parameters(), lr=params['lr'])
-
-            scheduler = StepLR(optimizer, step_size=1, gamma=params['gamma'])
-            for epoch in range(1, params['epochs'] + 1):
-                train(model, device, train_loader, optimizer, epoch, params['batch_size'], writer)
-                test(model, device, test_loader, epoch, writer)
-                scheduler.step()
-
-            # Save model
-            torch.save(model.state_dict(), '/mnt/output/model.pt')
-
-            writer.close()
-
-
-        if __name__ == '__main__':
-            params = {
-                'seed': 1,
-                'batch_size': 64,
-                'test_batch_size': 1000,
-                'epochs': {{workflow.parameters.epochs}},
-                'lr': 0.001,
-                'gamma': 0.7,
-            }
-            main(params)
-      volumeMounts:
-        # TensorBoard sidecar will automatically mount these volumes
-        # The `data` volume is mounted for saving datasets
-        # The `output` volume is mounted to save model output and share TensorBoard logs
-        - name: data
-          mountPath: /mnt/data
-        - name: output
-          mountPath: /mnt/output
-    nodeSelector:
-      {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
+metadata:
+  name: "PyTorch Training"
+  kind: Workflow
+  version: 20210118175809
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/"
+  labels:
+    "created-by": "system"
+    framework: pytorch
+spec:
+  arguments:
+    parameters:
+      - name: epochs
+        value: '10'
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
+  entrypoint: main
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: train-model
+    - name: train-model
+      # Indicates that we want to push files in /mnt/output to object storage
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      script:
         image: onepanel/dl:0.17.0
         command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-volumeClaimTemplates:
-  # Provision volumes for storing data and output
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
+          - python
+          - '-u'
+        source: |
+          import json
+          import torch
+          import torch.nn as nn
+          import torch.nn.functional as F
+          import torch.optim as optim
+          from torchvision import datasets, transforms
+          from torch.optim.lr_scheduler import StepLR
+          from torch.utils.tensorboard import SummaryWriter
+
+
+          class Net(nn.Module):
+              def __init__(self):
+                  super(Net, self).__init__()
+                  self.conv1 = nn.Conv2d(1, 32, 3, 1)
+                  self.conv2 = nn.Conv2d(32, 64, 3, 1)
+                  self.dropout1 = nn.Dropout(0.25)
+                  self.dropout2 = nn.Dropout(0.5)
+                  self.fc1 = nn.Linear(9216, 128)
+                  self.fc2 = nn.Linear(128, 10)
+
+              def forward(self, x):
+                  x = self.conv1(x)
+                  x = F.relu(x)
+                  x = self.conv2(x)
+                  x = F.relu(x)
+                  x = F.max_pool2d(x, 2)
+                  x = self.dropout1(x)
+                  x = torch.flatten(x, 1)
+                  x = self.fc1(x)
+                  x = F.relu(x)
+                  x = self.dropout2(x)
+                  x = self.fc2(x)
+                  output = F.log_softmax(x, dim=1)
+                  return output
+
+
+          def train(model, device, train_loader, optimizer, epoch, batch_size, writer):
+              model.train()
+              for batch_idx, (data, target) in enumerate(train_loader):
+                  data, target = data.to(device), target.to(device)
+                  optimizer.zero_grad()
+                  output = model(data)
+                  loss = F.nll_loss(output, target)
+                  loss.backward()
+                  optimizer.step()
+                  if batch_idx % 10 == 0:
+                      print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
+                          epoch, batch_idx * len(data), len(train_loader.dataset),
+                          100. * batch_idx / len(train_loader), loss.item()))
+
+                      writer.add_scalar('training loss', loss.item(), epoch)
+
+
+          def test(model, device, test_loader, epoch, writer):
+              model.eval()
+              test_loss = 0
+              correct = 0
+              with torch.no_grad():
+                  for data, target in test_loader:
+                      data, target = data.to(device), target.to(device)
+                      output = model(data)
+                      test_loss += F.nll_loss(output, target, reduction='sum').item()  # sum up batch loss
+                      pred = output.argmax(dim=1, keepdim=True)  # get the index of the max log-probability
+                      correct += pred.eq(target.view_as(pred)).sum().item()
+
+              loss = test_loss / len(test_loader.dataset)
+              accuracy = correct / len(test_loader.dataset)
+
+              print('\nTest set: Average loss: {}, Accuracy: {}\n'.format(
+                  loss, accuracy))
+
+               # Store metrics for this task
+              metrics = [
+                {'name': 'accuracy', 'value': accuracy},
+                {'name': 'loss', 'value': loss}
+              ]
+              with open('/tmp/sys-metrics.json', 'w') as f:
+                json.dump(metrics, f)
+
+
+          def main(params):
+              writer = SummaryWriter(log_dir='/mnt/output/tensorboard')
+
+              use_cuda = torch.cuda.is_available()
+
+              torch.manual_seed(params['seed'])
+
+              device = torch.device('cuda' if use_cuda else 'cpu')
+
+              train_kwargs = {'batch_size': params['batch_size']}
+              test_kwargs = {'batch_size': params['test_batch_size']}
+              if use_cuda:
+                  cuda_kwargs = {'num_workers': 1,
+                                 'pin_memory': True,
+                                 'shuffle': True}
+                  train_kwargs.update(cuda_kwargs)
+                  test_kwargs.update(cuda_kwargs)
+
+              transform=transforms.Compose([
+                  transforms.ToTensor(),
+                  transforms.Normalize((0.1307,), (0.3081,))
+              ])
+              dataset1 = datasets.MNIST('/mnt/data', train=True, download=True,
+                                 transform=transform)
+              dataset2 = datasets.MNIST('/mnt/data', train=False,
+                                 transform=transform)
+              train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
+              test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
+
+              model = Net().to(device)
+              optimizer = optim.Adadelta(model.parameters(), lr=params['lr'])
+
+              scheduler = StepLR(optimizer, step_size=1, gamma=params['gamma'])
+              for epoch in range(1, params['epochs'] + 1):
+                  train(model, device, train_loader, optimizer, epoch, params['batch_size'], writer)
+                  test(model, device, test_loader, epoch, writer)
+                  scheduler.step()
+
+              # Save model
+              torch.save(model.state_dict(), '/mnt/output/model.pt')
+
+              writer.close()
+
+
+          if __name__ == '__main__':
+              params = {
+                  'seed': 1,
+                  'batch_size': 64,
+                  'test_batch_size': 1000,
+                  'epochs': {{workflow.parameters.epochs}},
+                  'lr': 0.001,
+                  'gamma': 0.7,
+              }
+              main(params)
+        volumeMounts:
+          # TensorBoard sidecar will automatically mount these volumes
+          # The `data` volume is mounted for saving datasets
+          # The `output` volume is mounted to save model output and share TensorBoard logs
+          - name: data
+            mountPath: /mnt/data
+          - name: output
+            mountPath: /mnt/output
+      nodeSelector:
+        "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: onepanel/dl:0.17.0
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+  volumeClaimTemplates:
+    # Provision volumes for storing data and output
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi

db/yaml/workflows/pytorch-mnist-training/20210323175655.yaml

@@ -1,207 +1,216 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/
-arguments:
-  parameters:
-    - name: epochs
-      value: '10'
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
-entrypoint: main
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: train-model
-  - name: train-model
-    # Indicates that we want to push files in /mnt/output to object storage
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    script:
-      image: onepanel/dl:v0.20.0
-      command:
-        - python
-        - '-u'
-      source: |
-        import json
-        import torch
-        import torch.nn as nn
-        import torch.nn.functional as F
-        import torch.optim as optim
-        from torchvision import datasets, transforms
-        from torch.optim.lr_scheduler import StepLR
-        from torch.utils.tensorboard import SummaryWriter
-
-
-        class Net(nn.Module):
-            def __init__(self):
-                super(Net, self).__init__()
-                self.conv1 = nn.Conv2d(1, 32, 3, 1)
-                self.conv2 = nn.Conv2d(32, 64, 3, 1)
-                self.dropout1 = nn.Dropout(0.25)
-                self.dropout2 = nn.Dropout(0.5)
-                self.fc1 = nn.Linear(9216, 128)
-                self.fc2 = nn.Linear(128, 10)
-
-            def forward(self, x):
-                x = self.conv1(x)
-                x = F.relu(x)
-                x = self.conv2(x)
-                x = F.relu(x)
-                x = F.max_pool2d(x, 2)
-                x = self.dropout1(x)
-                x = torch.flatten(x, 1)
-                x = self.fc1(x)
-                x = F.relu(x)
-                x = self.dropout2(x)
-                x = self.fc2(x)
-                output = F.log_softmax(x, dim=1)
-                return output
-
-
-        def train(model, device, train_loader, optimizer, epoch, batch_size, writer):
-            model.train()
-            for batch_idx, (data, target) in enumerate(train_loader):
-                data, target = data.to(device), target.to(device)
-                optimizer.zero_grad()
-                output = model(data)
-                loss = F.nll_loss(output, target)
-                loss.backward()
-                optimizer.step()
-                if batch_idx % 10 == 0:
-                    print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
-                        epoch, batch_idx * len(data), len(train_loader.dataset),
-                        100. * batch_idx / len(train_loader), loss.item()))
-
-                    writer.add_scalar('training loss', loss.item(), epoch)
-
-
-        def test(model, device, test_loader, epoch, writer):
-            model.eval()
-            test_loss = 0
-            correct = 0
-            with torch.no_grad():
-                for data, target in test_loader:
-                    data, target = data.to(device), target.to(device)
-                    output = model(data)
-                    test_loss += F.nll_loss(output, target, reduction='sum').item()  # sum up batch loss
-                    pred = output.argmax(dim=1, keepdim=True)  # get the index of the max log-probability
-                    correct += pred.eq(target.view_as(pred)).sum().item()
-
-            loss = test_loss / len(test_loader.dataset)
-            accuracy = correct / len(test_loader.dataset)
-
-            print('\nTest set: Average loss: {}, Accuracy: {}\n'.format(
-                loss, accuracy))
-
-             # Store metrics for this task
-            metrics = [
-              {'name': 'accuracy', 'value': accuracy},
-              {'name': 'loss', 'value': loss}
-            ]
-            with open('/mnt/tmp/sys-metrics.json', 'w') as f:
-              json.dump(metrics, f)
-
-
-        def main(params):
-            writer = SummaryWriter(log_dir='/mnt/output/tensorboard')
-
-            use_cuda = torch.cuda.is_available()
-
-            torch.manual_seed(params['seed'])
-
-            device = torch.device('cuda' if use_cuda else 'cpu')
-
-            train_kwargs = {'batch_size': params['batch_size']}
-            test_kwargs = {'batch_size': params['test_batch_size']}
-            if use_cuda:
-                cuda_kwargs = {'num_workers': 1,
-                               'pin_memory': True,
-                               'shuffle': True}
-                train_kwargs.update(cuda_kwargs)
-                test_kwargs.update(cuda_kwargs)
-
-            transform=transforms.Compose([
-                transforms.ToTensor(),
-                transforms.Normalize((0.1307,), (0.3081,))
-            ])
-            dataset1 = datasets.MNIST('/mnt/data', train=True, download=True,
-                               transform=transform)
-            dataset2 = datasets.MNIST('/mnt/data', train=False,
-                               transform=transform)
-            train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
-            test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
-
-            model = Net().to(device)
-            optimizer = optim.Adadelta(model.parameters(), lr=params['lr'])
-
-            scheduler = StepLR(optimizer, step_size=1, gamma=params['gamma'])
-            for epoch in range(1, params['epochs'] + 1):
-                train(model, device, train_loader, optimizer, epoch, params['batch_size'], writer)
-                test(model, device, test_loader, epoch, writer)
-                scheduler.step()
-
-            # Save model
-            torch.save(model.state_dict(), '/mnt/output/model.pt')
-
-            writer.close()
-
-
-        if __name__ == '__main__':
-            params = {
-                'seed': 1,
-                'batch_size': 64,
-                'test_batch_size': 1000,
-                'epochs': {{workflow.parameters.epochs}},
-                'lr': 0.001,
-                'gamma': 0.7,
-            }
-            main(params)
-      volumeMounts:
-        # TensorBoard sidecar will automatically mount these volumes
-        # The `data` volume is mounted for saving datasets
-        # The `output` volume is mounted to save model output and share TensorBoard logs
-        - name: data
-          mountPath: /mnt/data
-        - name: output
-          mountPath: /mnt/output
-    nodeSelector:
-        {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
+metadata:
+  name: "PyTorch Training"
+  kind: Workflow
+  version: 20210323175655
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/"
+  labels:
+    "created-by": "system"
+    framework: pytorch
+spec:
+  arguments:
+    parameters:
+      - name: epochs
+        value: '10'
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
+  entrypoint: main
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: train-model
+    - name: train-model
+      # Indicates that we want to push files in /mnt/output to object storage
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      script:
         image: onepanel/dl:v0.20.0
         command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-volumeClaimTemplates:
-  # Provision volumes for storing data and output
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
+          - python
+          - '-u'
+        source: |
+          import json
+          import torch
+          import torch.nn as nn
+          import torch.nn.functional as F
+          import torch.optim as optim
+          from torchvision import datasets, transforms
+          from torch.optim.lr_scheduler import StepLR
+          from torch.utils.tensorboard import SummaryWriter
+
+
+          class Net(nn.Module):
+              def __init__(self):
+                  super(Net, self).__init__()
+                  self.conv1 = nn.Conv2d(1, 32, 3, 1)
+                  self.conv2 = nn.Conv2d(32, 64, 3, 1)
+                  self.dropout1 = nn.Dropout(0.25)
+                  self.dropout2 = nn.Dropout(0.5)
+                  self.fc1 = nn.Linear(9216, 128)
+                  self.fc2 = nn.Linear(128, 10)
+
+              def forward(self, x):
+                  x = self.conv1(x)
+                  x = F.relu(x)
+                  x = self.conv2(x)
+                  x = F.relu(x)
+                  x = F.max_pool2d(x, 2)
+                  x = self.dropout1(x)
+                  x = torch.flatten(x, 1)
+                  x = self.fc1(x)
+                  x = F.relu(x)
+                  x = self.dropout2(x)
+                  x = self.fc2(x)
+                  output = F.log_softmax(x, dim=1)
+                  return output
+
+
+          def train(model, device, train_loader, optimizer, epoch, batch_size, writer):
+              model.train()
+              for batch_idx, (data, target) in enumerate(train_loader):
+                  data, target = data.to(device), target.to(device)
+                  optimizer.zero_grad()
+                  output = model(data)
+                  loss = F.nll_loss(output, target)
+                  loss.backward()
+                  optimizer.step()
+                  if batch_idx % 10 == 0:
+                      print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
+                          epoch, batch_idx * len(data), len(train_loader.dataset),
+                          100. * batch_idx / len(train_loader), loss.item()))
+
+                      writer.add_scalar('training loss', loss.item(), epoch)
+
+
+          def test(model, device, test_loader, epoch, writer):
+              model.eval()
+              test_loss = 0
+              correct = 0
+              with torch.no_grad():
+                  for data, target in test_loader:
+                      data, target = data.to(device), target.to(device)
+                      output = model(data)
+                      test_loss += F.nll_loss(output, target, reduction='sum').item()  # sum up batch loss
+                      pred = output.argmax(dim=1, keepdim=True)  # get the index of the max log-probability
+                      correct += pred.eq(target.view_as(pred)).sum().item()
+
+              loss = test_loss / len(test_loader.dataset)
+              accuracy = correct / len(test_loader.dataset)
+
+              print('\nTest set: Average loss: {}, Accuracy: {}\n'.format(
+                  loss, accuracy))
+
+               # Store metrics for this task
+              metrics = [
+                {'name': 'accuracy', 'value': accuracy},
+                {'name': 'loss', 'value': loss}
+              ]
+              with open('/mnt/tmp/sys-metrics.json', 'w') as f:
+                json.dump(metrics, f)
+
+
+          def main(params):
+              writer = SummaryWriter(log_dir='/mnt/output/tensorboard')
+
+              use_cuda = torch.cuda.is_available()
+
+              torch.manual_seed(params['seed'])
+
+              device = torch.device('cuda' if use_cuda else 'cpu')
+
+              train_kwargs = {'batch_size': params['batch_size']}
+              test_kwargs = {'batch_size': params['test_batch_size']}
+              if use_cuda:
+                  cuda_kwargs = {'num_workers': 1,
+                                 'pin_memory': True,
+                                 'shuffle': True}
+                  train_kwargs.update(cuda_kwargs)
+                  test_kwargs.update(cuda_kwargs)
+
+              transform=transforms.Compose([
+                  transforms.ToTensor(),
+                  transforms.Normalize((0.1307,), (0.3081,))
+              ])
+              dataset1 = datasets.MNIST('/mnt/data', train=True, download=True,
+                                 transform=transform)
+              dataset2 = datasets.MNIST('/mnt/data', train=False,
+                                 transform=transform)
+              train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
+              test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
+
+              model = Net().to(device)
+              optimizer = optim.Adadelta(model.parameters(), lr=params['lr'])
+
+              scheduler = StepLR(optimizer, step_size=1, gamma=params['gamma'])
+              for epoch in range(1, params['epochs'] + 1):
+                  train(model, device, train_loader, optimizer, epoch, params['batch_size'], writer)
+                  test(model, device, test_loader, epoch, writer)
+                  scheduler.step()
+
+              # Save model
+              torch.save(model.state_dict(), '/mnt/output/model.pt')
+
+              writer.close()
+
+
+          if __name__ == '__main__':
+              params = {
+                  'seed': 1,
+                  'batch_size': 64,
+                  'test_batch_size': 1000,
+                  'epochs': {{workflow.parameters.epochs}},
+                  'lr': 0.001,
+                  'gamma': 0.7,
+              }
+              main(params)
+        volumeMounts:
+          # TensorBoard sidecar will automatically mount these volumes
+          # The `data` volume is mounted for saving datasets
+          # The `output` volume is mounted to save model output and share TensorBoard logs
+          - name: data
+            mountPath: /mnt/data
+          - name: output
+            mountPath: /mnt/output
+      nodeSelector:
+          "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: onepanel/dl:v0.20.0
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+  volumeClaimTemplates:
+    # Provision volumes for storing data and output
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi

db/yaml/workflows/tensorflow-mnist-training/20200605090535.yaml

@@ -1,76 +1,85 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/template.yaml
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/onepanelio/tensorflow-examples.git
-    - name: command
-      value: "python mnist/main.py --epochs=5"
-volumeClaimTemplates:
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: pytorch
-  # Uncomment section below to send metrics to Slack
-  #      - name: notify-in-slack
-  #        dependencies: [train-model]
-  #        template: slack-notify-success
-  #        arguments:
-  #          parameters:
-  #          - name: status
-  #            value: "{{tasks.train-model.status}}"
-  #          artifacts:
-  #          - name: metrics
-  #            from: "{{tasks.train-model.outputs.artifacts.sys-metrics}}"
-  - name: pytorch
-    inputs:
-      artifacts:
-        - name: src
-          path: /mnt/src
-          git:
-            repo: "{{workflow.parameters.source}}"
-    outputs:
-      artifacts:
-        - name: model
-          path: /mnt/output
-          optional: true
-          archive:
-            none: {}
-    container:
-      image: tensorflow/tensorflow:latest
-      command: [sh,-c]
-      args: ["{{workflow.parameters.command}}"]
-      workingDir: /mnt/src
-      volumeMounts:
-        - name: data
-          mountPath: /mnt/data
-        - name: output
-          mountPath: /mnt/output
-  - name: slack-notify-success
-    container:
-      image: technosophos/slack-notify
-      command: [sh,-c]
-      args: ['SLACK_USERNAME=Worker SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify']
-    inputs:
-      parameters:
-        - name: status
-      artifacts:
-        - name: metrics
-          path: /tmp/metrics.json
-          optional: true
+metadata:
+  name: "TensorFlow Training"
+  kind: Workflow
+  version: 20200605090535
+  action: create
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/template.yaml"
+  labels:
+    "created-by": "system"
+    framework: tensorflow
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/onepanelio/tensorflow-examples.git
+      - name: command
+        value: "python mnist/main.py --epochs=5"
+  volumeClaimTemplates:
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: pytorch
+    # Uncomment section below to send metrics to Slack
+    #      - name: notify-in-slack
+    #        dependencies: [train-model]
+    #        template: slack-notify-success
+    #        arguments:
+    #          parameters:
+    #          - name: status
+    #            value: "{{tasks.train-model.status}}"
+    #          artifacts:
+    #          - name: metrics
+    #            from: "{{tasks.train-model.outputs.artifacts.sys-metrics}}"
+    - name: pytorch
+      inputs:
+        artifacts:
+          - name: src
+            path: /mnt/src
+            git:
+              repo: "{{workflow.parameters.source}}"
+      outputs:
+        artifacts:
+          - name: model
+            path: /mnt/output
+            optional: true
+            archive:
+              none: {}
+      container:
+        image: tensorflow/tensorflow:latest
+        command: [sh,-c]
+        args: ["{{workflow.parameters.command}}"]
+        workingDir: /mnt/src
+        volumeMounts:
+          - name: data
+            mountPath: /mnt/data
+          - name: output
+            mountPath: /mnt/output
+    - name: slack-notify-success
+      container:
+        image: technosophos/slack-notify
+        command: [sh,-c]
+        args: ['SLACK_USERNAME=Worker SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify']
+      inputs:
+        parameters:
+          - name: status
+        artifacts:
+          - name: metrics
+            path: /tmp/metrics.json
+            optional: true

db/yaml/workflows/tensorflow-mnist-training/20201209124226.yaml

@@ -1,71 +1,80 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/template.yaml
-arguments:
-  parameters:
-    - name: epochs
-      value: '10'
-entrypoint: main
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: tf-dense
-  - name: tf-dense
-    script:
-      image: tensorflow/tensorflow:2.3.0
-      command:
-        - python
-        - '-u'
-      source: |
-        import tensorflow as tf
-        import datetime
-        mnist = tf.keras.datasets.mnist
-        (x_train, y_train),(x_test, y_test) = mnist.load_data()
-        x_train, x_test = x_train / 255.0, x_test / 255.0
-        def create_model():
-          return tf.keras.models.Sequential([
-            tf.keras.layers.Flatten(input_shape=(28, 28)),
-            tf.keras.layers.Dense(512, activation='relu'),
-            tf.keras.layers.Dropout(0.2),
-            tf.keras.layers.Dense(10, activation='softmax')
-          ])
-        model = create_model()
-        model.compile(optimizer='adam',
-                      loss='sparse_categorical_crossentropy',
-                      metrics=['accuracy'])
-        # Write logs to /mnt/output
-        log_dir = "/mnt/output/logs/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
-        tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
-        history = model.fit(x=x_train,
-                  y=y_train,
-                  epochs={{workflow.parameters.epochs}},
-                  validation_data=(x_test, y_test),
-                  callbacks=[tensorboard_callback])
-      volumeMounts:
-        # TensorBoard sidecar will automatically mount this volume
-        - name: output
-          mountPath: /mnt/output
-    sidecars:
-      - name: tensorboard
-        image: 'tensorflow/tensorflow:2.3.0'
+metadata:
+  name: "TensorFlow Training"
+  kind: Workflow
+  version: 20201209124226
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/template.yaml"
+  labels:
+    "created-by": "system"
+    framework: tensorflow
+spec:
+  arguments:
+    parameters:
+      - name: epochs
+        value: '10'
+  entrypoint: main
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: tf-dense
+    - name: tf-dense
+      script:
+        image: tensorflow/tensorflow:2.3.0
         command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-volumeClaimTemplates:
-  # Provision a volume that can be shared between main container and TensorBoard side car
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
+          - python
+          - '-u'
+        source: |
+          import tensorflow as tf
+          import datetime
+          mnist = tf.keras.datasets.mnist
+          (x_train, y_train),(x_test, y_test) = mnist.load_data()
+          x_train, x_test = x_train / 255.0, x_test / 255.0
+          def create_model():
+            return tf.keras.models.Sequential([
+              tf.keras.layers.Flatten(input_shape=(28, 28)),
+              tf.keras.layers.Dense(512, activation='relu'),
+              tf.keras.layers.Dropout(0.2),
+              tf.keras.layers.Dense(10, activation='softmax')
+            ])
+          model = create_model()
+          model.compile(optimizer='adam',
+                        loss='sparse_categorical_crossentropy',
+                        metrics=['accuracy'])
+          # Write logs to /mnt/output
+          log_dir = "/mnt/output/logs/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
+          tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
+          history = model.fit(x=x_train,
+                    y=y_train,
+                    epochs={{workflow.parameters.epochs}},
+                    validation_data=(x_test, y_test),
+                    callbacks=[tensorboard_callback])
+        volumeMounts:
+          # TensorBoard sidecar will automatically mount this volume
+          - name: output
+            mountPath: /mnt/output
+      sidecars:
+        - name: tensorboard
+          image: 'tensorflow/tensorflow:2.3.0'
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+  volumeClaimTemplates:
+    # Provision a volume that can be shared between main container and TensorBoard side car
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi

db/yaml/workflows/tensorflow-mnist-training/20201223062947.yaml

@@ -1,118 +1,127 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/
-arguments:
-  parameters:
-    - name: epochs
-      value: '10'
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
-entrypoint: main
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: train-model
-  - name: train-model
-    # Indicates that we want to push files in /mnt/output to object storage
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    script:
-      image: onepanel/dl:0.17.0
-      command:
-        - python
-        - '-u'
-      source: |
-        import json
-        import tensorflow as tf
-
-        mnist = tf.keras.datasets.mnist
-
-        (x_train, y_train),(x_test, y_test) = mnist.load_data()
-        x_train, x_test = x_train / 255.0, x_test / 255.0
-        x_train = x_train[..., tf.newaxis]
-        x_test = x_test[..., tf.newaxis]
-
-        model = tf.keras.Sequential([
-          tf.keras.layers.Conv2D(filters=32, kernel_size=5, activation='relu'),
-          tf.keras.layers.MaxPool2D(pool_size=2),
-          tf.keras.layers.Conv2D(filters=64, kernel_size=5, activation='relu'),
-          tf.keras.layers.MaxPool2D(pool_size=2),
-          tf.keras.layers.Flatten(),
-          tf.keras.layers.Dense(units=124, activation='relu'),
-          tf.keras.layers.Dropout(rate=0.75),
-          tf.keras.layers.Dense(units=10, activation='softmax')
-        ])
-        model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
-                      loss='sparse_categorical_crossentropy',
-                      metrics=['accuracy'])
-
-        # Write TensorBoard logs to /mnt/output
-        log_dir = '/mnt/output/tensorboard/'
-        tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
-
-        model.fit(x=x_train,
-                  y=y_train,
-                  epochs={{workflow.parameters.epochs}},
-                  validation_data=(x_test, y_test),
-                  callbacks=[tensorboard_callback])
-
-        # Store metrics for this task
-        loss, accuracy = model.evaluate(x_test, y_test)
-        metrics = [
-          {'name': 'accuracy', 'value': accuracy},
-          {'name': 'loss', 'value': loss}
-        ]
-        with open('/tmp/sys-metrics.json', 'w') as f:
-          json.dump(metrics, f)
-
-        # Save model
-        model.save('/mnt/output/model.h5')
-      volumeMounts:
-        # TensorBoard sidecar will automatically mount these volumes
-        # The `data` volume is mounted to support Keras datasets
-        # The `output` volume is mounted to save model output and share TensorBoard logs
-        - name: data
-          mountPath: /home/root/.keras/datasets
-        - name: output
-          mountPath: /mnt/output
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
+metadata:
+  name: "TensorFlow Training"
+  kind: Workflow
+  version: 20201223062947
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/"
+  labels:
+    "created-by": "system"
+    framework: tensorflow
+spec:
+  arguments:
+    parameters:
+      - name: epochs
+        value: '10'
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
+  entrypoint: main
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: train-model
+    - name: train-model
+      # Indicates that we want to push files in /mnt/output to object storage
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      script:
+        image: onepanel/dl:0.17.0
         command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-volumeClaimTemplates:
-  # Provision volumes for storing data and output
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
+          - python
+          - '-u'
+        source: |
+          import json
+          import tensorflow as tf
+
+          mnist = tf.keras.datasets.mnist
+
+          (x_train, y_train),(x_test, y_test) = mnist.load_data()
+          x_train, x_test = x_train / 255.0, x_test / 255.0
+          x_train = x_train[..., tf.newaxis]
+          x_test = x_test[..., tf.newaxis]
+
+          model = tf.keras.Sequential([
+            tf.keras.layers.Conv2D(filters=32, kernel_size=5, activation='relu'),
+            tf.keras.layers.MaxPool2D(pool_size=2),
+            tf.keras.layers.Conv2D(filters=64, kernel_size=5, activation='relu'),
+            tf.keras.layers.MaxPool2D(pool_size=2),
+            tf.keras.layers.Flatten(),
+            tf.keras.layers.Dense(units=124, activation='relu'),
+            tf.keras.layers.Dropout(rate=0.75),
+            tf.keras.layers.Dense(units=10, activation='softmax')
+          ])
+          model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
+                        loss='sparse_categorical_crossentropy',
+                        metrics=['accuracy'])
+
+          # Write TensorBoard logs to /mnt/output
+          log_dir = '/mnt/output/tensorboard/'
+          tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
+
+          model.fit(x=x_train,
+                    y=y_train,
+                    epochs={{workflow.parameters.epochs}},
+                    validation_data=(x_test, y_test),
+                    callbacks=[tensorboard_callback])
+
+          # Store metrics for this task
+          loss, accuracy = model.evaluate(x_test, y_test)
+          metrics = [
+            {'name': 'accuracy', 'value': accuracy},
+            {'name': 'loss', 'value': loss}
+          ]
+          with open('/tmp/sys-metrics.json', 'w') as f:
+            json.dump(metrics, f)
+
+          # Save model
+          model.save('/mnt/output/model.h5')
+        volumeMounts:
+          # TensorBoard sidecar will automatically mount these volumes
+          # The `data` volume is mounted to support Keras datasets
+          # The `output` volume is mounted to save model output and share TensorBoard logs
+          - name: data
+            mountPath: /home/root/.keras/datasets
+          - name: output
+            mountPath: /mnt/output
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+  volumeClaimTemplates:
+    # Provision volumes for storing data and output
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi

db/yaml/workflows/tensorflow-mnist-training/20210118175809.yaml

@@ -1,118 +1,127 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/
-arguments:
-  parameters:
-    - name: epochs
-      value: '10'
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
-entrypoint: main
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: train-model
-  - name: train-model
-    # Indicates that we want to push files in /mnt/output to object storage
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    script:
-      image: onepanel/dl:0.17.0
-      command:
-        - python
-        - '-u'
-      source: |
-        import json
-        import tensorflow as tf
-
-        mnist = tf.keras.datasets.mnist
-
-        (x_train, y_train),(x_test, y_test) = mnist.load_data()
-        x_train, x_test = x_train / 255.0, x_test / 255.0
-        x_train = x_train[..., tf.newaxis]
-        x_test = x_test[..., tf.newaxis]
-
-        model = tf.keras.Sequential([
-          tf.keras.layers.Conv2D(filters=32, kernel_size=5, activation='relu'),
-          tf.keras.layers.MaxPool2D(pool_size=2),
-          tf.keras.layers.Conv2D(filters=64, kernel_size=5, activation='relu'),
-          tf.keras.layers.MaxPool2D(pool_size=2),
-          tf.keras.layers.Flatten(),
-          tf.keras.layers.Dense(units=124, activation='relu'),
-          tf.keras.layers.Dropout(rate=0.75),
-          tf.keras.layers.Dense(units=10, activation='softmax')
-        ])
-        model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
-                      loss='sparse_categorical_crossentropy',
-                      metrics=['accuracy'])
-
-        # Write TensorBoard logs to /mnt/output
-        log_dir = '/mnt/output/tensorboard/'
-        tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
-
-        model.fit(x=x_train,
-                  y=y_train,
-                  epochs={{workflow.parameters.epochs}},
-                  validation_data=(x_test, y_test),
-                  callbacks=[tensorboard_callback])
-
-        # Store metrics for this task
-        loss, accuracy = model.evaluate(x_test, y_test)
-        metrics = [
-          {'name': 'accuracy', 'value': accuracy},
-          {'name': 'loss', 'value': loss}
-        ]
-        with open('/tmp/sys-metrics.json', 'w') as f:
-          json.dump(metrics, f)
-
-        # Save model
-        model.save('/mnt/output/model.h5')
-      volumeMounts:
-        # TensorBoard sidecar will automatically mount these volumes
-        # The `data` volume is mounted to support Keras datasets
-        # The `output` volume is mounted to save model output and share TensorBoard logs
-        - name: data
-          mountPath: /home/root/.keras/datasets
-        - name: output
-          mountPath: /mnt/output
-    nodeSelector:
-      {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
+metadata:
+  name: "TensorFlow Training"
+  kind: Workflow
+  version: 20210118175809
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/"
+  labels:
+    "created-by": "system"
+    framework: tensorflow
+spec:
+  arguments:
+    parameters:
+      - name: epochs
+        value: '10'
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
+  entrypoint: main
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: train-model
+    - name: train-model
+      # Indicates that we want to push files in /mnt/output to object storage
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      script:
         image: onepanel/dl:0.17.0
         command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-volumeClaimTemplates:
-  # Provision volumes for storing data and output
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
+          - python
+          - '-u'
+        source: |
+          import json
+          import tensorflow as tf
+
+          mnist = tf.keras.datasets.mnist
+
+          (x_train, y_train),(x_test, y_test) = mnist.load_data()
+          x_train, x_test = x_train / 255.0, x_test / 255.0
+          x_train = x_train[..., tf.newaxis]
+          x_test = x_test[..., tf.newaxis]
+
+          model = tf.keras.Sequential([
+            tf.keras.layers.Conv2D(filters=32, kernel_size=5, activation='relu'),
+            tf.keras.layers.MaxPool2D(pool_size=2),
+            tf.keras.layers.Conv2D(filters=64, kernel_size=5, activation='relu'),
+            tf.keras.layers.MaxPool2D(pool_size=2),
+            tf.keras.layers.Flatten(),
+            tf.keras.layers.Dense(units=124, activation='relu'),
+            tf.keras.layers.Dropout(rate=0.75),
+            tf.keras.layers.Dense(units=10, activation='softmax')
+          ])
+          model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
+                        loss='sparse_categorical_crossentropy',
+                        metrics=['accuracy'])
+
+          # Write TensorBoard logs to /mnt/output
+          log_dir = '/mnt/output/tensorboard/'
+          tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
+
+          model.fit(x=x_train,
+                    y=y_train,
+                    epochs={{workflow.parameters.epochs}},
+                    validation_data=(x_test, y_test),
+                    callbacks=[tensorboard_callback])
+
+          # Store metrics for this task
+          loss, accuracy = model.evaluate(x_test, y_test)
+          metrics = [
+            {'name': 'accuracy', 'value': accuracy},
+            {'name': 'loss', 'value': loss}
+          ]
+          with open('/tmp/sys-metrics.json', 'w') as f:
+            json.dump(metrics, f)
+
+          # Save model
+          model.save('/mnt/output/model.h5')
+        volumeMounts:
+          # TensorBoard sidecar will automatically mount these volumes
+          # The `data` volume is mounted to support Keras datasets
+          # The `output` volume is mounted to save model output and share TensorBoard logs
+          - name: data
+            mountPath: /home/root/.keras/datasets
+          - name: output
+            mountPath: /mnt/output
+      nodeSelector:
+        "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: onepanel/dl:0.17.0
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+  volumeClaimTemplates:
+    # Provision volumes for storing data and output
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi

db/yaml/workflows/tensorflow-mnist-training/20210323175655.yaml

@@ -1,118 +1,127 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/
-arguments:
-  parameters:
-    - name: epochs
-      value: '10'
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
-entrypoint: main
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: train-model
-  - name: train-model
-    # Indicates that we want to push files in /mnt/output to object storage
-    outputs:
-      artifacts:
-        - name: output
-          path: /mnt/output
-          optional: true
-    script:
-      image: onepanel/dl:v0.20.0
-      command:
-        - python
-        - '-u'
-      source: |
-        import json
-        import tensorflow as tf
-
-        mnist = tf.keras.datasets.mnist
-
-        (x_train, y_train),(x_test, y_test) = mnist.load_data()
-        x_train, x_test = x_train / 255.0, x_test / 255.0
-        x_train = x_train[..., tf.newaxis]
-        x_test = x_test[..., tf.newaxis]
-
-        model = tf.keras.Sequential([
-          tf.keras.layers.Conv2D(filters=32, kernel_size=5, activation='relu'),
-          tf.keras.layers.MaxPool2D(pool_size=2),
-          tf.keras.layers.Conv2D(filters=64, kernel_size=5, activation='relu'),
-          tf.keras.layers.MaxPool2D(pool_size=2),
-          tf.keras.layers.Flatten(),
-          tf.keras.layers.Dense(units=124, activation='relu'),
-          tf.keras.layers.Dropout(rate=0.75),
-          tf.keras.layers.Dense(units=10, activation='softmax')
-        ])
-        model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
-                      loss='sparse_categorical_crossentropy',
-                      metrics=['accuracy'])
-
-        # Write TensorBoard logs to /mnt/output
-        log_dir = '/mnt/output/tensorboard/'
-        tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
-
-        model.fit(x=x_train,
-                  y=y_train,
-                  epochs={{workflow.parameters.epochs}},
-                  validation_data=(x_test, y_test),
-                  callbacks=[tensorboard_callback])
-
-        # Store metrics for this task
-        loss, accuracy = model.evaluate(x_test, y_test)
-        metrics = [
-          {'name': 'accuracy', 'value': accuracy},
-          {'name': 'loss', 'value': loss}
-        ]
-        with open('/mnt/tmp/sys-metrics.json', 'w') as f:
-          json.dump(metrics, f)
-
-        # Save model
-        model.save('/mnt/output/model.h5')
-      volumeMounts:
-        # TensorBoard sidecar will automatically mount these volumes
-        # The `data` volume is mounted to support Keras datasets
-        # The `output` volume is mounted to save model output and share TensorBoard logs
-        - name: data
-          mountPath: /home/root/.keras/datasets
-        - name: output
-          mountPath: /mnt/output
-    nodeSelector:
-        {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
+metadata:
+  name: "TensorFlow Training"
+  kind: Workflow
+  version: 20210323175655
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/"
+  labels:
+    "created-by": "system"
+    framework: tensorflow
+spec:
+  arguments:
+    parameters:
+      - name: epochs
+        value: '10'
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
+  entrypoint: main
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: train-model
+    - name: train-model
+      # Indicates that we want to push files in /mnt/output to object storage
+      outputs:
+        artifacts:
+          - name: output
+            path: /mnt/output
+            optional: true
+      script:
         image: onepanel/dl:v0.20.0
         command:
-          - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/tensorboard
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-volumeClaimTemplates:
-  # Provision volumes for storing data and output
-  - metadata:
-      name: data
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes: [ "ReadWriteOnce" ]
-      resources:
-        requests:
-          storage: 2Gi
+          - python
+          - '-u'
+        source: |
+          import json
+          import tensorflow as tf
+
+          mnist = tf.keras.datasets.mnist
+
+          (x_train, y_train),(x_test, y_test) = mnist.load_data()
+          x_train, x_test = x_train / 255.0, x_test / 255.0
+          x_train = x_train[..., tf.newaxis]
+          x_test = x_test[..., tf.newaxis]
+
+          model = tf.keras.Sequential([
+            tf.keras.layers.Conv2D(filters=32, kernel_size=5, activation='relu'),
+            tf.keras.layers.MaxPool2D(pool_size=2),
+            tf.keras.layers.Conv2D(filters=64, kernel_size=5, activation='relu'),
+            tf.keras.layers.MaxPool2D(pool_size=2),
+            tf.keras.layers.Flatten(),
+            tf.keras.layers.Dense(units=124, activation='relu'),
+            tf.keras.layers.Dropout(rate=0.75),
+            tf.keras.layers.Dense(units=10, activation='softmax')
+          ])
+          model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
+                        loss='sparse_categorical_crossentropy',
+                        metrics=['accuracy'])
+
+          # Write TensorBoard logs to /mnt/output
+          log_dir = '/mnt/output/tensorboard/'
+          tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
+
+          model.fit(x=x_train,
+                    y=y_train,
+                    epochs={{workflow.parameters.epochs}},
+                    validation_data=(x_test, y_test),
+                    callbacks=[tensorboard_callback])
+
+          # Store metrics for this task
+          loss, accuracy = model.evaluate(x_test, y_test)
+          metrics = [
+            {'name': 'accuracy', 'value': accuracy},
+            {'name': 'loss', 'value': loss}
+          ]
+          with open('/mnt/tmp/sys-metrics.json', 'w') as f:
+            json.dump(metrics, f)
+
+          # Save model
+          model.save('/mnt/output/model.h5')
+        volumeMounts:
+          # TensorBoard sidecar will automatically mount these volumes
+          # The `data` volume is mounted to support Keras datasets
+          # The `output` volume is mounted to save model output and share TensorBoard logs
+          - name: data
+            mountPath: /home/root/.keras/datasets
+          - name: output
+            mountPath: /mnt/output
+      nodeSelector:
+          "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: onepanel/dl:v0.20.0
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/tensorboard
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+  volumeClaimTemplates:
+    # Provision volumes for storing data and output
+    - metadata:
+        name: data
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 2Gi

db/yaml/workflows/tf-object-detection-training/20200812104328.yaml

@@ -0,0 +1,221 @@
+metadata:
+  name: "TF Object Detection Training"
+  kind: Workflow
+  version: 20200812104328
+  action: create
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/"
+  labels:
+    "created-by": "system"
+    "used-by": "cvat"
+spec:
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/tensorflow/models.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
+
+      - name: trainingsource
+        value: https://github.com/onepanelio/cvat-training.git
+        type: hidden
+        visibility: private
+
+      - name: revision
+        value: v1.13.0
+        type: hidden
+        visibility: private
+
+      - name: sys-annotation-path
+        value: annotation-dump/sample_dataset
+        displayName: Dataset path
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+
+      - name: sys-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
+
+      - name: ref-model
+        value: frcnn-res50-coco
+        displayName: Model
+        hint: TF Detection API's model to use for training.
+        type: select.select
+        visibility: public
+        options:
+          - name: 'Faster RCNN-ResNet 101-COCO'
+            value: frcnn-res101-coco
+          - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
+            value: frcnn-res101-low
+          - name: 'Faster RCNN-ResNet 50-COCO'
+            value: frcnn-res50-coco
+          - name: 'Faster RCNN-NAS-COCO'
+            value: frcnn-nas-coco
+          - name: 'SSD MobileNet V1-COCO'
+            value: ssd-mobilenet-v1-coco2
+          - name: 'SSD MobileNet V2-COCO'
+            value: ssd-mobilenet-v2-coco
+          - name: 'SSDLite MobileNet-COCO'
+            value: ssdlite-mobilenet-coco
+
+      - name: extras
+        value: |-
+          epochs=1000
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+
+      - name: sys-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
+
+      - name: sys-num-classes
+        value: '81'
+        hint: Number of classes
+        displayName: Number of classes
+        visibility: private
+
+      - name: tf-image
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        visibility: public
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        visibility: public
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+      - name: dump-format
+        value: cvat_tfrecord
+        visibility: public
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+      name: main
+    - container:
+        args:
+          - |
+            apt-get update && \
+            apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
+            pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
+            cd /mnt/src/tf/research && \
+            export PYTHONPATH=$PYTHONPATH:` + "`pwd`:`pwd`/slim" + ` && \
+            cd /mnt/src/train && \
+            python convert_workflow.py \
+              --extras="{{workflow.parameters.extras}}" \
+              --model="{{workflow.parameters.ref-model}}" \
+              --num_classes="{{workflow.parameters.sys-num-classes}}" \
+              --sys_finetune_checkpoint={{workflow.parameters.sys-finetune-checkpoint}}
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.sys-annotation-path}}'
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.sys-finetune-checkpoint}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: '{{workflow.parameters.revision}}'
+            name: src
+            path: /mnt/src/tf
+          - git:
+              repo: '{{workflow.parameters.trainingsource}}'
+              revision: 'optional-artifacts'
+            name: tsrc
+            path: /mnt/src/train
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.sys-output-path}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/tf-object-detection-training/20200824101019.yaml

@@ -0,0 +1,222 @@
+metadata:
+  name: "TF Object Detection Training"
+  kind: Workflow
+  version: 20200824101019
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/"
+  labels:
+    "created-by": "system"
+    "used-by": "cvat"
+spec:
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/tensorflow/models.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
+
+      - name: trainingsource
+        value: https://github.com/onepanelio/cvat-training.git
+        type: hidden
+        visibility: private
+
+      - name: revision
+        value: v1.13.0
+        type: hidden
+        visibility: private
+
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        displayName: Dataset path
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        visibility: private
+
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
+
+      - name: cvat-model
+        value: frcnn-res50-coco
+        displayName: Model
+        hint: TF Detection API's model to use for training.
+        type: select.select
+        visibility: public
+        options:
+          - name: 'Faster RCNN-ResNet 101-COCO'
+            value: frcnn-res101-coco
+          - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
+            value: frcnn-res101-low
+          - name: 'Faster RCNN-ResNet 50-COCO'
+            value: frcnn-res50-coco
+          - name: 'Faster RCNN-NAS-COCO'
+            value: frcnn-nas-coco
+          - name: 'SSD MobileNet V1-COCO'
+            value: ssd-mobilenet-v1-coco2
+          - name: 'SSD MobileNet V2-COCO'
+            value: ssd-mobilenet-v2-coco
+          - name: 'SSDLite MobileNet-COCO'
+            value: ssdlite-mobilenet-coco
+
+      - name: hyperparameters
+        value: |-
+          num-steps=10000
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
+
+      - name: cvat-num-classes
+        value: '81'
+        hint: Number of classes
+        displayName: Number of classes
+        visibility: private
+
+      - name: tf-image
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        visibility: public
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        visibility: public
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+      - name: dump-format
+        value: cvat_tfrecord
+        visibility: public
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+      name: main
+    - container:
+        args:
+          - |
+            apt-get update && \
+            apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
+            pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
+            cd /mnt/src/tf/research && \
+            export PYTHONPATH=$PYTHONPATH:` + "`pwd`:`pwd`" + `/slim && \
+            cd /mnt/src/train && \
+            python convert_workflow.py \
+              --extras="{{workflow.parameters.hyperparameters}}" \
+              --model="{{workflow.parameters.cvat-model}}" \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+              --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-finetune-checkpoint}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: '{{workflow.parameters.revision}}'
+            name: src
+            path: /mnt/src/tf
+          - git:
+              repo: '{{workflow.parameters.trainingsource}}'
+              revision: 'optional-artifacts'
+            name: tsrc
+            path: /mnt/src/train
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/tf-object-detection-training/20201115134934.yaml

@@ -1,221 +1,231 @@
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/tensorflow/models.git
-      displayName: Model source code
-      type: hidden
-      visibility: private
+metadata:
+  name: "TF Object Detection Training"
+  kind: Workflow
+  version: 20201115134934
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/"
+  labels:
+    "created-by": "system"
+    "used-by": "cvat"
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/tensorflow/models.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
 
-    - name: trainingsource
-      value: https://github.com/onepanelio/cvat-training.git
-      type: hidden
-      visibility: private
+      - name: trainingsource
+        value: https://github.com/onepanelio/cvat-training.git
+        type: hidden
+        visibility: private
 
-    - name: revision
-      value: v1.13.0
-      type: hidden
-      visibility: private
+      - name: revision
+        value: v1.13.0
+        type: hidden
+        visibility: private
 
-    - name: cvat-annotation-path
-      value: annotation-dump/sample_dataset
-      displayName: Dataset path
-      hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
-      visibility: private
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        displayName: Dataset path
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        visibility: private
 
-    - name: cvat-output-path
-      value: workflow-data/output/sample_output
-      hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
-      displayName: Workflow output path
-      visibility: private
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
 
-    - name: cvat-model
-      value: frcnn-res50-coco
-      displayName: Model
-      hint: TF Detection API's model to use for training.
-      type: select.select
-      visibility: public
-      options:
-        - name: 'Faster RCNN-ResNet 101-COCO'
-          value: frcnn-res101-coco
-        - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
-          value: frcnn-res101-low
-        - name: 'Faster RCNN-ResNet 50-COCO'
-          value: frcnn-res50-coco
-        - name: 'Faster RCNN-NAS-COCO'
-          value: frcnn-nas-coco
-        - name: 'SSD MobileNet V1-COCO'
-          value: ssd-mobilenet-v1-coco2
-        - name: 'SSD MobileNet V2-COCO'
-          value: ssd-mobilenet-v2-coco
-        - name: 'SSDLite MobileNet-COCO'
-          value: ssdlite-mobilenet-coco
+      - name: cvat-model
+        value: frcnn-res50-coco
+        displayName: Model
+        hint: TF Detection API's model to use for training.
+        type: select.select
+        visibility: public
+        options:
+          - name: 'Faster RCNN-ResNet 101-COCO'
+            value: frcnn-res101-coco
+          - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
+            value: frcnn-res101-low
+          - name: 'Faster RCNN-ResNet 50-COCO'
+            value: frcnn-res50-coco
+          - name: 'Faster RCNN-NAS-COCO'
+            value: frcnn-nas-coco
+          - name: 'SSD MobileNet V1-COCO'
+            value: ssd-mobilenet-v1-coco2
+          - name: 'SSD MobileNet V2-COCO'
+            value: ssd-mobilenet-v2-coco
+          - name: 'SSDLite MobileNet-COCO'
+            value: ssdlite-mobilenet-coco
 
-    - name: hyperparameters
-      value: |-
-        num-steps=10000
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+      - name: hyperparameters
+        value: |-
+          num-steps=10000
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: cvat-num-classes
-      value: '81'
-      hint: Number of classes
-      displayName: Number of classes
-      visibility: private
+      - name: cvat-num-classes
+        value: '81'
+        hint: Number of classes
+        displayName: Number of classes
+        visibility: private
 
-    - name: tf-image
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      visibility: public
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        visibility: public
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.select
-      name: sys-node-pool
-      value: Standard_D4s_v3
-      visibility: public
-      required: true
-      options:
-        - name: 'CPU: 2, RAM: 8GB'
-          value: Standard_D2s_v3
-        - name: 'CPU: 4, RAM: 16GB'
-          value: Standard_D4s_v3
-        - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
-          value: Standard_NC6
-    - name: dump-format
-      value: cvat_tfrecord
-      visibility: public
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: tensorflow
-    # Uncomment the lines below if you want to send Slack notifications
-    #    - arguments:
-    #        artifacts:
-    #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
-    #          name: metrics
-    #        parameters:
-    #        - name: status
-    #          value: '{{tasks.train-model.status}}'
-    #      dependencies:
-    #      - train-model
-    #      name: notify-in-slack
-    #      template: slack-notify-success
-  - name: tensorflow
-    container:
-      args:
-        - |
-          apt-get update && \
-          apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
-          pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
-          cd /mnt/src/tf/research && \
-          export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
-          cd /mnt/src/train && \
-          python convert_workflow.py \
-            --extras="{{workflow.parameters.hyperparameters}}" \
-            --model="{{workflow.parameters.cvat-model}}" \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-            --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
-        command: [sh, -c]
-        tty: true
-        args: ["tensorboard --logdir /mnt/output/"]
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
-        - name: models
-          path: /mnt/data/models/
-          optional: true
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-finetune-checkpoint}}'
-        - git:
-            repo: '{{workflow.parameters.source}}'
-            revision: '{{workflow.parameters.revision}}'
-          name: src
-          path: /mnt/src/tf
-        - git:
-            repo: '{{workflow.parameters.trainingsource}}'
-            revision: 'optional-artifacts'
-          name: tsrc
-          path: /mnt/src/train
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
-# Uncomment the lines below if you want to send Slack notifications
-#- container:
-#    args:
-#    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
-#      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
-#      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
-#    command:
-#    - sh
-#    - -c
-#    image: technosophos/slack-notify
-#  inputs:
-#    artifacts:
-#    - name: metrics
-#      optional: true
-#      path: /tmp/metrics.json
-#    parameters:
-#    - name: status
-#  name: slack-notify-success
-volumeClaimTemplates:
-  - metadata:
-      creationTimestamp: null
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      creationTimestamp: null
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        visibility: public
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+      - name: dump-format
+        value: cvat_tfrecord
+        visibility: public
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+    - name: tensorflow
+      container:
+        args:
+          - |
+            apt-get update && \
+            apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
+            pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
+            cd /mnt/src/tf/research && \
+            export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
+            cd /mnt/src/train && \
+            python convert_workflow.py \
+              --extras="{{workflow.parameters.hyperparameters}}" \
+              --model="{{workflow.parameters.cvat-model}}" \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+              --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command: [sh, -c]
+          tty: true
+          args: ["tensorboard --logdir /mnt/output/"]
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-finetune-checkpoint}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: '{{workflow.parameters.revision}}'
+            name: src
+            path: /mnt/src/tf
+          - git:
+              repo: '{{workflow.parameters.trainingsource}}'
+              revision: 'optional-artifacts'
+            name: tsrc
+            path: /mnt/src/train
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/tf-object-detection-training/20201130130433.yaml

@@ -1,221 +1,231 @@
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/tensorflow/models.git
-      displayName: Model source code
-      type: hidden
-      visibility: private
+metadata:
+  name: "TF Object Detection Training"
+  kind: Workflow
+  version: 20201130130433
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/"
+  labels:
+    "created-by": "system"
+    "used-by": "cvat"
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/tensorflow/models.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
 
-    - name: trainingsource
-      value: https://github.com/onepanelio/cvat-training.git
-      type: hidden
-      visibility: private
+      - name: trainingsource
+        value: https://github.com/onepanelio/cvat-training.git
+        type: hidden
+        visibility: private
 
-    - name: revision
-      value: v1.13.0
-      type: hidden
-      visibility: private
+      - name: revision
+        value: v1.13.0
+        type: hidden
+        visibility: private
 
-    - name: cvat-annotation-path
-      value: annotation-dump/sample_dataset
-      displayName: Dataset path
-      hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
-      visibility: private
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        displayName: Dataset path
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        visibility: private
 
-    - name: cvat-output-path
-      value: workflow-data/output/sample_output
-      hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
-      displayName: Workflow output path
-      visibility: private
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
 
-    - name: cvat-model
-      value: frcnn-res50-coco
-      displayName: Model
-      hint: TF Detection API's model to use for training.
-      type: select.select
-      visibility: public
-      options:
-        - name: 'Faster RCNN-ResNet 101-COCO'
-          value: frcnn-res101-coco
-        - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
-          value: frcnn-res101-low
-        - name: 'Faster RCNN-ResNet 50-COCO'
-          value: frcnn-res50-coco
-        - name: 'Faster RCNN-NAS-COCO'
-          value: frcnn-nas-coco
-        - name: 'SSD MobileNet V1-COCO'
-          value: ssd-mobilenet-v1-coco2
-        - name: 'SSD MobileNet V2-COCO'
-          value: ssd-mobilenet-v2-coco
-        - name: 'SSDLite MobileNet-COCO'
-          value: ssdlite-mobilenet-coco
+      - name: cvat-model
+        value: frcnn-res50-coco
+        displayName: Model
+        hint: TF Detection API's model to use for training.
+        type: select.select
+        visibility: public
+        options:
+          - name: 'Faster RCNN-ResNet 101-COCO'
+            value: frcnn-res101-coco
+          - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
+            value: frcnn-res101-low
+          - name: 'Faster RCNN-ResNet 50-COCO'
+            value: frcnn-res50-coco
+          - name: 'Faster RCNN-NAS-COCO'
+            value: frcnn-nas-coco
+          - name: 'SSD MobileNet V1-COCO'
+            value: ssd-mobilenet-v1-coco2
+          - name: 'SSD MobileNet V2-COCO'
+            value: ssd-mobilenet-v2-coco
+          - name: 'SSDLite MobileNet-COCO'
+            value: ssdlite-mobilenet-coco
 
-    - name: hyperparameters
-      value: |-
-        num-steps=10000
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+      - name: hyperparameters
+        value: |-
+          num-steps=10000
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: cvat-num-classes
-      value: '81'
-      hint: Number of classes
-      displayName: Number of classes
-      visibility: private
+      - name: cvat-num-classes
+        value: '81'
+        hint: Number of classes
+        displayName: Number of classes
+        visibility: private
 
-    - name: tf-image
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      visibility: public
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        visibility: public
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.select
-      name: sys-node-pool
-      value: Standard_D4s_v3
-      visibility: public
-      required: true
-      options:
-        - name: 'CPU: 2, RAM: 8GB'
-          value: Standard_D2s_v3
-        - name: 'CPU: 4, RAM: 16GB'
-          value: Standard_D4s_v3
-        - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
-          value: Standard_NC6
-    - name: dump-format
-      value: cvat_tfrecord
-      visibility: public
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: tensorflow
-    # Uncomment the lines below if you want to send Slack notifications
-    #    - arguments:
-    #        artifacts:
-    #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
-    #          name: metrics
-    #        parameters:
-    #        - name: status
-    #          value: '{{tasks.train-model.status}}'
-    #      dependencies:
-    #      - train-model
-    #      name: notify-in-slack
-    #      template: slack-notify-success
-  - name: tensorflow
-    container:
-      args:
-        - |
-          apt-get update && \
-          apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
-          pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
-          cd /mnt/src/tf/research && \
-          export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
-          cd /mnt/src/train && \
-          python convert_workflow.py \
-            --extras="{{workflow.parameters.hyperparameters}}" \
-            --model="{{workflow.parameters.cvat-model}}" \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-            --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
-        command: [sh, -c]
-        tty: true
-        args: ["tensorboard --logdir /mnt/output/"]
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
-        - name: models
-          path: /mnt/data/models/
-          optional: true
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
-        - git:
-            repo: '{{workflow.parameters.source}}'
-            revision: '{{workflow.parameters.revision}}'
-          name: src
-          path: /mnt/src/tf
-        - git:
-            repo: '{{workflow.parameters.trainingsource}}'
-            revision: 'optional-artifacts'
-          name: tsrc
-          path: /mnt/src/train
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
-# Uncomment the lines below if you want to send Slack notifications
-#- container:
-#    args:
-#    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
-#      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
-#      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
-#    command:
-#    - sh
-#    - -c
-#    image: technosophos/slack-notify
-#  inputs:
-#    artifacts:
-#    - name: metrics
-#      optional: true
-#      path: /tmp/metrics.json
-#    parameters:
-#    - name: status
-#  name: slack-notify-success
-volumeClaimTemplates:
-  - metadata:
-      creationTimestamp: null
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      creationTimestamp: null
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        visibility: public
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+      - name: dump-format
+        value: cvat_tfrecord
+        visibility: public
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+    - name: tensorflow
+      container:
+        args:
+          - |
+            apt-get update && \
+            apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
+            pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
+            cd /mnt/src/tf/research && \
+            export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
+            cd /mnt/src/train && \
+            python convert_workflow.py \
+              --extras="{{workflow.parameters.hyperparameters}}" \
+              --model="{{workflow.parameters.cvat-model}}" \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+              --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command: [sh, -c]
+          tty: true
+          args: ["tensorboard --logdir /mnt/output/"]
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: '{{workflow.parameters.revision}}'
+            name: src
+            path: /mnt/src/tf
+          - git:
+              repo: '{{workflow.parameters.trainingsource}}'
+              revision: 'optional-artifacts'
+            name: tsrc
+            path: /mnt/src/train
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/tf-object-detection-training/20201208155115.yaml

@@ -1,223 +1,233 @@
-entrypoint: main
-arguments:
-  parameters:
-    - name: source
-      value: https://github.com/tensorflow/models.git
-      displayName: Model source code
-      type: hidden
-      visibility: private
+metadata:
+  name: "TF Object Detection Training"
+  kind: Workflow
+  version: 20201208155115
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/"
+  labels:
+    "created-by": "system"
+    "used-by": "cvat"
+spec:
+  entrypoint: main
+  arguments:
+    parameters:
+      - name: source
+        value: https://github.com/tensorflow/models.git
+        displayName: Model source code
+        type: hidden
+        visibility: private
 
-    - name: trainingsource
-      value: https://github.com/onepanelio/cvat-training.git
-      type: hidden
-      visibility: private
+      - name: trainingsource
+        value: https://github.com/onepanelio/cvat-training.git
+        type: hidden
+        visibility: private
 
-    - name: revision
-      value: v1.13.0
-      type: hidden
-      visibility: private
+      - name: revision
+        value: v1.13.0
+        type: hidden
+        visibility: private
 
-    - name: cvat-annotation-path
-      value: annotation-dump/sample_dataset
-      displayName: Dataset path
-      hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
-      visibility: private
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        displayName: Dataset path
+        hint: Path to annotated data in default object storage (i.e S3). In CVAT, this parameter will be pre-populated.
+        visibility: private
 
-    - name: cvat-output-path
-      value: workflow-data/output/sample_output
-      hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
-      displayName: Workflow output path
-      visibility: private
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: private
 
-    - name: cvat-model
-      value: frcnn-res50-coco
-      displayName: Model
-      hint: TF Detection API's model to use for training.
-      type: select.select
-      visibility: public
-      options:
-        - name: 'Faster RCNN-ResNet 101-COCO'
-          value: frcnn-res101-coco
-        - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
-          value: frcnn-res101-low
-        - name: 'Faster RCNN-ResNet 50-COCO'
-          value: frcnn-res50-coco
-        - name: 'Faster RCNN-NAS-COCO'
-          value: frcnn-nas-coco
-        - name: 'SSD MobileNet V1-COCO'
-          value: ssd-mobilenet-v1-coco2
-        - name: 'SSD MobileNet V2-COCO'
-          value: ssd-mobilenet-v2-coco
-        - name: 'SSDLite MobileNet-COCO'
-          value: ssdlite-mobilenet-coco
+      - name: cvat-model
+        value: frcnn-res50-coco
+        displayName: Model
+        hint: TF Detection API's model to use for training.
+        type: select.select
+        visibility: public
+        options:
+          - name: 'Faster RCNN-ResNet 101-COCO'
+            value: frcnn-res101-coco
+          - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
+            value: frcnn-res101-low
+          - name: 'Faster RCNN-ResNet 50-COCO'
+            value: frcnn-res50-coco
+          - name: 'Faster RCNN-NAS-COCO'
+            value: frcnn-nas-coco
+          - name: 'SSD MobileNet V1-COCO'
+            value: ssd-mobilenet-v1-coco2
+          - name: 'SSD MobileNet V2-COCO'
+            value: ssd-mobilenet-v2-coco
+          - name: 'SSDLite MobileNet-COCO'
+            value: ssdlite-mobilenet-coco
 
-    - name: hyperparameters
-      value: |-
-        num-steps=10000
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
+      - name: hyperparameters
+        value: |-
+          num-steps=10000
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        hint: "Please refer to our <a href='https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model#arguments-optional' target='_blank'>documentation</a> for more information on parameters. Number of classes will be automatically populated if you had 'sys-num-classes' parameter in a workflow."
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: cvat-num-classes
-      value: '81'
-      hint: Number of classes
-      displayName: Number of classes
-      visibility: private
+      - name: cvat-num-classes
+        value: '81'
+        hint: Number of classes
+        displayName: Number of classes
+        visibility: private
 
-    - name: tf-image
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      visibility: public
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        visibility: public
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.select
-      name: sys-node-pool
-      value: Standard_D4s_v3
-      visibility: public
-      required: true
-      options:
-        - name: 'CPU: 2, RAM: 8GB'
-          value: Standard_D2s_v3
-        - name: 'CPU: 4, RAM: 16GB'
-          value: Standard_D4s_v3
-        - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
-          value: Standard_NC6
-    - name: dump-format
-      value: cvat_tfrecord
-      visibility: public
-templates:
-  - name: main
-    dag:
-      tasks:
-        - name: train-model
-          template: tensorflow
-    # Uncomment the lines below if you want to send Slack notifications
-    #    - arguments:
-    #        artifacts:
-    #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
-    #          name: metrics
-    #        parameters:
-    #        - name: status
-    #          value: '{{tasks.train-model.status}}'
-    #      dependencies:
-    #      - train-model
-    #      name: notify-in-slack
-    #      template: slack-notify-success
-  - name: tensorflow
-    container:
-      args:
-        - |
-          apt-get update && \
-          apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
-          pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
-          cd /mnt/src/tf/research && \
-          export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
-          cd /mnt/src/train && \
-          python convert_workflow.py \
-            --extras="{{workflow.parameters.hyperparameters}}" \
-            --model="{{workflow.parameters.cvat-model}}" \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-            --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    sidecars:
-      - name: tensorboard
-        image: tensorflow/tensorflow:2.3.0
-        command: [sh, -c]
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
-        args: ["tensorboard --logdir /mnt/output/"]
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
-        - name: models
-          path: /mnt/data/models/
-          optional: true
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
-        - git:
-            repo: '{{workflow.parameters.source}}'
-            revision: '{{workflow.parameters.revision}}'
-          name: src
-          path: /mnt/src/tf
-        - git:
-            repo: '{{workflow.parameters.trainingsource}}'
-            revision: 'optional-artifacts'
-          name: tsrc
-          path: /mnt/src/train
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-          {{.ArtifactRepositoryType}}:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
-# Uncomment the lines below if you want to send Slack notifications
-#- container:
-#    args:
-#    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
-#      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
-#      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
-#    command:
-#    - sh
-#    - -c
-#    image: technosophos/slack-notify
-#  inputs:
-#    artifacts:
-#    - name: metrics
-#      optional: true
-#      path: /tmp/metrics.json
-#    parameters:
-#    - name: status
-#  name: slack-notify-success
-volumeClaimTemplates:
-  - metadata:
-      creationTimestamp: null
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      creationTimestamp: null
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.select
+        name: sys-node-pool
+        value: Standard_D4s_v3
+        visibility: public
+        required: true
+        options:
+          - name: 'CPU: 2, RAM: 8GB'
+            value: Standard_D2s_v3
+          - name: 'CPU: 4, RAM: 16GB'
+            value: Standard_D4s_v3
+          - name: 'GPU: 1xK80, CPU: 6, RAM: 56GB'
+            value: Standard_NC6
+      - name: dump-format
+        value: cvat_tfrecord
+        visibility: public
+  templates:
+    - name: main
+      dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      # Uncomment the lines below if you want to send Slack notifications
+      #    - arguments:
+      #        artifacts:
+      #        - from: '{{tasks.train-model.outputs.artifacts.sys-metrics}}'
+      #          name: metrics
+      #        parameters:
+      #        - name: status
+      #          value: '{{tasks.train-model.status}}'
+      #      dependencies:
+      #      - train-model
+      #      name: notify-in-slack
+      #      template: slack-notify-success
+    - name: tensorflow
+      container:
+        args:
+          - |
+            apt-get update && \
+            apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
+            pip install pillow lxml Cython contextlib2 jupyter matplotlib numpy scipy boto3 pycocotools pyyaml google-cloud-storage && \
+            cd /mnt/src/tf/research && \
+            export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
+            cd /mnt/src/train && \
+            python convert_workflow.py \
+              --extras="{{workflow.parameters.hyperparameters}}" \
+              --model="{{workflow.parameters.cvat-model}}" \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+              --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      sidecars:
+        - name: tensorboard
+          image: tensorflow/tensorflow:2.3.0
+          command: [sh, -c]
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args: ["tensorboard --logdir /mnt/output/"]
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
+          - git:
+              repo: '{{workflow.parameters.source}}'
+              revision: '{{workflow.parameters.revision}}'
+            name: src
+            path: /mnt/src/tf
+          - git:
+              repo: '{{workflow.parameters.trainingsource}}'
+              revision: 'optional-artifacts'
+            name: tsrc
+            path: /mnt/src/train
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            "{{.ArtifactRepositoryType}}":
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  # Uncomment the lines below if you want to send Slack notifications
+  #- container:
+  #    args:
+  #    - SLACK_USERNAME=Onepanel SLACK_TITLE="{{workflow.name}} {{inputs.parameters.status}}"
+  #      SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd
+  #      SLACK_MESSAGE=$(cat /tmp/metrics.json)} ./slack-notify
+  #    command:
+  #    - sh
+  #    - -c
+  #    image: technosophos/slack-notify
+  #  inputs:
+  #    artifacts:
+  #    - name: metrics
+  #      optional: true
+  #      path: /tmp/metrics.json
+  #    parameters:
+  #    - name: status
+  #  name: slack-notify-success
+  volumeClaimTemplates:
+    - metadata:
+        creationTimestamp: null
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        creationTimestamp: null
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/tf-object-detection-training/20201223202929.yaml

@@ -1,165 +1,174 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/
-arguments:
-  parameters:
-    - name: cvat-annotation-path
-      value: annotation-dump/sample_dataset
-      displayName: Dataset path
-      hint: Path to annotated data (TFRecord format) in default object storage. In CVAT, this parameter will be pre-populated.
-      visibility: internal
+metadata:
+  name: "TF Object Detection Training"
+  kind: Workflow
+  version: 20201223202929
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/"
+  labels:
+    "created-by": "system"
+    "used-by": "cvat"
+spec:
+  arguments:
+    parameters:
+      - name: cvat-annotation-path
+        value: annotation-dump/sample_dataset
+        displayName: Dataset path
+        hint: Path to annotated data (TFRecord format) in default object storage. In CVAT, this parameter will be pre-populated.
+        visibility: internal
 
-    - name: cvat-output-path
-      value: workflow-data/output/sample_output
-      hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
-      displayName: Workflow output path
-      visibility: internal
+      - name: cvat-output-path
+        value: workflow-data/output/sample_output
+        hint: Path to store output artifacts in default object storage (i.e s3). In CVAT, this parameter will be pre-populated.
+        displayName: Workflow output path
+        visibility: internal
 
-    - name: cvat-model
-      value: frcnn-res50-coco
-      displayName: Model
-      hint: TF Detection API's model to use for training.
-      type: select.select
-      visibility: public
-      options:
-        - name: 'Faster RCNN-ResNet 101-COCO'
-          value: frcnn-res101-coco
-        - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
-          value: frcnn-res101-low
-        - name: 'Faster RCNN-ResNet 50-COCO'
-          value: frcnn-res50-coco
-        - name: 'Faster RCNN-NAS-COCO'
-          value: frcnn-nas-coco
-        - name: 'SSD MobileNet V1-COCO'
-          value: ssd-mobilenet-v1-coco2
-        - name: 'SSD MobileNet V2-COCO'
-          value: ssd-mobilenet-v2-coco
-        - name: 'SSDLite MobileNet-COCO'
-          value: ssdlite-mobilenet-coco
+      - name: cvat-model
+        value: frcnn-res50-coco
+        displayName: Model
+        hint: TF Detection API's model to use for training.
+        type: select.select
+        visibility: public
+        options:
+          - name: 'Faster RCNN-ResNet 101-COCO'
+            value: frcnn-res101-coco
+          - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
+            value: frcnn-res101-low
+          - name: 'Faster RCNN-ResNet 50-COCO'
+            value: frcnn-res50-coco
+          - name: 'Faster RCNN-NAS-COCO'
+            value: frcnn-nas-coco
+          - name: 'SSD MobileNet V1-COCO'
+            value: ssd-mobilenet-v1-coco2
+          - name: 'SSD MobileNet V2-COCO'
+            value: ssd-mobilenet-v2-coco
+          - name: 'SSDLite MobileNet-COCO'
+            value: ssdlite-mobilenet-coco
 
-    - name: hyperparameters
-      value: |-
-        num-steps=10000
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      hint: 'See <a href="https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model/#tfod-hyperparameters" target="_blank">documentation</a> for more information on parameters.'
+      - name: hyperparameters
+        value: |-
+          num-steps=10000
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        hint: 'See <a href="https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_annotation_model/#tfod-hyperparameters" target="_blank">documentation</a> for more information on parameters.'
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Select the last fine-tune checkpoint for this model. It may take up to 5 minutes for a recent checkpoint show here. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: cvat-num-classes
-      value: '10'
-      hint: Number of classes. In CVAT, this parameter will be pre-populated.
-      displayName: Number of classes
-      visibility: internal
+      - name: cvat-num-classes
+        value: '10'
+        hint: Number of classes. In CVAT, this parameter will be pre-populated.
+        displayName: Number of classes
+        visibility: internal
 
-    - name: tf-image
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      visibility: public
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        visibility: public
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - name: dump-format
-      value: cvat_tfrecord
-      visibility: public
+      - name: dump-format
+        value: cvat_tfrecord
+        visibility: public
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
 
-entrypoint: main
-templates:
-  - dag:
-      tasks:
-        - name: train-model
-          template: tensorflow
-    name: main
-  - container:
-      args:
-        - |
-          apt-get update && \
-          apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
-          pip install pillow lxml Cython contextlib2 matplotlib numpy scipy pycocotools pyyaml test-generator && \
-          cd /mnt/src/tf/research && \
-          export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
-          mkdir -p /mnt/src/protoc && \
-          wget -P /mnt/src/protoc https://github.com/protocolbuffers/protobuf/releases/download/v3.10.1/protoc-3.10.1-linux-x86_64.zip && \
-          cd /mnt/src/protoc/ && \
-          unzip protoc-3.10.1-linux-x86_64.zip && \
-          cd /mnt/src/tf/research/ && \
-          /mnt/src/protoc/bin/protoc object_detection/protos/*.proto --python_out=. && \
-          cd /mnt/src/train/workflows/tf-object-detection-training && \
-          python main.py \
-            --extras="{{workflow.parameters.hyperparameters}}" \
-            --model="{{workflow.parameters.cvat-model}}" \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-            --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    nodeSelector:
-      beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          s3:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
-        - name: models
-          path: /mnt/data/models/
-          optional: true
-          s3:
-            key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
-        - git:
-            repo: https://github.com/tensorflow/models.git
-            revision: v1.13.0
-          name: src
-          path: /mnt/src/tf
-        - git:
-            repo: https://github.com/onepanelio/templates.git
-          name: tsrc
-          path: /mnt/src/train
-    name: tensorflow
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-          s3:
-            key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
-volumeClaimTemplates:
-  - metadata:
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: train-model
+            template: tensorflow
+      name: main
+    - container:
+        args:
+          - |
+            apt-get update && \
+            apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
+            pip install pillow lxml Cython contextlib2 matplotlib numpy scipy pycocotools pyyaml test-generator && \
+            cd /mnt/src/tf/research && \
+            export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
+            mkdir -p /mnt/src/protoc && \
+            wget -P /mnt/src/protoc https://github.com/protocolbuffers/protobuf/releases/download/v3.10.1/protoc-3.10.1-linux-x86_64.zip && \
+            cd /mnt/src/protoc/ && \
+            unzip protoc-3.10.1-linux-x86_64.zip && \
+            cd /mnt/src/tf/research/ && \
+            /mnt/src/protoc/bin/protoc object_detection/protos/*.proto --python_out=. && \
+            cd /mnt/src/train/workflows/tf-object-detection-training && \
+            python main.py \
+              --extras="{{workflow.parameters.hyperparameters}}" \
+              --model="{{workflow.parameters.cvat-model}}" \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+              --sys_finetune_checkpoint={{workflow.parameters.cvat-finetune-checkpoint}}
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        beta.kubernetes.io/instance-type: '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            s3:
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-annotation-path}}'
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            s3:
+              key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
+          - git:
+              repo: https://github.com/tensorflow/models.git
+              revision: v1.13.0
+            name: src
+            path: /mnt/src/tf
+          - git:
+              repo: https://github.com/onepanelio/templates.git
+            name: tsrc
+            path: /mnt/src/train
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+            s3:
+              key: '{{workflow.namespace}}/{{workflow.parameters.cvat-output-path}}/{{workflow.name}}'
+  volumeClaimTemplates:
+    - metadata:
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workflows/tf-object-detection-training/20210118175809.yaml

@@ -1,260 +1,269 @@
-# source: https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/
-arguments:
-  parameters:
-    - name: cvat-annotation-path
-      value: 'artifacts/{{workflow.namespace}}/annotations/'
-      hint: Path to annotated data (COCO format) in default object storage. In CVAT, this parameter will be pre-populated.
-      displayName: Dataset path
-      visibility: internal
+metadata:
+  name: "TF Object Detection Training"
+  kind: Workflow
+  version: 20210118175809
+  action: update
+  source: "https://github.com/onepanelio/templates/blob/master/workflows/tf-object-detection-training/"
+  labels:
+    "created-by": "system"
+    "used-by": "cvat"
+spec:
+  arguments:
+    parameters:
+      - name: cvat-annotation-path
+        value: 'artifacts/{{workflow.namespace}}/annotations/'
+        hint: Path to annotated data (COCO format) in default object storage. In CVAT, this parameter will be pre-populated.
+        displayName: Dataset path
+        visibility: internal
 
-    - name: val-split
-      value: 10
-      displayName: Validation split size
-      type: input.number
-      visibility: public
-      hint: Enter validation set size in percentage of full dataset. (0 - 100)
+      - name: val-split
+        value: 10
+        displayName: Validation split size
+        type: input.number
+        visibility: public
+        hint: Enter validation set size in percentage of full dataset. (0 - 100)
 
-    - name: num-augmentation-cycles
-      value: 1
-      displayName: Number of augmentation cycles
-      type: input.number
-      visibility: public
-      hint: Number of augmentation cycles, zero means no data augmentation
+      - name: num-augmentation-cycles
+        value: 1
+        displayName: Number of augmentation cycles
+        type: input.number
+        visibility: public
+        hint: Number of augmentation cycles, zero means no data augmentation
 
-    - name: preprocessing-parameters
-      value: |-
-        RandomBrightnessContrast:
-            p: 0.2
-        GaussianBlur:
-            p: 0.3
-        GaussNoise:
-            p: 0.4
-        HorizontalFlip:
-            p: 0.5
-        VerticalFlip:
-            p: 0.3
-      displayName: Preprocessing parameters
-      visibility: public
-      type: textarea.textarea
-      hint: 'See <a href="https://albumentations.ai/docs/api_reference/augmentations/transforms/" target="_blank">documentation</a> for more information on parameters.'
+      - name: preprocessing-parameters
+        value: |-
+          RandomBrightnessContrast:
+              p: 0.2
+          GaussianBlur:
+              p: 0.3
+          GaussNoise:
+              p: 0.4
+          HorizontalFlip:
+              p: 0.5
+          VerticalFlip:
+              p: 0.3
+        displayName: Preprocessing parameters
+        visibility: public
+        type: textarea.textarea
+        hint: 'See <a href="https://albumentations.ai/docs/api_reference/augmentations/transforms/" target="_blank">documentation</a> for more information on parameters.'
 
-    - name: cvat-model
-      value: frcnn-res50-coco
-      displayName: Model
-      hint: TF Detection API's model to use for training.
-      type: select.select
-      visibility: public
-      options:
-        - name: 'Faster RCNN-ResNet 101-COCO'
-          value: frcnn-res101-coco
-        - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
-          value: frcnn-res101-low
-        - name: 'Faster RCNN-ResNet 50-COCO'
-          value: frcnn-res50-coco
-        - name: 'Faster RCNN-NAS-COCO'
-          value: frcnn-nas-coco
-        - name: 'SSD MobileNet V1-COCO'
-          value: ssd-mobilenet-v1-coco2
-        - name: 'SSD MobileNet V2-COCO'
-          value: ssd-mobilenet-v2-coco
-        - name: 'SSDLite MobileNet-COCO'
-          value: ssdlite-mobilenet-coco
+      - name: cvat-model
+        value: frcnn-res50-coco
+        displayName: Model
+        hint: TF Detection API's model to use for training.
+        type: select.select
+        visibility: public
+        options:
+          - name: 'Faster RCNN-ResNet 101-COCO'
+            value: frcnn-res101-coco
+          - name: 'Faster RCNN-ResNet 101-Low Proposal-COCO'
+            value: frcnn-res101-low
+          - name: 'Faster RCNN-ResNet 50-COCO'
+            value: frcnn-res50-coco
+          - name: 'Faster RCNN-NAS-COCO'
+            value: frcnn-nas-coco
+          - name: 'SSD MobileNet V1-COCO'
+            value: ssd-mobilenet-v1-coco2
+          - name: 'SSD MobileNet V2-COCO'
+            value: ssd-mobilenet-v2-coco
+          - name: 'SSDLite MobileNet-COCO'
+            value: ssdlite-mobilenet-coco
 
-    - name: cvat-num-classes
-      value: '10'
-      hint: Number of classes. In CVAT, this parameter will be pre-populated.
-      displayName: Number of classes
-      visibility: internal
+      - name: cvat-num-classes
+        value: '10'
+        hint: Number of classes. In CVAT, this parameter will be pre-populated.
+        displayName: Number of classes
+        visibility: internal
 
-    - name: hyperparameters
-      value: |-
-        num_steps: 10000
-      displayName: Hyperparameters
-      visibility: public
-      type: textarea.textarea
-      hint: 'See <a href="https://docs.onepanel.ai/docs/reference/workflows/training#tfod-hyperparameters" target="_blank">documentation</a> for more information on parameters.'
+      - name: hyperparameters
+        value: |-
+          num_steps: 10000
+        displayName: Hyperparameters
+        visibility: public
+        type: textarea.textarea
+        hint: 'See <a href="https://docs.onepanel.ai/docs/reference/workflows/training#tfod-hyperparameters" target="_blank">documentation</a> for more information on parameters.'
 
-    - name: dump-format
-      value: cvat_coco
-      displayName: CVAT dump format
-      visibility: private
+      - name: dump-format
+        value: cvat_coco
+        displayName: CVAT dump format
+        visibility: private
 
-    - name: cvat-finetune-checkpoint
-      value: ''
-      hint: Path to the last fine-tune checkpoint for this model in default object storage. Leave empty if this is the first time you're training this model.
-      displayName: Checkpoint path
-      visibility: public
+      - name: cvat-finetune-checkpoint
+        value: ''
+        hint: Path to the last fine-tune checkpoint for this model in default object storage. Leave empty if this is the first time you're training this model.
+        displayName: Checkpoint path
+        visibility: public
 
-    - name: tf-image
-      value: tensorflow/tensorflow:1.13.1-py3
-      type: select.select
-      displayName: Select TensorFlow image
-      visibility: public
-      hint: Select the GPU image if you are running on a GPU node pool
-      options:
-        - name: 'TensorFlow 1.13.1 CPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-py3'
-        - name: 'TensorFlow 1.13.1 GPU Image'
-          value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
+      - name: tf-image
+        value: tensorflow/tensorflow:1.13.1-py3
+        type: select.select
+        displayName: Select TensorFlow image
+        visibility: public
+        hint: Select the GPU image if you are running on a GPU node pool
+        options:
+          - name: 'TensorFlow 1.13.1 CPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-py3'
+          - name: 'TensorFlow 1.13.1 GPU Image'
+            value: 'tensorflow/tensorflow:1.13.1-gpu-py3'
 
-    - displayName: Node pool
-      hint: Name of node pool or group to run this workflow task
-      type: select.nodepool
-      name: sys-node-pool
-      value: {{.DefaultNodePoolOption}}
-      visibility: public
-      required: true
+      - displayName: Node pool
+        hint: Name of node pool or group to run this workflow task
+        type: select.nodepool
+        name: sys-node-pool
+        value: "{{.DefaultNodePoolOption}}"
+        visibility: public
+        required: true
 
-entrypoint: main
-templates:
-  - dag:
-      tasks:
-        - name: preprocessing
-          template: preprocessing
-        - name: train-model
-          template: tensorflow
-          dependencies: [preprocessing]
-          arguments:
-            artifacts:
-              - name: data
-                from: "{{tasks.preprocessing.outputs.artifacts.processed-data}}"
-    name: main
-  - container:
-      args:
-        - |
-          apt-get update && \
-          apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
-          pip install --upgrade pip && \
-          pip install pillow lxml Cython contextlib2 matplotlib numpy scipy pycocotools pyyaml test-generator && \
-          cd /mnt/src/tf/research && \
-          export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
-          mkdir -p /mnt/src/protoc && \
-          wget -P /mnt/src/protoc https://github.com/protocolbuffers/protobuf/releases/download/v3.10.1/protoc-3.10.1-linux-x86_64.zip && \
-          cd /mnt/src/protoc/ && \
-          unzip protoc-3.10.1-linux-x86_64.zip && \
-          cd /mnt/src/tf/research/ && \
-          /mnt/src/protoc/bin/protoc object_detection/protos/*.proto --python_out=. && \
-          cd /mnt/src/train/workflows/tf-object-detection-training && \
-          python main.py \
-            --extras="{{workflow.parameters.hyperparameters}}" \
-            --model="{{workflow.parameters.cvat-model}}" \
-            --num_classes="{{workflow.parameters.cvat-num-classes}}" \
-            --sys_finetune_checkpoint="{{workflow.parameters.cvat-finetune-checkpoint}}" \
-            --from_preprocessing=True
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: processed-data
-        - mountPath: /mnt/output
-          name: output
-      workingDir: /mnt/src
-    nodeSelector:
-      {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-        - name: models
-          path: /mnt/data/models/
-          optional: true
-          s3:
-            key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
-        - git:
-            repo: https://github.com/tensorflow/models.git
-            revision: v1.13.0
-          name: src
-          path: /mnt/src/tf
-        - git:
-            repo: https://github.com/onepanelio/templates.git
-            revision: v0.18.0
-          name: tsrc
-          path: /mnt/src/train
-    name: tensorflow
-    outputs:
-      artifacts:
-        - name: model
-          optional: true
-          path: /mnt/output
-    sidecars:
-      - name: tensorboard
-        image: '{{workflow.parameters.tf-image}}'
+  entrypoint: main
+  templates:
+    - dag:
+        tasks:
+          - name: preprocessing
+            template: preprocessing
+          - name: train-model
+            template: tensorflow
+            dependencies: [preprocessing]
+            arguments:
+              artifacts:
+                - name: data
+                  from: "{{tasks.preprocessing.outputs.artifacts.processed-data}}"
+      name: main
+    - container:
+        args:
+          - |
+            apt-get update && \
+            apt-get install -y python3-pip git wget unzip libglib2.0-0 libsm6 libxext6 libxrender-dev && \
+            pip install --upgrade pip && \
+            pip install pillow lxml Cython contextlib2 matplotlib numpy scipy pycocotools pyyaml test-generator && \
+            cd /mnt/src/tf/research && \
+            export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim && \
+            mkdir -p /mnt/src/protoc && \
+            wget -P /mnt/src/protoc https://github.com/protocolbuffers/protobuf/releases/download/v3.10.1/protoc-3.10.1-linux-x86_64.zip && \
+            cd /mnt/src/protoc/ && \
+            unzip protoc-3.10.1-linux-x86_64.zip && \
+            cd /mnt/src/tf/research/ && \
+            /mnt/src/protoc/bin/protoc object_detection/protos/*.proto --python_out=. && \
+            cd /mnt/src/train/workflows/tf-object-detection-training && \
+            python main.py \
+              --extras="{{workflow.parameters.hyperparameters}}" \
+              --model="{{workflow.parameters.cvat-model}}" \
+              --num_classes="{{workflow.parameters.cvat-num-classes}}" \
+              --sys_finetune_checkpoint="{{workflow.parameters.cvat-finetune-checkpoint}}" \
+              --from_preprocessing=True
         command:
           - sh
-          - '-c'
-        env:
-          - name: ONEPANEL_INTERACTIVE_SIDECAR
-            value: 'true'
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: processed-data
+          - mountPath: /mnt/output
+            name: output
+        workingDir: /mnt/src
+      nodeSelector:
+        "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+          - name: models
+            path: /mnt/data/models/
+            optional: true
+            s3:
+              key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
+          - git:
+              repo: https://github.com/tensorflow/models.git
+              revision: v1.13.0
+            name: src
+            path: /mnt/src/tf
+          - git:
+              repo: https://github.com/onepanelio/templates.git
+              revision: v0.18.0
+            name: tsrc
+            path: /mnt/src/train
+      name: tensorflow
+      outputs:
+        artifacts:
+          - name: model
+            optional: true
+            path: /mnt/output
+      sidecars:
+        - name: tensorboard
+          image: '{{workflow.parameters.tf-image}}'
+          command:
+            - sh
+            - '-c'
+          env:
+            - name: ONEPANEL_INTERACTIVE_SIDECAR
+              value: 'true'
+          args:
+            # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+            - tensorboard --logdir /mnt/output/checkpoints/
+          ports:
+            - containerPort: 6006
+              name: tensorboard
+    - container:
         args:
-          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
-          - tensorboard --logdir /mnt/output/checkpoints/
-        ports:
-          - containerPort: 6006
-            name: tensorboard
-  - container:
-      args:
-        - |
-          pip install --upgrade pip &&\
-          pip install opencv-python albumentations tqdm pyyaml pycocotools && \
-          cd /mnt/src/preprocessing/workflows/albumentations-preprocessing && \
-          python -u main.py \
-            --data_aug_params="{{workflow.parameters.preprocessing-parameters}}" \
-            --format="tfrecord" \
-            --val_split={{workflow.parameters.val-split}} \
-            --aug_steps={{workflow.parameters.num-augmentation-cycles}}
-      command:
-        - sh
-        - -c
-      image: '{{workflow.parameters.tf-image}}'
-      volumeMounts:
-        - mountPath: /mnt/data
-          name: data
-        - mountPath: /mnt/output
-          name: processed-data
-      workingDir: /mnt/src
-    nodeSelector:
-      {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
-    inputs:
-      artifacts:
-        - name: data
-          path: /mnt/data/datasets/
-          s3:
-            key: '{{workflow.parameters.cvat-annotation-path}}'
-        - git:
-            repo: https://github.com/onepanelio/templates.git
-            revision: v0.18.0
-          name: src
-          path: /mnt/src/preprocessing
-    name: preprocessing
-    outputs:
-      artifacts:
-        - name: processed-data
-          optional: true
-          path: /mnt/output
-volumeClaimTemplates:
-  - metadata:
-      name: data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      name: processed-data
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
-  - metadata:
-      name: output
-    spec:
-      accessModes:
-        - ReadWriteOnce
-      resources:
-        requests:
-          storage: 200Gi
+          - |
+            pip install --upgrade pip &&\
+            pip install opencv-python albumentations tqdm pyyaml pycocotools && \
+            cd /mnt/src/preprocessing/workflows/albumentations-preprocessing && \
+            python -u main.py \
+              --data_aug_params="{{workflow.parameters.preprocessing-parameters}}" \
+              --format="tfrecord" \
+              --val_split={{workflow.parameters.val-split}} \
+              --aug_steps={{workflow.parameters.num-augmentation-cycles}}
+        command:
+          - sh
+          - -c
+        image: '{{workflow.parameters.tf-image}}'
+        volumeMounts:
+          - mountPath: /mnt/data
+            name: data
+          - mountPath: /mnt/output
+            name: processed-data
+        workingDir: /mnt/src
+      nodeSelector:
+        "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
+      inputs:
+        artifacts:
+          - name: data
+            path: /mnt/data/datasets/
+            s3:
+              key: '{{workflow.parameters.cvat-annotation-path}}'
+          - git:
+              repo: https://github.com/onepanelio/templates.git
+              revision: v0.18.0
+            name: src
+            path: /mnt/src/preprocessing
+      name: preprocessing
+      outputs:
+        artifacts:
+          - name: processed-data
+            optional: true
+            path: /mnt/output
+  volumeClaimTemplates:
+    - metadata:
+        name: data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        name: processed-data
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi
+    - metadata:
+        name: output
+      spec:
+        accessModes:
+          - ReadWriteOnce
+        resources:
+          requests:
+            storage: 200Gi

db/yaml/workspaces/cvat/20200528140124.yaml

@@ -0,0 +1,105 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200528140124
+  action: create
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.7.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.7.0
+      ports:
+        - containerPort: 80
+          name: http
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes
+  # postExecutionWorkflow:
+  #   entrypoint: main
+  #   templates:
+  #   - name: main
+  #     dag:
+  #        tasks:
+  #        - name: slack-notify
+  #          template: slack-notify
+  #   - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20200626113635.yaml

@@ -0,0 +1,116 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200626113635
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.7.6
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.7.5
+      ports:
+        - containerPort: 80
+          name: http
+    - name: filesyncer
+      image: onepanel/filesyncer:v0.0.4
+      command: ['python3', 'main.py']
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+      timeout: 600s
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+      timeout: 600s
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20200704151301.yaml

@@ -0,0 +1,118 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200704151301
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.7.10-stable
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.7.10-stable
+      ports:
+        - containerPort: 80
+          name: http
+  # Uncomment following lines to enable S3 FileSyncer
+  # Refer to https://docs.onepanel.ai/docs/getting-started/use-cases/computervision/annotation/cvat/cvat_quick_guide#setting-up-environment-variables
+  #- name: filesyncer
+  #  image: onepanel/filesyncer:v0.0.4
+  #  command: ['python3', 'main.py']
+  #  volumeMounts:
+  #  - name: share
+  #    mountPath: /mnt/share
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+      timeout: 600s
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+      timeout: 600s
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20200724220450.yaml

@@ -0,0 +1,135 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200724220450
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: storage-prefix
+        displayName: Directory in default object storage
+        value: data
+        hint: Location of data and models in default object storage, will continuously sync to '/mnt/share'
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.7.10-stable
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.7.10-stable
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: "onepanel/filesyncer:{{.ArtifactRepositoryType}}"
+      args:
+        - download
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workspace.parameters.storage-prefix}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+      timeout: 600s
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+      timeout: 600s
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20200812113316.yaml

@@ -0,0 +1,144 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200812113316
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location to sync raw input, models and checkpoints from default object storage. Note that this will be relative to the current namespace.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.12.0_cvat.1.0.0-beta.2-cuda
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.12.0_cvat.1.0.0-beta.2
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: "onepanel/filesyncer:{{.ArtifactRepositoryType}}"
+      imagePullPolicy: Always
+      args:
+        - download
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+      timeout: 600s
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+      timeout: 600s
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20200824101905.yaml

@@ -0,0 +1,144 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200824101905
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location to sync raw input, models and checkpoints from default object storage. Note that this will be relative to the current namespace.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.12.0-rc.6_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.12.0-rc.1_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: "onepanel/filesyncer:{{.ArtifactRepositoryType}}"
+      imagePullPolicy: Always
+      args:
+        - download
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+      timeout: 600s
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+      timeout: 600s
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20200825154403.yaml

@@ -0,0 +1,144 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200825154403
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location to sync raw input, models and checkpoints from default object storage. Note that this will be relative to the current namespace.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.12.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.12.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: "onepanel/filesyncer:{{.ArtifactRepositoryType}}"
+      imagePullPolicy: Always
+      args:
+        - download
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+      timeout: 600s
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+      timeout: 600s
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20200826185926.yaml

@@ -0,0 +1,156 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20200826185926
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location to sync raw input, models and checkpoints from default object storage. Note that this will be relative to the current namespace.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.12.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.12.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: "onepanel/filesyncer:{{.ArtifactRepositoryType}}"
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+      timeout: 600s
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+      timeout: 600s
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20201001070806.yaml

@@ -0,0 +1,154 @@
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20201001070806
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location to sync raw input, models and checkpoints from default object storage. Note that this will be relative to the current namespace.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.12.1_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.12.1_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: "onepanel/filesyncer:{{.ArtifactRepositoryType}}"
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20201016170415.yaml

@@ -1,147 +1,154 @@
-# Workspace arguments
-arguments:
-  parameters:
-    - name: sync-directory
-      displayName: Directory to sync raw input and training output
-      value: workflow-data
-      hint: Location to sync raw input, models and checkpoints from default object storage. Note that this will be relative to the current namespace.
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:0.14.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /home/django/data
-      - name: ONEPANEL_SYNC_DIRECTORY
-        value: '{{workspace.parameters.sync-directory}}'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: data
-        mountPath: /home/django/data
-      - name: keys
-        mountPath: /home/django/keys
-      - name: logs
-        mountPath: /home/django/logs
-      - name: models
-        mountPath: /home/django/models
-      - name: share
-        mountPath: /home/django/share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:0.14.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  # You can add multiple FileSyncer sidecar containers if needed
-  - name: filesyncer
-    image: onepanel/filesyncer:{{.ArtifactRepositoryType}}
-    imagePullPolicy: Always
-    args:
-      - download
-      - -server-prefix=/sys/filesyncer
-    env:
-      - name: FS_PATH
-        value: /mnt/share
-      - name: FS_PREFIX
-        value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
-    volumeMounts:
-      - name: share
-        mountPath: /mnt/share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-# Uncomment the lines below if you want to send Slack notifications
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20201016170415
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location to sync raw input, models and checkpoints from default object storage. Note that this will be relative to the current namespace.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.14.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /home/django/data
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: data
+          mountPath: /home/django/data
+        - name: keys
+          mountPath: /home/django/keys
+        - name: logs
+          mountPath: /home/django/logs
+        - name: models
+          mountPath: /home/django/models
+        - name: share
+          mountPath: /home/django/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.14.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: "onepanel/filesyncer:{{.ArtifactRepositoryType}}"
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20201102104048.yaml

@@ -1,159 +1,166 @@
-# Workspace arguments
-arguments:
-  parameters:
-    - name: sync-directory
-      displayName: Directory to sync raw input and training output
-      value: workflow-data
-      hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:0.15.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_KEYS_DIR
-        value: /cvat/keys
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MODELS_DIR
-        value: /cvat/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: ONEPANEL_SYNC_DIRECTORY
-        value: '{{workspace.parameters.sync-directory}}'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:0.15.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  # You can add multiple FileSyncer sidecar containers if needed
-  - name: filesyncer
-    image: onepanel/filesyncer:s3
-    imagePullPolicy: Always
-    args:
-      - download
-      - -server-prefix=/sys/filesyncer
-    env:
-      - name: FS_PATH
-        value: /mnt/share
-      - name: FS_PREFIX
-        value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
-    volumeMounts:
-      - name: share
-        mountPath: /mnt/share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
-# DAG Workflow to be executed once a Workspace action completes (optional)
-# Uncomment the lines below if you want to send Slack notifications
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20201102104048
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.15.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_KEYS_DIR
+          value: /cvat/keys
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MODELS_DIR
+          value: /cvat/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.15.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: onepanel/filesyncer:s3
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20201113094916.yaml

@@ -1,159 +1,166 @@
-# Workspace arguments
-arguments:
-  parameters:
-    - name: sync-directory
-      displayName: Directory to sync raw input and training output
-      value: workflow-data
-      hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:0.16.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_KEYS_DIR
-        value: /cvat/keys
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MODELS_DIR
-        value: /cvat/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: ONEPANEL_SYNC_DIRECTORY
-        value: '{{workspace.parameters.sync-directory}}'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:0.16.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  # You can add multiple FileSyncer sidecar containers if needed
-  - name: filesyncer
-    image: onepanel/filesyncer:s3
-    imagePullPolicy: Always
-    args:
-      - download
-      - -server-prefix=/sys/filesyncer
-    env:
-      - name: FS_PATH
-        value: /mnt/share
-      - name: FS_PREFIX
-        value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
-    volumeMounts:
-      - name: share
-        mountPath: /mnt/share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
-# DAG Workflow to be executed once a Workspace action completes (optional)
-# Uncomment the lines below if you want to send Slack notifications
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20201113094916
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.16.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_KEYS_DIR
+          value: /cvat/keys
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MODELS_DIR
+          value: /cvat/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.16.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: onepanel/filesyncer:s3
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20201115133046.yaml

@@ -1,161 +1,168 @@
-# Workspace arguments
-arguments:
-  parameters:
-    - name: sync-directory
-      displayName: Directory to sync raw input and training output
-      value: workflow-data
-      hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:0.16.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MEDIA_DATA_DIR
-        value: /cvat/data/data
-      - name: CVAT_KEYS_DIR
-        value: /cvat/data/keys
-      - name: CVAT_MODELS_DIR
-        value: /cvat/data/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: ONEPANEL_SYNC_DIRECTORY
-        value: '{{workspace.parameters.sync-directory}}'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:0.16.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  # You can add multiple FileSyncer sidecar containers if needed
-  - name: filesyncer
-    image: onepanel/filesyncer:s3
-    imagePullPolicy: Always
-    args:
-      - download
-      - -server-prefix=/sys/filesyncer
-    env:
-      - name: FS_PATH
-        value: /mnt/share
-      - name: FS_PREFIX
-        value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
-    volumeMounts:
-      - name: share
-        mountPath: /mnt/share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
-# DAG Workflow to be executed once a Workspace action completes (optional)
-# Uncomment the lines below if you want to send Slack notifications
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20201115133046
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.16.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.16.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: onepanel/filesyncer:s3
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20201211161117.yaml

@@ -1,163 +1,170 @@
-# Workspace arguments
-arguments:
-  parameters:
-    - name: sync-directory
-      displayName: Directory to sync raw input and training output
-      value: workflow-data
-      hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:0.16.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MEDIA_DATA_DIR
-        value: /cvat/data/data
-      - name: CVAT_KEYS_DIR
-        value: /cvat/data/keys
-      - name: CVAT_MODELS_DIR
-        value: /cvat/data/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: ONEPANEL_SYNC_DIRECTORY
-        value: '{{workspace.parameters.sync-directory}}'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:0.16.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  # You can add multiple FileSyncer sidecar containers if needed
-  - name: filesyncer
-    image: onepanel/filesyncer:s3
-    imagePullPolicy: Always
-    args:
-      - download
-      - -server-prefix=/sys/filesyncer
-    env:
-      - name: FS_PATH
-        value: /mnt/share
-      - name: FS_PREFIX
-        value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
-    volumeMounts:
-      - name: share
-        mountPath: /mnt/share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
-# DAG Workflow to be executed once a Workspace action completes (optional)
-# Uncomment the lines below if you want to send Slack notifications
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20201211161117
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.16.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.16.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: onepanel/filesyncer:s3
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20210107094725.yaml

@@ -1,163 +1,170 @@
-# Workspace arguments
-arguments:
-  parameters:
-    - name: sync-directory
-      displayName: Directory to sync raw input and training output
-      value: workflow-data
-      hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:0.17.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MEDIA_DATA_DIR
-        value: /cvat/data/data
-      - name: CVAT_KEYS_DIR
-        value: /cvat/data/keys
-      - name: CVAT_MODELS_DIR
-        value: /cvat/data/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: ONEPANEL_SYNC_DIRECTORY
-        value: '{{workspace.parameters.sync-directory}}'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:0.17.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  # You can add multiple FileSyncer sidecar containers if needed
-  - name: filesyncer
-    image: onepanel/filesyncer:0.17.0
-    imagePullPolicy: Always
-    args:
-      - download
-      - -server-prefix=/sys/filesyncer
-    env:
-      - name: FS_PATH
-        value: /mnt/share
-      - name: FS_PREFIX
-        value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
-    volumeMounts:
-      - name: share
-        mountPath: /mnt/share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
-# DAG Workflow to be executed once a Workspace action completes (optional)
-# Uncomment the lines below if you want to send Slack notifications
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20210107094725
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  # Workspace arguments
+  arguments:
+    parameters:
+      - name: sync-directory
+        displayName: Directory to sync raw input and training output
+        value: workflow-data
+        hint: Location (relative to current namespace) to sync raw input, models and checkpoints from default object storage to '/share'.
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:0.17.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: ONEPANEL_SYNC_DIRECTORY
+          value: '{{workspace.parameters.sync-directory}}'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:0.17.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    # You can add multiple FileSyncer sidecar containers if needed
+    - name: filesyncer
+      image: onepanel/filesyncer:0.17.0
+      imagePullPolicy: Always
+      args:
+        - download
+        - -server-prefix=/sys/filesyncer
+      env:
+        - name: FS_PATH
+          value: /mnt/share
+        - name: FS_PREFIX
+          value: '{{workflow.namespace}}/{{workspace.parameters.sync-directory}}'
+      volumeMounts:
+        - name: share
+          mountPath: /mnt/share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  # Uncomment the lines below if you want to send Slack notifications
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/cvat/20210129134326.yaml

@@ -1,134 +1,141 @@
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:v0.18.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MEDIA_DATA_DIR
-        value: /cvat/data/data
-      - name: CVAT_KEYS_DIR
-        value: /cvat/data/keys
-      - name: CVAT_MODELS_DIR
-        value: /cvat/data/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
-        value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
-      - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
-        value: 'key=used-by,value=cvat'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:v0.18.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.18.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20210129134326
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.18.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
+          value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
+        - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
+          value: 'key=used-by,value=cvat'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.18.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.18.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi

db/yaml/workspaces/cvat/20210224180017.yaml

@@ -1,134 +1,141 @@
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:v0.19.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MEDIA_DATA_DIR
-        value: /cvat/data/data
-      - name: CVAT_KEYS_DIR
-        value: /cvat/data/keys
-      - name: CVAT_MODELS_DIR
-        value: /cvat/data/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
-        value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
-      - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
-        value: 'key=used-by,value=cvat'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:v0.19.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.19.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20210224180017
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.19.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
+          value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
+        - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
+          value: 'key=used-by,value=cvat'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.19.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.19.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi

db/yaml/workspaces/cvat/20210323175655.yaml

@@ -1,134 +1,141 @@
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:v0.19.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MEDIA_DATA_DIR
-        value: /cvat/data/data
-      - name: CVAT_KEYS_DIR
-        value: /cvat/data/keys
-      - name: CVAT_MODELS_DIR
-        value: /cvat/data/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
-        value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
-      - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
-        value: 'key=used-by,value=cvat'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:v0.19.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.20.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20210323175655
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.19.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
+          value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
+        - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
+          value: 'key=used-by,value=cvat'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.19.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.20.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi

db/yaml/workspaces/cvat/20210719190719.yaml

@@ -1,134 +1,141 @@
-containers:
-  - name: cvat-db
-    image: postgres:10-alpine
-    env:
-      - name: POSTGRES_USER
-        value: root
-      - name: POSTGRES_DB
-        value: cvat
-      - name: POSTGRES_HOST_AUTH_METHOD
-        value: trust
-      - name: PGDATA
-        value: /var/lib/psql/data
-    ports:
-      - containerPort: 5432
-        name: tcp
-    volumeMounts:
-      - name: db
-        mountPath: /var/lib/psql
-  - name: cvat-redis
-    image: redis:4.0-alpine
-    ports:
-      - containerPort: 6379
-        name: tcp
-  - name: cvat
-    image: onepanel/cvat:v0.19.0_cvat.1.0.0
-    env:
-      - name: DJANGO_MODWSGI_EXTRA_ARGS
-        value: ""
-      - name: ALLOWED_HOSTS
-        value: '*'
-      - name: CVAT_REDIS_HOST
-        value: localhost
-      - name: CVAT_POSTGRES_HOST
-        value: localhost
-      - name: CVAT_SHARE_URL
-        value: /cvat/data
-      - name: CVAT_SHARE_DIR
-        value: /share
-      - name: CVAT_DATA_DIR
-        value: /cvat/data
-      - name: CVAT_MEDIA_DATA_DIR
-        value: /cvat/data/data
-      - name: CVAT_KEYS_DIR
-        value: /cvat/data/keys
-      - name: CVAT_MODELS_DIR
-        value: /cvat/data/models
-      - name: CVAT_LOGS_DIR
-        value: /cvat/logs
-      - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
-        value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
-      - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
-        value: 'key=used-by,value=cvat'
-      - name: NVIDIA_VISIBLE_DEVICES
-        value: all
-      - name: NVIDIA_DRIVER_CAPABILITIES
-        value: compute,utility
-      - name: NVIDIA_REQUIRE_CUDA
-        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: http
-    volumeMounts:
-      - name: cvat-data
-        mountPath: /cvat
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-  - name: cvat-ui
-    image: onepanel/cvat-ui:v0.19.0_cvat.1.0.0
-    ports:
-      - containerPort: 80
-        name: http
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v1.0.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: share
-        mountPath: /share
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: cvat-ui
-    port: 80
-    protocol: TCP
-    targetPort: 80
-  - name: cvat
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
-      - queryParams:
-          id:
-            regex: \d+.*
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-volumeClaimTemplates:
-  - metadata:
-      name: db
-    spec:
-      accessModes: ["ReadWriteOnce"]
-      resources:
-        requests:
-          storage: 20Gi
+metadata:
+  name: CVAT
+  kind: Workspace
+  version: 20210719190719
+  action: update
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT)"
+spec:
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v0.19.0_cvat.1.0.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
+          value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
+        - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
+          value: 'key=used-by,value=cvat'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v0.19.0_cvat.1.0.0
+      ports:
+        - containerPort: 80
+          name: http
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v1.0.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: ["ReadWriteOnce"]
+        resources:
+          requests:
+            storage: 20Gi

db/yaml/workspaces/cvat_1_6_0/20211028205201.yaml

@@ -0,0 +1,143 @@
+metadata:
+  name: CVAT_1.6.0
+  kind: Workspace
+  version: 20211028205201
+  action: create
+  description: "Powerful and efficient Computer Vision Annotation Tool (CVAT 1.6.0)"
+spec:
+  containers:
+    - name: cvat-db
+      image: postgres:10-alpine
+      env:
+        - name: POSTGRES_USER
+          value: root
+        - name: POSTGRES_DB
+          value: cvat
+        - name: POSTGRES_HOST_AUTH_METHOD
+          value: trust
+        - name: PGDATA
+          value: /var/lib/psql/data
+      ports:
+        - containerPort: 5432
+          name: tcp
+      volumeMounts:
+        - name: db
+          mountPath: /var/lib/psql
+    - name: cvat-redis
+      image: redis:4.0-alpine
+      ports:
+        - containerPort: 6379
+          name: tcp
+    - name: cvat
+      image: onepanel/cvat:v1.0.2_cvat.1.6.0
+      env:
+        - name: DJANGO_MODWSGI_EXTRA_ARGS
+          value: ""
+        - name: ALLOWED_HOSTS
+          value: '*'
+        - name: CVAT_REDIS_HOST
+          value: localhost
+        - name: CVAT_POSTGRES_HOST
+          value: localhost
+        - name: CVAT_SHARE_URL
+          value: /cvat/data
+        - name: CVAT_SHARE_DIR
+          value: /share
+        - name: CVAT_DATA_DIR
+          value: /cvat/data
+        - name: CVAT_MEDIA_DATA_DIR
+          value: /cvat/data/data
+        - name: CVAT_KEYS_DIR
+          value: /cvat/data/keys
+        - name: CVAT_MODELS_DIR
+          value: /cvat/data/models
+        - name: CVAT_LOGS_DIR
+          value: /cvat/logs
+        - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
+          value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
+        - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
+          value: 'key=used-by,value=cvat'
+        - name: NVIDIA_VISIBLE_DEVICES
+          value: all
+        - name: NVIDIA_DRIVER_CAPABILITIES
+          value: compute,utility
+        - name: NVIDIA_REQUIRE_CUDA
+          value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+        - name: CVAT_SERVERLESS
+          value: True
+      ports:
+        - containerPort: 8080
+          name: http
+      volumeMounts:
+        - name: cvat-data
+          mountPath: /cvat
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+    - name: cvat-ui
+      image: onepanel/cvat-ui:v1.0.2_cvat.1.6.0
+      ports:
+        - containerPort: 80
+          name: http
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v1.0.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: share
+          mountPath: /share
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: cvat-ui
+      port: 80
+      protocol: TCP
+      targetPort: 80
+    - name: cvat
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            regex: \/?api.*|\/?git.*|\/?tensorflow.*|\/?onepanelio.*|\/?tracking.*|\/?auto_annotation.*|\/?analytics.*|\/?static.*|\/?admin.*|\/?documentation.*|\/?dextr.*|\/?reid.*|\/?django-rq.*
+        - queryParams:
+            id:
+              regex: \d+.*
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  volumeClaimTemplates:
+    - metadata:
+        name: db
+      spec:
+        accessModes: [ "ReadWriteOnce" ]
+        resources:
+          requests:
+            storage: 20Gi

db/yaml/workspaces/jupyterlab/20200525160514.yaml

@@ -0,0 +1,64 @@
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20200525160514
+  action: create
+  description: "Interactive development environment for notebooks"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: jupyterlab-tensorflow
+      image: jupyter/tensorflow-notebook
+      command: [start.sh, jupyter]
+      env:
+        - name: tornado
+          value: "{ 'headers': { 'Content-Security-Policy': \"frame-ancestors * 'self'\" }  }"
+      args:
+        - lab
+        - --LabApp.token=''
+        - --LabApp.allow_remote_access=True
+        - --LabApp.allow_origin="*"
+        - --LabApp.disable_check_xsrf=True
+        - --LabApp.trust_xheaders=True
+        - --LabApp.tornado_settings=$(tornado)
+        - --notebook-dir='/data'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+      # Volumes to be mounted in this container
+      # Onepanel will automatically create these volumes and mount them to the container
+      volumeMounts:
+        - name: data
+          mountPath: /data
+  # Ports that need to be exposed
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+  # Routes that will map to ports
+  routes:
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes
+  # postExecutionWorkflow:
+  #   entrypoint: main
+  #   templates:
+  #   - name: main
+  #     dag:
+  #        tasks:
+  #        - name: slack-notify
+  #          template: slack-notify
+  #   - name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/jupyterlab/20200821162630.yaml

@@ -0,0 +1,65 @@
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20200821162630
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: jupyterlab-tensorflow
+      image: onepanel/jupyterlab:1.0.1
+      command: ["/bin/bash", "-c", "start.sh jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
+      args:
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+      volumeMounts:
+        - name: data
+          mountPath: /data
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+  routes:
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: / #jupyter runs at the default route
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #    container:
+  #      image: technosophos/slack-notify
+  #      args:
+  #      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #      command:
+  #      - sh
+  #      - -c

db/yaml/workspaces/jupyterlab/20200929153931.yaml

@@ -1,58 +1,65 @@
-# Docker containers that are part of the Workspace
-containers:
-  - name: jupyterlab-tensorflow
-    image: onepanel/jupyterlab:1.0.1
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
-    args:
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-    volumeMounts:
-      - name: data
-        mountPath: /data
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-routes:
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: / #jupyter runs at the default route
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#    container:
-#      image: technosophos/slack-notify
-#      args:
-#      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#      command:
-#      - sh
-#      - -c
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20200929153931
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: jupyterlab-tensorflow
+      image: onepanel/jupyterlab:1.0.1
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
+      args:
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+      volumeMounts:
+        - name: data
+          mountPath: /data
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+  routes:
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: / #jupyter runs at the default route
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #    container:
+  #      image: technosophos/slack-notify
+  #      args:
+  #      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #      command:
+  #      - sh
+  #      - -c

db/yaml/workspaces/jupyterlab/20201028145442.yaml

@@ -1,77 +1,84 @@
-# Docker containers that are part of the Workspace
-containers:
-  - name: jupyterlab
-    image: onepanel/jupyterlab:1.0.1
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-routes:
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: / #jupyter runs at the default route
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#    container:
-#      image: technosophos/slack-notify
-#      args:
-#      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#      command:
-#      - sh
-#      - -c
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20201028145442
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: jupyterlab
+      image: onepanel/jupyterlab:1.0.1
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+  routes:
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: / #jupyter runs at the default route
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #    container:
+  #      image: technosophos/slack-notify
+  #      args:
+  #      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #      command:
+  #      - sh
+  #      - -c

db/yaml/workspaces/jupyterlab/20201031165106.yaml

@@ -1,79 +1,86 @@
-# Docker containers that are part of the Workspace
-containers:
-  - name: jupyterlab
-    image: onepanel/jupyterlab:1.0.1
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
-      - name: TENSORBOARD_PROXY_URL
-        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-routes:
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: / #jupyter runs at the default route
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#    container:
-#      image: technosophos/slack-notify
-#      args:
-#      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#      command:
-#      - sh
-#      - -c
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20201031165106
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: jupyterlab
+      image: onepanel/jupyterlab:1.0.1
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
+        - name: TENSORBOARD_PROXY_URL
+          value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+  routes:
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: / #jupyter runs at the default route
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #    container:
+  #      image: technosophos/slack-notify
+  #      args:
+  #      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #      command:
+  #      - sh
+  #      - -c

db/yaml/workspaces/jupyterlab/20201214133458.yaml

@@ -1,80 +1,87 @@
-# Docker containers that are part of the Workspace
-containers:
-  - name: jupyterlab
-    image: onepanel/jupyterlab:1.0.1
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
-    workingDir: /data
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
-      - name: TENSORBOARD_PROXY_URL
-        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-routes:
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: / #jupyter runs at the default route
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#    container:
-#      image: technosophos/slack-notify
-#      args:
-#      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#      command:
-#      - sh
-#      - -c
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20201214133458
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: jupyterlab
+      image: onepanel/jupyterlab:1.0.1
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * \'self\'\"}}' --notebook-dir='/data' --allow-root"]
+      workingDir: /data
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
+        - name: TENSORBOARD_PROXY_URL
+          value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+  routes:
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: / #jupyter runs at the default route
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #    container:
+  #      image: technosophos/slack-notify
+  #      args:
+  #      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #      command:
+  #      - sh
+  #      - -c

db/yaml/workspaces/jupyterlab/20201229205644.yaml

@@ -1,93 +1,100 @@
-# Docker containers that are part of the Workspace
-containers:
-  - name: jupyterlab
-    image: onepanel/dl:0.17.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
-    workingDir: /data
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
-      - name: TENSORBOARD_PROXY_URL
-        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-      - containerPort: 8080
-        name: nni
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-  - name: nni
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-routes:
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: /nni
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: / #jupyter runs at the default route
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  - name: slack-notify
-#    container:
-#      image: technosophos/slack-notify
-#      args:
-#      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#      command:
-#      - sh
-#      - -c
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20201229205644
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: jupyterlab
+      image: onepanel/dl:0.17.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
+      workingDir: /data
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
+        - name: TENSORBOARD_PROXY_URL
+          value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+        - containerPort: 8080
+          name: nni
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+    - name: nni
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: /nni
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: / #jupyter runs at the default route
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  - name: slack-notify
+  #    container:
+  #      image: technosophos/slack-notify
+  #      args:
+  #      - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #      command:
+  #      - sh
+  #      - -c

db/yaml/workspaces/jupyterlab/20210129142057.yaml

@@ -1,101 +1,108 @@
-containers:
-  - name: jupyterlab
-    image: onepanel/dl:0.17.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
-    workingDir: /data
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
-      - name: TENSORBOARD_PROXY_URL
-        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-      - containerPort: 8080
-        name: nni
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.18.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -host=localhost:8889
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-  - name: nni
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8889
-    protocol: TCP
-    targetPort: 8889
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8889
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: /nni
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20210129142057
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  containers:
+    - name: jupyterlab
+      image: onepanel/dl:0.17.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
+      workingDir: /data
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
+        - name: TENSORBOARD_PROXY_URL
+          value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+        - containerPort: 8080
+          name: nni
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.18.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -host=localhost:8889
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+    - name: nni
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8889
+      protocol: TCP
+      targetPort: 8889
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8889
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: /nni
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80

db/yaml/workspaces/jupyterlab/20210224180017.yaml

@@ -1,101 +1,108 @@
-containers:
-  - name: jupyterlab
-    image: onepanel/dl:0.17.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
-    workingDir: /data
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
-      - name: TENSORBOARD_PROXY_URL
-        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-      - containerPort: 8080
-        name: nni
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.19.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -host=localhost:8889
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-  - name: nni
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8889
-    protocol: TCP
-    targetPort: 8889
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8889
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: /nni
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20210224180017
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  containers:
+    - name: jupyterlab
+      image: onepanel/dl:0.17.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
+      workingDir: /data
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
+        - name: TENSORBOARD_PROXY_URL
+          value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+        - containerPort: 8080
+          name: nni
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.19.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -host=localhost:8889
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+    - name: nni
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8889
+      protocol: TCP
+      targetPort: 8889
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8889
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: /nni
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80

db/yaml/workspaces/jupyterlab/20210323175655.yaml

@@ -1,101 +1,108 @@
-containers:
-  - name: jupyterlab
-    image: onepanel/dl:v0.20.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
-    workingDir: /data
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
-      - name: TENSORBOARD_PROXY_URL
-        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-      - containerPort: 8080
-        name: nni
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.20.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -host=localhost:8889
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-  - name: nni
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8889
-    protocol: TCP
-    targetPort: 8889
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8889
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: /nni
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20210323175655
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  containers:
+    - name: jupyterlab
+      image: onepanel/dl:v0.20.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
+      workingDir: /data
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
+        - name: TENSORBOARD_PROXY_URL
+          value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+        - containerPort: 8080
+          name: nni
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.20.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -host=localhost:8889
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+    - name: nni
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8889
+      protocol: TCP
+      targetPort: 8889
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8889
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: /nni
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80

db/yaml/workspaces/jupyterlab/20210719190719.yaml

@@ -1,101 +1,108 @@
-containers:
-  - name: jupyterlab
-    image: onepanel/dl:v0.20.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
-    workingDir: /data
-    env:
-      - name: tornado
-        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
-      - name: TENSORBOARD_PROXY_URL
-        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8888
-        name: jupyterlab
-      - containerPort: 6006
-        name: tensorboard
-      - containerPort: 8080
-        name: nni
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              jupytertxt="/data/.jupexported.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
-              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v1.0.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -host=localhost:8889
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: jupyterlab
-    port: 80
-    protocol: TCP
-    targetPort: 8888
-  - name: tensorboard
-    port: 6006
-    protocol: TCP
-    targetPort: 6006
-  - name: nni
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8889
-    protocol: TCP
-    targetPort: 8889
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8889
-  - match:
-      - uri:
-          prefix: /tensorboard
-    route:
-      - destination:
-          port:
-            number: 6006
-  - match:
-      - uri:
-          prefix: /nni
-    route:
-      - destination:
-          port:
-            number: 8080
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
+metadata:
+  name: JupyterLab
+  kind: Workspace
+  version: 20210719190719
+  action: update
+  description: "Interactive development environment for notebooks"
+spec:
+  containers:
+    - name: jupyterlab
+      image: onepanel/dl:v0.20.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
+      workingDir: /data
+      env:
+        - name: tornado
+          value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
+        - name: TENSORBOARD_PROXY_URL
+          value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8888
+          name: jupyterlab
+        - containerPort: 6006
+          name: tensorboard
+        - containerPort: 8080
+          name: nni
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                jupytertxt="/data/.jupexported.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+                cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v1.0.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -host=localhost:8889
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: jupyterlab
+      port: 80
+      protocol: TCP
+      targetPort: 8888
+    - name: tensorboard
+      port: 6006
+      protocol: TCP
+      targetPort: 6006
+    - name: nni
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8889
+      protocol: TCP
+      targetPort: 8889
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8889
+    - match:
+        - uri:
+            prefix: /tensorboard
+      route:
+        - destination:
+            port:
+              number: 6006
+    - match:
+        - uri:
+            prefix: /nni
+      route:
+        - destination:
+            port:
+              number: 8080
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80

db/yaml/workspaces/vnc/20210414165510.yaml

@@ -1,57 +1,64 @@
-arguments:
-  parameters:
-    # parameter screen-resolution allows users to select screen resolution
-    - name: screen-resolution
-      value: 1680x1050
-      type: select.select
-      displayName: Screen Resolution
-      options:
-        - name: 1280x1024
-          value: 1280x1024
-        - name: 1680x1050
-          value: 1680x1050
-        - name: 2880x1800
-          value: 2880x1800
-containers:
-  - name: ubuntu
-    image: onepanel/vnc:dl-vnc
-    env:
-      - name: VNC_PASSWORDLESS
-        value: true
-      - name: VNC_RESOLUTION
-        value: '{{workflow.parameters.screen-resolution}}'
-    ports:
-      - containerPort: 6901
-        name: vnc
-    volumeMounts:
-      - name: data
-        mountPath: /data
-ports:
-  - name: vnc
-    port: 80
-    protocol: TCP
-    targetPort: 6901
-routes:
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  -  name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
+metadata:
+  name: "Deep Learning Desktop"
+  kind: Workspace
+  version: 20210414165510
+  action: create
+  description: "Deep learning desktop with VNC"
+spec:
+  arguments:
+    parameters:
+      # parameter screen-resolution allows users to select screen resolution
+      - name: screen-resolution
+        value: 1680x1050
+        type: select.select
+        displayName: Screen Resolution
+        options:
+          - name: 1280x1024
+            value: 1280x1024
+          - name: 1680x1050
+            value: 1680x1050
+          - name: 2880x1800
+            value: 2880x1800
+  containers:
+    - name: ubuntu
+      image: onepanel/vnc:dl-vnc
+      env:
+        - name: VNC_PASSWORDLESS
+          value: true
+        - name: VNC_RESOLUTION
+          value: '{{workflow.parameters.screen-resolution}}'
+      ports:
+        - containerPort: 6901
+          name: vnc
+      volumeMounts:
+        - name: data
+          mountPath: /data
+  ports:
+    - name: vnc
+      port: 80
+      protocol: TCP
+      targetPort: 6901
+  routes:
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  -  name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh

db/yaml/workspaces/vnc/20210719190719.yaml

@@ -1,81 +1,88 @@
-arguments:
-  parameters:
-    # parameter screen-resolution allows users to select screen resolution
-    - name: screen-resolution
-      value: 1680x1050
-      type: select.select
-      displayName: Screen Resolution
-      options:
-        - name: 1280x1024
-          value: 1280x1024
-        - name: 1680x1050
-          value: 1680x1050
-        - name: 2880x1800
-          value: 2880x1800
-containers:
-  - name: ubuntu
-    image: onepanel/vnc:dl-vnc
-    env:
-      - name: VNC_PASSWORDLESS
-        value: true
-      - name: VNC_RESOLUTION
-        value: '{{workflow.parameters.screen-resolution}}'
-    ports:
-      - containerPort: 6901
-        name: vnc
-    volumeMounts:
-      - name: data
-        mountPath: /data
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v1.0.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -host=localhost:8889
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: vnc
-    port: 80
-    protocol: TCP
-    targetPort: 6901
-  - name: fs
-    port: 8889
-    protocol: TCP
-    targetPort: 8889
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8889
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 80
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  -  name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
+metadata:
+  name: "Deep Learning Desktop"
+  kind: Workspace
+  version: 20210719190719
+  action: update
+  description: "Deep learning desktop with VNC"
+spec:
+  arguments:
+    parameters:
+      # parameter screen-resolution allows users to select screen resolution
+      - name: screen-resolution
+        value: 1680x1050
+        type: select.select
+        displayName: Screen Resolution
+        options:
+          - name: 1280x1024
+            value: 1280x1024
+          - name: 1680x1050
+            value: 1680x1050
+          - name: 2880x1800
+            value: 2880x1800
+  containers:
+    - name: ubuntu
+      image: onepanel/vnc:dl-vnc
+      env:
+        - name: VNC_PASSWORDLESS
+          value: true
+        - name: VNC_RESOLUTION
+          value: '{{workflow.parameters.screen-resolution}}'
+      ports:
+        - containerPort: 6901
+          name: vnc
+      volumeMounts:
+        - name: data
+          mountPath: /data
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v1.0.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -host=localhost:8889
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: vnc
+      port: 80
+      protocol: TCP
+      targetPort: 6901
+    - name: fs
+      port: 8889
+      protocol: TCP
+      targetPort: 8889
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8889
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 80
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  -  name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh

db/yaml/workspaces/vscode/20200929144301.yaml

@@ -1,41 +1,48 @@
-# Docker containers that are part of the Workspace
-containers:
-  - name: vscode
-    image: onepanel/vscode:1.0.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
-    ports:
-      - containerPort: 8080
-        name: vscode
-    volumeMounts:
-      - name: data
-        mountPath: /data
-ports:
-  - name: vscode
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-routes:
-  - match:
-      - uri:
-          prefix: / #vscode runs at the default route
-    route:
-      - destination:
-          port:
-            number: 8080
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  -  name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: "Visual Studio Code"
+  kind: Workspace
+  version: 20200929144301
+  action: create
+  description: "Open source code editor"
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: vscode
+      image: onepanel/vscode:1.0.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
+      ports:
+        - containerPort: 8080
+          name: vscode
+      volumeMounts:
+        - name: data
+          mountPath: /data
+  ports:
+    - name: vscode
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            prefix: / #vscode runs at the default route
+      route:
+        - destination:
+            port:
+              number: 8080
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  -  name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/vscode/20201028145443.yaml

@@ -1,60 +1,66 @@
-# Docker containers that are part of the Workspace
-containers:
-  - name: vscode
-    image: onepanel/vscode:1.0.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
-    ports:
-      - containerPort: 8080
-        name: vscode
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              vscodetxt="/data/.vscode-extensions.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
-ports:
-  - name: vscode
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-routes:
-  - match:
-      - uri:
-          prefix: / #vscode runs at the default route
-    route:
-      - destination:
-          port:
-            number: 8080
-# DAG Workflow to be executed once a Workspace action completes (optional)
-#postExecutionWorkflow:
-#  entrypoint: main
-#  templates:
-#  - name: main
-#    dag:
-#       tasks:
-#       - name: slack-notify
-#         template: slack-notify
-#  -  name: slack-notify
-#     container:
-#       image: technosophos/slack-notify
-#       args:
-#       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
-#       command:
-#       - sh
-#       - -c
+metadata:
+  name: "Visual Studio Code"
+  kind: Workspace
+  version: 20201028145443
+  action: update
+spec:
+  # Docker containers that are part of the Workspace
+  containers:
+    - name: vscode
+      image: onepanel/vscode:1.0.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
+      ports:
+        - containerPort: 8080
+          name: vscode
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                vscodetxt="/data/.vscode-extensions.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
+  ports:
+    - name: vscode
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+  routes:
+    - match:
+        - uri:
+            prefix: / #vscode runs at the default route
+      route:
+        - destination:
+            port:
+              number: 8080
+  # DAG Workflow to be executed once a Workspace action completes (optional)
+  #postExecutionWorkflow:
+  #  entrypoint: main
+  #  templates:
+  #  - name: main
+  #    dag:
+  #       tasks:
+  #       - name: slack-notify
+  #         template: slack-notify
+  #  -  name: slack-notify
+  #     container:
+  #       image: technosophos/slack-notify
+  #       args:
+  #       - SLACK_USERNAME=onepanel SLACK_TITLE="Your workspace is ready" SLACK_ICON=https://www.gravatar.com/avatar/5c4478592fe00878f62f0027be59c1bd SLACK_MESSAGE="Your workspace is now running" ./slack-notify
+  #       command:
+  #       - sh
+  #       - -c

db/yaml/workspaces/vscode/20210129152427.yaml

@@ -1,68 +1,74 @@
-containers:
-  - name: vscode
-    image: onepanel/vscode:1.0.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
-    env:
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: vscode
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              vscodetxt="/data/.vscode-extensions.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.18.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: vscode
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 8080
+metadata:
+  name: "Visual Studio Code"
+  kind: Workspace
+  version: 20210129152427
+  action: update
+spec:
+  containers:
+    - name: vscode
+      image: onepanel/vscode:1.0.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
+      env:
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: vscode
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                vscodetxt="/data/.vscode-extensions.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.18.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: vscode
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 8080

db/yaml/workspaces/vscode/20210224180017.yaml

@@ -1,68 +1,74 @@
-containers:
-  - name: vscode
-    image: onepanel/vscode:1.0.0
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
-    env:
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: vscode
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              vscodetxt="/data/.vscode-extensions.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.19.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: vscode
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 8080
+metadata:
+  name: "Visual Studio Code"
+  kind: Workspace
+  version: 20210224180017
+  action: update
+spec:
+  containers:
+    - name: vscode
+      image: onepanel/vscode:1.0.0
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
+      env:
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: vscode
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                vscodetxt="/data/.vscode-extensions.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.19.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: vscode
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 8080

db/yaml/workspaces/vscode/20210323175655.yaml

@@ -1,68 +1,74 @@
-containers:
-  - name: vscode
-    image: onepanel/vscode:v0.20.0_code-server.3.9.1
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
-    env:
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: vscode
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              vscodetxt="/data/.vscode-extensions.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v0.20.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: vscode
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 8080
+metadata:
+  name: "Visual Studio Code"
+  kind: Workspace
+  version: 20210323175655
+  action: update
+spec:
+  containers:
+    - name: vscode
+      image: onepanel/vscode:v0.20.0_code-server.3.9.1
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
+      env:
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: vscode
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                vscodetxt="/data/.vscode-extensions.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v0.20.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: vscode
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 8080

db/yaml/workspaces/vscode/20210719190719.yaml

@@ -1,68 +1,74 @@
-containers:
-  - name: vscode
-    image: onepanel/vscode:v0.20.0_code-server.3.9.1
-    command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
-    env:
-      - name: ONEPANEL_MAIN_CONTAINER
-        value: 'true'
-    ports:
-      - containerPort: 8080
-        name: vscode
-    volumeMounts:
-      - name: data
-        mountPath: /data
-    lifecycle:
-      postStart:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              condayml="/data/.environment.yml";
-              vscodetxt="/data/.vscode-extensions.txt";
-              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
-              if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
-      preStop:
-        exec:
-          command:
-            - /bin/sh
-            - -c
-            - >
-              conda env export > /data/.environment.yml -n base;
-              code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
-  - name: sys-filesyncer
-    image: onepanel/filesyncer:v1.0.0
-    imagePullPolicy: Always
-    args:
-      - server
-      - -server-prefix=/sys/filesyncer
-    volumeMounts:
-      - name: data
-        mountPath: /data
-      - name: sys-namespace-config
-        mountPath: /etc/onepanel
-        readOnly: true
-ports:
-  - name: vscode
-    port: 8080
-    protocol: TCP
-    targetPort: 8080
-  - name: fs
-    port: 8888
-    protocol: TCP
-    targetPort: 8888
-routes:
-  - match:
-      - uri:
-          prefix: /sys/filesyncer
-    route:
-      - destination:
-          port:
-            number: 8888
-  - match:
-      - uri:
-          prefix: /
-    route:
-      - destination:
-          port:
-            number: 8080
+metadata:
+  name: "Visual Studio Code"
+  kind: Workspace
+  version: 20210719190719
+  action: update
+spec:
+  containers:
+    - name: vscode
+      image: onepanel/vscode:v0.20.0_code-server.3.9.1
+      command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
+      env:
+        - name: ONEPANEL_MAIN_CONTAINER
+          value: 'true'
+      ports:
+        - containerPort: 8080
+          name: vscode
+      volumeMounts:
+        - name: data
+          mountPath: /data
+      lifecycle:
+        postStart:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                condayml="/data/.environment.yml";
+                vscodetxt="/data/.vscode-extensions.txt";
+                if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+                if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
+        preStop:
+          exec:
+            command:
+              - /bin/sh
+              - -c
+              - >
+                conda env export > /data/.environment.yml -n base;
+                code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
+    - name: sys-filesyncer
+      image: onepanel/filesyncer:v1.0.0
+      imagePullPolicy: Always
+      args:
+        - server
+        - -server-prefix=/sys/filesyncer
+      volumeMounts:
+        - name: data
+          mountPath: /data
+        - name: sys-namespace-config
+          mountPath: /etc/onepanel
+          readOnly: true
+  ports:
+    - name: vscode
+      port: 8080
+      protocol: TCP
+      targetPort: 8080
+    - name: fs
+      port: 8888
+      protocol: TCP
+      targetPort: 8888
+  routes:
+    - match:
+        - uri:
+            prefix: /sys/filesyncer
+      route:
+        - destination:
+            port:
+              number: 8888
+    - match:
+        - uri:
+            prefix: /
+      route:
+        - destination:
+            port:
+              number: 8080

go.mod

@@ -4,7 +4,6 @@ go 1.15
 
 require (
 	cloud.google.com/go/storage v1.10.0
-	github.com/Azure/go-autorest v14.0.0+incompatible // indirect
 	github.com/Azure/go-autorest/autorest/adal v0.8.2 // indirect
 	github.com/Masterminds/squirrel v1.1.0
 	github.com/argoproj/argo v0.0.0-20210112203504-f97bef5d0036
@@ -12,12 +11,10 @@ require (
 	github.com/asaskevich/govalidator v0.0.0-20200428143746-21a406dcc535
 	github.com/elazarl/goproxy v0.0.0-20191011121108-aa519ddbe484 // indirect
 	github.com/ghodss/yaml v1.0.0
-	github.com/go-sql-driver/mysql v1.5.0 // indirect
 	github.com/golang/protobuf v1.4.3
 	github.com/google/uuid v1.1.2
 	github.com/gorilla/handlers v1.4.2
 	github.com/grpc-ecosystem/go-grpc-middleware v1.2.0
-	github.com/grpc-ecosystem/grpc-gateway v1.14.6
 	github.com/grpc-ecosystem/grpc-gateway/v2 v2.0.1
 	github.com/hashicorp/go-uuid v1.0.2 // indirect
 	github.com/hashicorp/golang-lru v0.5.4 // indirect
@@ -30,7 +27,7 @@ require (
 	github.com/sirupsen/logrus v1.6.0
 	github.com/stretchr/testify v1.6.1
 	github.com/tmc/grpc-websocket-proxy v0.0.0-20200122045848-3419fae592fc
-	golang.org/x/net v0.0.0-20201110031124-69a78807bb2b
+	golang.org/x/net v0.7.0
 	golang.org/x/oauth2 v0.0.0-20200902213428-5d25da1a8d43
 	google.golang.org/api v0.30.0
 	google.golang.org/genproto v0.0.0-20201019141844-1ed22bb0c154
@@ -42,7 +39,6 @@ require (
 	k8s.io/api v0.18.2
 	k8s.io/apimachinery v0.18.2
 	k8s.io/client-go v0.18.2
-	sigs.k8s.io/structured-merge-diff v0.0.0-20190525122527-15d366b2352e // indirect
 	sigs.k8s.io/yaml v1.2.0
 )
 

go.sum

@@ -7,7 +7,6 @@ cloud.google.com/go v0.44.2/go.mod h1:60680Gw3Yr4ikxnPRS/oxxkBccT6SA1yMk63TGekxK
 cloud.google.com/go v0.45.1/go.mod h1:RpBamKRgapWJb87xiFSdk4g1CME7QZg3uwTez+TSTjc=
 cloud.google.com/go v0.46.3/go.mod h1:a6bKKbmY7er1mI7TEI4lsAkts/mkhTSZK8w33B4RAg0=
 cloud.google.com/go v0.50.0/go.mod h1:r9sluTvynVuxRIOHXQEHMFffphuXHOMZMycpNR5e6To=
-cloud.google.com/go v0.51.0/go.mod h1:hWtGJ6gnXH+KgDv+V0zFGDvpi07n3z8ZNj3T1RW0Gcw=
 cloud.google.com/go v0.52.0/go.mod h1:pXajvRH/6o3+F9jDHZWQ5PbGhn+o8w9qiu/CffaVdO4=
 cloud.google.com/go v0.53.0/go.mod h1:fp/UouUEsRkN6ryDKNW/Upv/JBKnv6WDthjR6+vze6M=
 cloud.google.com/go v0.54.0/go.mod h1:1rq2OEkV3YMf6n/9ZvGWI3GWw0VoqH/1x2nd8Is/bPc=
@@ -37,12 +36,8 @@ cloud.google.com/go/storage v1.10.0 h1:STgFzyU5/8miMl0//zKh2aQeTyeaUH3WN9bSUiJ09
 cloud.google.com/go/storage v1.10.0/go.mod h1:FLPqc6j+Ki4BU591ie1oL6qBQGu2Bl/tZ9ullr3+Kg0=
 dmitri.shuralyov.com/gpu/mtl v0.0.0-20190408044501-666a987793e9/go.mod h1:H6x//7gZCb22OMCxBHrMx7a5I7Hp++hsVxbQ4BYO7hU=
 github.com/Azure/go-ansiterm v0.0.0-20170929234023-d6e3b3328b78/go.mod h1:LmzpDX56iTiv29bbRTIsUNlaFfuhWRQBWjQdVyAevI8=
-github.com/Azure/go-autorest v14.0.0+incompatible h1:r/ug62X9o8vikt53/nkAPmFmzfSrCCAplPH7wa+mK0U=
-github.com/Azure/go-autorest v14.0.0+incompatible/go.mod h1:r+4oMnoxhatjLLJ6zxSWATqVooLgysK6ZNox3g/xq24=
 github.com/Azure/go-autorest/autorest v0.9.0 h1:MRvx8gncNaXJqOoLmhNjUAKh33JJF8LyxPhomEtOsjs=
 github.com/Azure/go-autorest/autorest v0.9.0/go.mod h1:xyHB1BMZT0cuDHU7I0+g046+BFDTQ8rEZB0s4Yfa6bI=
-github.com/Azure/go-autorest/autorest v0.9.6 h1:5YWtOnckcudzIw8lPPBcWOnmIFWMtHci1ZWAZulMSx0=
-github.com/Azure/go-autorest/autorest v0.9.6/go.mod h1:/FALq9T/kS7b5J5qsQ+RSTUdAmGFqi0vUdVNNx8q630=
 github.com/Azure/go-autorest/autorest/adal v0.5.0/go.mod h1:8Z9fGy2MpX0PvDjB1pEgQTmVqjGhiHBW7RJJEciWzS0=
 github.com/Azure/go-autorest/autorest/adal v0.8.2 h1:O1X4oexUxnZCaEUGsvMnr8ZGj8HI37tNezwY4npRqA0=
 github.com/Azure/go-autorest/autorest/adal v0.8.2/go.mod h1:ZjhuQClTqx435SRJ2iMlOxPYt3d2C/T/7TiQCVZSn3Q=
@@ -148,11 +143,9 @@ github.com/docker/go-units v0.4.0/go.mod h1:fgPhTUdO+D/Jk86RDLlptpiXQzgHJF7gydDD
 github.com/docker/spdystream v0.0.0-20160310174837-449fdfce4d96/go.mod h1:Qh8CwZgvJUkLughtfhJv5dyTYa91l1fOUCrgjqmcifM=
 github.com/docker/spdystream v0.0.0-20181023171402-6480d4af844c h1:ZfSZ3P3BedhKGUhzj7BQlPSU4OvT6tfOKe3DVHzOA7s=
 github.com/docker/spdystream v0.0.0-20181023171402-6480d4af844c/go.mod h1:Qh8CwZgvJUkLughtfhJv5dyTYa91l1fOUCrgjqmcifM=
-github.com/docopt/docopt-go v0.0.0-20180111231733-ee0de3bc6815/go.mod h1:WwZ+bS3ebgob9U8Nd0kOddGdZWjyMGR8Wziv+TBNwSE=
 github.com/dustin/go-humanize v0.0.0-20171111073723-bb3d318650d4/go.mod h1:HtrtbFcZ19U5GC7JDqmcUSB87Iq5E25KnS6fMYU6eOk=
 github.com/dustin/go-humanize v1.0.0/go.mod h1:HtrtbFcZ19U5GC7JDqmcUSB87Iq5E25KnS6fMYU6eOk=
 github.com/elazarl/goproxy v0.0.0-20170405201442-c4fc26588b6e/go.mod h1:/Zj4wYkgs4iZTTu3o/KG3Itv/qCCa8VVMlb3i9OVuzc=
-github.com/elazarl/goproxy v0.0.0-20180725130230-947c36da3153/go.mod h1:/Zj4wYkgs4iZTTu3o/KG3Itv/qCCa8VVMlb3i9OVuzc=
 github.com/elazarl/goproxy v0.0.0-20191011121108-aa519ddbe484 h1:pEtiCjIXx3RvGjlUJuCNxNOw0MNblyR9Wi+vJGBFh+8=
 github.com/elazarl/goproxy v0.0.0-20191011121108-aa519ddbe484/go.mod h1:Ro8st/ElPeALwNFlcTpWmkr6IoMFfkjXAvTHpevnDsM=
 github.com/elazarl/goproxy/ext v0.0.0-20190711103511-473e67f1d7d2 h1:dWB6v3RcOy03t/bUadywsbyrQwCqZeNIEX6M1OtSZOM=
@@ -168,13 +161,13 @@ github.com/envoyproxy/protoc-gen-validate v0.1.0/go.mod h1:iSmxcyjqTsJpI2R4NaDN7
 github.com/evanphx/json-patch v4.2.0+incompatible/go.mod h1:50XU6AFN0ol/bzJsmQLiYLvXMP4fmwYFNcr97nuDLSk=
 github.com/evanphx/json-patch v4.5.0+incompatible h1:ouOWdg56aJriqS0huScTkVXPC5IcNrDCXZ6OoTAWu7M=
 github.com/evanphx/json-patch v4.5.0+incompatible/go.mod h1:50XU6AFN0ol/bzJsmQLiYLvXMP4fmwYFNcr97nuDLSk=
-github.com/evanphx/json-patch v4.9.0+incompatible/go.mod h1:50XU6AFN0ol/bzJsmQLiYLvXMP4fmwYFNcr97nuDLSk=
 github.com/fasthttp-contrib/websocket v0.0.0-20160511215533-1f3b11f56072/go.mod h1:duJ4Jxv5lDcvg4QuQr0oowTf7dz4/CR8NtyCooz9HL8=
 github.com/fatih/color v1.7.0/go.mod h1:Zm6kSWBoL9eyXnKyktHP6abPY2pDugNf5KwzbycvMj4=
 github.com/fatih/structs v1.0.0/go.mod h1:9NiDSp5zOcgEDl+j00MP/WkGVPOlPRLejGD8Ga6PJ7M=
 github.com/fatih/structs v1.1.0/go.mod h1:9NiDSp5zOcgEDl+j00MP/WkGVPOlPRLejGD8Ga6PJ7M=
 github.com/flynn/go-shlex v0.0.0-20150515145356-3f9db97f8568/go.mod h1:xEzjJPgXI435gkrCt3MPfRiAkVrwSbHsst4LCFVfpJc=
 github.com/fsnotify/fsnotify v1.4.7/go.mod h1:jwhsz4b93w/PPRr/qN1Yymfu8t87LnFCMoQvtojpjFo=
+github.com/fsnotify/fsnotify v1.4.9 h1:hsms1Qyu0jgnwNXIxa+/V/PDsU6CfLf6CNO8H7IWoS4=
 github.com/fsnotify/fsnotify v1.4.9/go.mod h1:znqG4EE+3YCdAaPaxE2ZRY/06pZUdp0tY4IgpuI1SZQ=
 github.com/gavv/httpexpect/v2 v2.0.3/go.mod h1:LAoDcy8I/EXEtKJV6wMEJvOMAZVo0MfEk5u4NfiNQa4=
 github.com/gdamore/encoding v1.0.0/go.mod h1:alR0ol34c49FCSBLjhosxzcPHQbf2trDkoo5dl+VrEg=
@@ -194,8 +187,6 @@ github.com/go-kit/kit v0.9.0/go.mod h1:xBxKIO96dXMWWy0MnWVtmwkA9/13aqxPnvrjFYMA2
 github.com/go-logfmt/logfmt v0.3.0/go.mod h1:Qt1PoO58o5twSAckw1HlFXLmHsOX5/0LbT9GBnD5lWE=
 github.com/go-logfmt/logfmt v0.4.0/go.mod h1:3RMwSq7FuexP4Kalkev3ejPJsZTpXXBr9+V4qmtdjCk=
 github.com/go-logr/logr v0.1.0/go.mod h1:ixOQHD9gLJUVQQ2ZOR7zLEifBX6tGkNJF4QyIY7sIas=
-github.com/go-logr/logr v0.2.0 h1:QvGt2nLcHH0WK9orKa+ppBPAxREcH364nPUedEpK0TY=
-github.com/go-logr/logr v0.2.0/go.mod h1:z6/tIYblkpsD+a4lm/fGIIU9mZ+XfAiaFtq7xTgseGU=
 github.com/go-openapi/analysis v0.0.0-20180825180245-b006789cd277/go.mod h1:k70tL6pCuVxPJOHXQ+wIac1FUrvNkHolPie/cLEU6hI=
 github.com/go-openapi/analysis v0.17.0/go.mod h1:IowGgpVeD0vNm45So8nr+IcQ3pxVtpRoBWb8PVZO0ik=
 github.com/go-openapi/analysis v0.18.0/go.mod h1:IowGgpVeD0vNm45So8nr+IcQ3pxVtpRoBWb8PVZO0ik=
@@ -368,11 +359,10 @@ github.com/googleapis/gax-go/v2 v2.0.5/go.mod h1:DWXyrwAJ9X0FpwwEdw+IPEYBICEFu5m
 github.com/googleapis/gnostic v0.0.0-20170729233727-0c5108395e2d/go.mod h1:sJBsCZ4ayReDTBIg8b9dl28c5xFWyhBTVRp3pOg5EKY=
 github.com/googleapis/gnostic v0.1.0 h1:rVsPeBmXbYv4If/cumu1AzZPwV58q433hvONV1UEZoI=
 github.com/googleapis/gnostic v0.1.0/go.mod h1:sJBsCZ4ayReDTBIg8b9dl28c5xFWyhBTVRp3pOg5EKY=
-github.com/googleapis/gnostic v0.4.1 h1:DLJCy1n/vrD4HPjOvYcT8aYQXpPIzoRZONaYwyycI+I=
-github.com/googleapis/gnostic v0.4.1/go.mod h1:LRhVm6pbyptWbWbuZ38d1eyptfvIytN3ir6b65WBswg=
 github.com/gophercloud/gophercloud v0.1.0/go.mod h1:vxM41WHh5uqHVBMZHzuwNOHh8XEoIEcSTewFxm1c5g8=
 github.com/gophercloud/gophercloud v0.7.0 h1:vhmQQEM2SbnGCg2/3EzQnQZ3V7+UCGy9s8exQCprNYg=
 github.com/gophercloud/gophercloud v0.7.0/go.mod h1:gmC5oQqMDOMO1t1gq5DquX/yAU808e/4mzjjDA76+Ss=
+github.com/gopherjs/gopherjs v0.0.0-20181017120253-0766667cb4d1 h1:EGx4pi6eqNxGaHF6qqu48+N2wcFQ5qg5FXgOdqsJ5d8=
 github.com/gopherjs/gopherjs v0.0.0-20181017120253-0766667cb4d1/go.mod h1:wJfORRmW1u3UXTncJ5qlYoELFm8eSnnEO6hX4iZ3EWY=
 github.com/gorilla/handlers v1.4.2 h1:0QniY0USkHQ1RGCLfKxeNHK9bkDHGRYGNDFBCS+YARg=
 github.com/gorilla/handlers v1.4.2/go.mod h1:Qkdc/uu4tH4g6mTK6auzZ766c4CA0Ng8+o/OAirnOIQ=
@@ -403,6 +393,7 @@ github.com/hashicorp/golang-lru v0.5.3/go.mod h1:iADmTwqILo4mZ8BN3D2Q6+9jd8WM5uG
 github.com/hashicorp/golang-lru v0.5.4 h1:YDjusn29QI/Das2iO9M0BHnIbxPeyuCHsjMW+lJfyTc=
 github.com/hashicorp/golang-lru v0.5.4/go.mod h1:iADmTwqILo4mZ8BN3D2Q6+9jd8WM5uGBxy+E8yxSoD4=
 github.com/hashicorp/hcl v1.0.0/go.mod h1:E5yfLk+7swimpb2L/Alb/PJmXilQ/rhwaUYs4T20WEQ=
+github.com/hpcloud/tail v1.0.0 h1:nfCOvKYfkgYP8hkirhJocXT2+zOD8yUNjXaWfTlyFKI=
 github.com/hpcloud/tail v1.0.0/go.mod h1:ab1qPbhIpdTxEkNHXyeSf5vhxWSCs/tWer42PpOxQnU=
 github.com/iancoleman/strcase v0.1.1/go.mod h1:SK73tn/9oHe+/Y0h39VT4UCxmurVJkR5NA7kMEAOgSE=
 github.com/ianlancetaylor/demangle v0.0.0-20181102032728-5e5cf60278f6/go.mod h1:aSSvb/t6k1mPoxDqO4vJh6VOCGPwU4O0C2/Eqndh1Sc=
@@ -429,6 +420,7 @@ github.com/json-iterator/go v1.1.8/go.mod h1:KdQUCv79m/52Kvf8AW2vK1V8akMuk1QjK/u
 github.com/json-iterator/go v1.1.10 h1:Kz6Cvnvv2wGdaG/V8yMvfkmNiXq9Ya2KUv4rouJJr68=
 github.com/json-iterator/go v1.1.10/go.mod h1:KdQUCv79m/52Kvf8AW2vK1V8akMuk1QjK/uOdHXbAo4=
 github.com/jstemmer/go-junit-report v0.0.0-20190106144839-af01ea7f8024/go.mod h1:6v2b51hI/fHJwM22ozAgKL4VKDeJcHhJFhtBdhmNjmU=
+github.com/jstemmer/go-junit-report v0.9.1 h1:6QPYqodiu3GuPL+7mfx+NwDdp2eTkp9IfEUpgAwUN0o=
 github.com/jstemmer/go-junit-report v0.9.1/go.mod h1:Brl9GWCQeLvo8nXZwPNNblvFj/XSXhF0NWZEnDohbsk=
 github.com/jtolds/gls v4.20.0+incompatible h1:xdiiI2gbIgH/gLH7ADydsJ1uDOEzR8yvV7C0MuV77Wo=
 github.com/jtolds/gls v4.20.0+incompatible/go.mod h1:QJZ7F/aHp+rZTRtaJ1ow/lLfFfVYBRgL+9YlvaHOwJU=
@@ -673,6 +665,7 @@ github.com/yudai/pp v2.0.1+incompatible/go.mod h1:PuxR/8QJ7cyCkFp/aUDS+JY727OFEZ
 github.com/yuin/goldmark v1.1.25/go.mod h1:3hX8gzYuyVAZsxl0MRgGTJEmQBFcNTphYh9decYSb74=
 github.com/yuin/goldmark v1.1.27/go.mod h1:3hX8gzYuyVAZsxl0MRgGTJEmQBFcNTphYh9decYSb74=
 github.com/yuin/goldmark v1.1.32/go.mod h1:3hX8gzYuyVAZsxl0MRgGTJEmQBFcNTphYh9decYSb74=
+github.com/yuin/goldmark v1.4.13/go.mod h1:6yULJ656Px+3vBD8DxQVa3kxgyrAnzto9xy5taEt/CY=
 go.etcd.io/bbolt v1.3.2/go.mod h1:IbVyRI1SCnLcuJnV2u8VeU0CEYM7e686BmAb1XKL+uU=
 go.etcd.io/bbolt v1.3.3/go.mod h1:IbVyRI1SCnLcuJnV2u8VeU0CEYM7e686BmAb1XKL+uU=
 go.etcd.io/etcd v0.0.0-20191023171146-3cf2f69b5738/go.mod h1:dnLIgRNXwCJa5e+c6mIZCrds/GIG4ncV9HhK5PX7jPg=
@@ -713,8 +706,9 @@ golang.org/x/crypto v0.0.0-20191206172530-e9b2fee46413/go.mod h1:LzIPMQfyMNhhGPh
 golang.org/x/crypto v0.0.0-20200220183623-bac4c82f6975/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
 golang.org/x/crypto v0.0.0-20200311171314-f7b00557c8c4/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
 golang.org/x/crypto v0.0.0-20200604202706-70a84ac30bf9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
-golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9 h1:psW17arqaxU48Z5kZ0CQnkZWQJsqcURM6tKiBApRjXI=
 golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
+golang.org/x/crypto v0.0.0-20210921155107-089bfa567519 h1:7I4JAnoQBe7ZtJcBaYHi5UtiO8tQHbUSXxL+pnGRANg=
+golang.org/x/crypto v0.0.0-20210921155107-089bfa567519/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
 golang.org/x/exp v0.0.0-20190121172915-509febef88a4/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
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 golang.org/x/exp v0.0.0-20190306152737-a1d7652674e8/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
@@ -739,6 +733,7 @@ golang.org/x/lint v0.0.0-20190909230951-414d861bb4ac/go.mod h1:6SW0HCj/g11FgYtHl
 golang.org/x/lint v0.0.0-20190930215403-16217165b5de/go.mod h1:6SW0HCj/g11FgYtHlgUYUwCkIfeOF89ocIRzGO/8vkc=
 golang.org/x/lint v0.0.0-20191125180803-fdd1cda4f05f/go.mod h1:5qLYkcX4OjUUV8bRuDixDT3tpyyb+LUpUlRWLxfhWrs=
 golang.org/x/lint v0.0.0-20200130185559-910be7a94367/go.mod h1:3xt1FjdF8hUf6vQPIChWIBhFzV8gjjsPE/fR3IyQdNY=
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 golang.org/x/lint v0.0.0-20200302205851-738671d3881b/go.mod h1:3xt1FjdF8hUf6vQPIChWIBhFzV8gjjsPE/fR3IyQdNY=
 golang.org/x/mobile v0.0.0-20190312151609-d3739f865fa6/go.mod h1:z+o9i4GpDbdi3rU15maQ/Ox0txvL9dWGYEHz965HBQE=
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@@ -749,6 +744,8 @@ golang.org/x/mod v0.1.1-0.20191107180719-034126e5016b/go.mod h1:QqPTAvyqsEbceGzB
 golang.org/x/mod v0.2.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
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 golang.org/x/mod v0.3.1-0.20200828183125-ce943fd02449/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
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 golang.org/x/net v0.0.0-20170114055629-f2499483f923/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
 golang.org/x/net v0.0.0-20180724234803-3673e40ba225/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
 golang.org/x/net v0.0.0-20180826012351-8a410e7b638d/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
@@ -791,8 +788,10 @@ golang.org/x/net v0.0.0-20200602114024-627f9648deb9/go.mod h1:qpuaurCH72eLCgpAm/
 golang.org/x/net v0.0.0-20200625001655-4c5254603344/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
 golang.org/x/net v0.0.0-20200707034311-ab3426394381/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
 golang.org/x/net v0.0.0-20200822124328-c89045814202/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
-golang.org/x/net v0.0.0-20201110031124-69a78807bb2b h1:uwuIcX0g4Yl1NC5XAz37xsr2lTtcqevgzYNVt49waME=
-golang.org/x/net v0.0.0-20201110031124-69a78807bb2b/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
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+golang.org/x/net v0.7.0 h1:rJrUqqhjsgNp7KqAIc25s9pZnjU7TUcSY7HcVZjdn1g=
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 golang.org/x/oauth2 v0.0.0-20180821212333-d2e6202438be/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
 golang.org/x/oauth2 v0.0.0-20190226205417-e64efc72b421/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
 golang.org/x/oauth2 v0.0.0-20190604053449-0f29369cfe45/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
@@ -809,6 +808,7 @@ golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJ
 golang.org/x/sync v0.0.0-20190911185100-cd5d95a43a6e/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
 golang.org/x/sync v0.0.0-20200317015054-43a5402ce75a/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
 golang.org/x/sync v0.0.0-20200625203802-6e8e738ad208/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
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 golang.org/x/sys v0.0.0-20170830134202-bb24a47a89ea/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
 golang.org/x/sys v0.0.0-20180830151530-49385e6e1522/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
 golang.org/x/sys v0.0.0-20180905080454-ebe1bf3edb33/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
@@ -839,7 +839,6 @@ golang.org/x/sys v0.0.0-20190826190057-c7b8b68b1456/go.mod h1:h1NjWce9XRLGQEsW7w
 golang.org/x/sys v0.0.0-20191001151750-bb3f8db39f24/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20191005200804-aed5e4c7ecf9/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20191008105621-543471e840be/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
-golang.org/x/sys v0.0.0-20191022100944-742c48ecaeb7/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20191128015809-6d18c012aee9/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20191204072324-ce4227a45e2e/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20191228213918-04cbcbbfeed8/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
@@ -857,17 +856,25 @@ golang.org/x/sys v0.0.0-20200511232937-7e40ca221e25/go.mod h1:h1NjWce9XRLGQEsW7w
 golang.org/x/sys v0.0.0-20200515095857-1151b9dac4a9/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
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 golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
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@@ -931,6 +938,8 @@ golang.org/x/tools v0.0.0-20200630154851-b2d8b0336632/go.mod h1:EkVYQZoAsY45+roY
 golang.org/x/tools v0.0.0-20200729194436-6467de6f59a7/go.mod h1:njjCfa9FT2d7l9Bc6FUM5FLjQPp3cFF28FI3qnDFljA=
 golang.org/x/tools v0.0.0-20200804011535-6c149bb5ef0d/go.mod h1:njjCfa9FT2d7l9Bc6FUM5FLjQPp3cFF28FI3qnDFljA=
 golang.org/x/tools v0.0.0-20200825202427-b303f430e36d/go.mod h1:njjCfa9FT2d7l9Bc6FUM5FLjQPp3cFF28FI3qnDFljA=
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 golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
 golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
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@@ -961,6 +970,7 @@ google.golang.org/appengine v1.4.0/go.mod h1:xpcJRLb0r/rnEns0DIKYYv+WjYCduHsrkT7
 google.golang.org/appengine v1.5.0/go.mod h1:xpcJRLb0r/rnEns0DIKYYv+WjYCduHsrkT7/EB5XEv4=
 google.golang.org/appengine v1.6.1/go.mod h1:i06prIuMbXzDqacNJfV5OdTW448YApPu5ww/cMBSeb0=
 google.golang.org/appengine v1.6.5/go.mod h1:8WjMMxjGQR8xUklV/ARdw2HLXBOI7O7uCIDZVag1xfc=
+google.golang.org/appengine v1.6.6 h1:lMO5rYAqUxkmaj76jAkRUvt5JZgFymx/+Q5Mzfivuhc=
 google.golang.org/appengine v1.6.6/go.mod h1:8WjMMxjGQR8xUklV/ARdw2HLXBOI7O7uCIDZVag1xfc=
 google.golang.org/genproto v0.0.0-20180817151627-c66870c02cf8/go.mod h1:JiN7NxoALGmiZfu7CAH4rXhgtRTLTxftemlI0sWmxmc=
 google.golang.org/genproto v0.0.0-20190307195333-5fe7a883aa19/go.mod h1:VzzqZJRnGkLBvHegQrXjBqPurQTc5/KpmUdxsrq26oE=
@@ -1030,6 +1040,7 @@ gopkg.in/check.v1 v1.0.0-20190902080502-41f04d3bba15 h1:YR8cESwS4TdDjEe65xsg0ogR
 gopkg.in/check.v1 v1.0.0-20190902080502-41f04d3bba15/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
 gopkg.in/cheggaaa/pb.v1 v1.0.25/go.mod h1:V/YB90LKu/1FcN3WVnfiiE5oMCibMjukxqG/qStrOgw=
 gopkg.in/errgo.v2 v2.1.0/go.mod h1:hNsd1EY+bozCKY1Ytp96fpM3vjJbqLJn88ws8XvfDNI=
+gopkg.in/fsnotify.v1 v1.4.7 h1:xOHLXZwVvI9hhs+cLKq5+I5onOuwQLhQwiu63xxlHs4=
 gopkg.in/fsnotify.v1 v1.4.7/go.mod h1:Tz8NjZHkW78fSQdbUxIjBTcgA1z1m8ZHf0WmKUhAMys=
 gopkg.in/go-playground/webhooks.v5 v5.15.0/go.mod h1:LZbya/qLVdbqDR1aKrGuWV6qbia2zCYSR5dpom2SInQ=
 gopkg.in/inf.v0 v0.9.1 h1:73M5CoZyi3ZLMOyDlQh031Cx6N9NDJ2Vvfl76EDAgDc=
@@ -1058,6 +1069,7 @@ gopkg.in/square/go-jose.v2 v2.4.1/go.mod h1:M9dMgbHiYLoDGQrXy7OpJDJWiKiU//h+vD76
 gopkg.in/src-d/go-billy.v4 v4.3.2/go.mod h1:nDjArDMp+XMs1aFAESLRjfGSgfvoYN0hDfzEk0GjC98=
 gopkg.in/src-d/go-git-fixtures.v3 v3.5.0/go.mod h1:dLBcvytrw/TYZsNTWCnkNF2DSIlzWYqTe3rJR56Ac7g=
 gopkg.in/src-d/go-git.v4 v4.13.1/go.mod h1:nx5NYcxdKxq5fpltdHnPa2Exj4Sx0EclMWZQbYDu2z8=
+gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7 h1:uRGJdciOHaEIrze2W8Q3AKkepLTh2hOroT7a+7czfdQ=
 gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7/go.mod h1:dt/ZhP58zS4L8KSrWDmTeBkI65Dw0HsyUHuEVlX15mw=
 gopkg.in/warnings.v0 v0.1.2/go.mod h1:jksf8JmL6Qr/oQM2OXTHunEvvTAsrWBLb6OOjuVWRNI=
 gopkg.in/yaml.v2 v2.0.0-20170812160011-eb3733d160e7/go.mod h1:JAlM8MvJe8wmxCU4Bli9HhUf9+ttbYbLASfIpnQbh74=
@@ -1086,50 +1098,30 @@ istio.io/gogo-genproto v0.0.0-20190930162913-45029607206a h1:w7zILua2dnYo9CxImhp
 istio.io/gogo-genproto v0.0.0-20190930162913-45029607206a/go.mod h1:OzpAts7jljZceG4Vqi5/zXy/pOg1b209T3jb7Nv5wIs=
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 k8s.io/api v0.17.8/go.mod h1:N++Llhs8kCixMUoCaXXAyMMPbo8dDVnh+IQ36xZV2/0=
-k8s.io/api v0.18.2 h1:wG5g5ZmSVgm5B+eHMIbI9EGATS2L8Z72rda19RIEgY8=
-k8s.io/api v0.18.2/go.mod h1:SJCWI7OLzhZSvbY7U8zwNl9UA4o1fizoug34OV/2r78=
-k8s.io/api v0.19.6 h1:F3lfwgpKcKms6F1mMqkQXFzXmme8QqHTJBtBkev3TOg=
-k8s.io/api v0.19.6/go.mod h1:Plxx44Nh4zVblkJrIgxVPgPre1mvng6tXf1Sj3bs0fU=
 k8s.io/apiextensions-apiserver v0.18.2/go.mod h1:q3faSnRGmYimiocj6cHQ1I3WpLqmDgJFlKL37fC4ZvY=
 k8s.io/apimachinery v0.17.8 h1:zXvd8rYMAjRJXpILP9tdAiUnFIENM9EmHuE81apIoms=
 k8s.io/apimachinery v0.17.8/go.mod h1:Lg8zZ5iC/O8UjCqW6DNhcQG2m4TdjF9kwG3891OWbbA=
-k8s.io/apimachinery v0.18.2 h1:44CmtbmkzVDAhCpRVSiP2R5PPrC2RtlIv/MoB8xpdRA=
-k8s.io/apimachinery v0.18.2/go.mod h1:9SnR/e11v5IbyPCGbvJViimtJ0SwHG4nfZFjU77ftcA=
-k8s.io/apimachinery v0.19.6 h1:kBLzSGuDdY1NdSV2uFzI+FwZ9wtkmG+X3ZVcWXSqNgA=
-k8s.io/apimachinery v0.19.6/go.mod h1:6sRbGRAVY5DOCuZwB5XkqguBqpqLU6q/kOaOdk29z6Q=
 k8s.io/apiserver v0.18.2/go.mod h1:Xbh066NqrZO8cbsoenCwyDJ1OSi8Ag8I2lezeHxzwzw=
 k8s.io/client-go v0.17.8 h1:cuZSfjqVrNjoZ3wViQHljFPyWMOcgxUjjmQs5Rifbxk=
 k8s.io/client-go v0.17.8/go.mod h1:SJsDS64AAtt9VZyeaQMb4Ck5etCitZ/FwajWdzua5eY=
-k8s.io/client-go v0.18.2 h1:aLB0iaD4nmwh7arT2wIn+lMnAq7OswjaejkQ8p9bBYE=
-k8s.io/client-go v0.18.2/go.mod h1:Xcm5wVGXX9HAA2JJ2sSBUn3tCJ+4SVlCbl2MNNv+CIU=
-k8s.io/client-go v0.19.6 h1:vtPb33nP8DBMW+/CyuJ8fiie36c3CM1Ts6L4Tsr+PtU=
-k8s.io/client-go v0.19.6/go.mod h1:gEiS+efRlXYUEQ9Oz4lmNXlxAl5JZ8y2zbTDGhvXXnk=
 k8s.io/code-generator v0.17.5/go.mod h1:qdiSCSTKtS+3WtPelj2h57fylSQcPUlhMVm+TD9Dvqc=
 k8s.io/code-generator v0.18.2/go.mod h1:+UHX5rSbxmR8kzS+FAv7um6dtYrZokQvjHpDSYRVkTc=
 k8s.io/component-base v0.18.2/go.mod h1:kqLlMuhJNHQ9lz8Z7V5bxUUtjFZnrypArGl58gmDfUM=
 k8s.io/gengo v0.0.0-20190128074634-0689ccc1d7d6/go.mod h1:ezvh/TsK7cY6rbqRK0oQQ8IAqLxYwwyPxAX1Pzy0ii0=
 k8s.io/gengo v0.0.0-20190822140433-26a664648505/go.mod h1:ezvh/TsK7cY6rbqRK0oQQ8IAqLxYwwyPxAX1Pzy0ii0=
 k8s.io/gengo v0.0.0-20200114144118-36b2048a9120/go.mod h1:ezvh/TsK7cY6rbqRK0oQQ8IAqLxYwwyPxAX1Pzy0ii0=
-k8s.io/gengo v0.0.0-20200413195148-3a45101e95ac/go.mod h1:ezvh/TsK7cY6rbqRK0oQQ8IAqLxYwwyPxAX1Pzy0ii0=
 k8s.io/klog v0.0.0-20181102134211-b9b56d5dfc92/go.mod h1:Gq+BEi5rUBO/HRz0bTSXDUcqjScdoY3a9IHpCEIOOfk=
 k8s.io/klog v0.3.0/go.mod h1:Gq+BEi5rUBO/HRz0bTSXDUcqjScdoY3a9IHpCEIOOfk=
 k8s.io/klog v1.0.0 h1:Pt+yjF5aB1xDSVbau4VsWe+dQNzA0qv1LlXdC2dF6Q8=
 k8s.io/klog v1.0.0/go.mod h1:4Bi6QPql/J/LkTDqv7R/cd3hPo4k2DG6Ptcz060Ez5I=
-k8s.io/klog/v2 v2.0.0/go.mod h1:PBfzABfn139FHAV07az/IF9Wp1bkk3vpT2XSJ76fSDE=
-k8s.io/klog/v2 v2.2.0 h1:XRvcwJozkgZ1UQJmfMGpvRthQHOvihEhYtDfAaxMz/A=
-k8s.io/klog/v2 v2.2.0/go.mod h1:Od+F08eJP+W3HUb4pSrPpgp9DGU4GzlpG/TmITuYh/Y=
 k8s.io/kube-openapi v0.0.0-20200121204235-bf4fb3bd569c/go.mod h1:GRQhZsXIAJ1xR0C9bd8UpWHZ5plfAS9fzPjJuQ6JL3E=
 k8s.io/kube-openapi v0.0.0-20200316234421-82d701f24f9d/go.mod h1:F+5wygcW0wmRTnM3cOgIqGivxkwSWIWT5YdsDbeAOaU=
 k8s.io/kube-openapi v0.0.0-20200410145947-bcb3869e6f29 h1:NeQXVJ2XFSkRoPzRo8AId01ZER+j8oV4SZADT4iBOXQ=
 k8s.io/kube-openapi v0.0.0-20200410145947-bcb3869e6f29/go.mod h1:F+5wygcW0wmRTnM3cOgIqGivxkwSWIWT5YdsDbeAOaU=
-k8s.io/kube-openapi v0.0.0-20200805222855-6aeccd4b50c6 h1:+WnxoVtG8TMiudHBSEtrVL1egv36TkkJm+bA8AxicmQ=
-k8s.io/kube-openapi v0.0.0-20200805222855-6aeccd4b50c6/go.mod h1:UuqjUnNftUyPE5H64/qeyjQoUZhGpeFDVdxjTeEVN2o=
 k8s.io/utils v0.0.0-20191114184206-e782cd3c129f/go.mod h1:sZAwmy6armz5eXlNoLmJcl4F1QuKu7sr+mFQ0byX7Ew=
 k8s.io/utils v0.0.0-20200324210504-a9aa75ae1b89/go.mod h1:sZAwmy6armz5eXlNoLmJcl4F1QuKu7sr+mFQ0byX7Ew=
 k8s.io/utils v0.0.0-20200327001022-6496210b90e8 h1:6JFbaLjRyBz8K2Jvt+pcT+N3vvwMZfg8MfVENwe9aag=
 k8s.io/utils v0.0.0-20200327001022-6496210b90e8/go.mod h1:sZAwmy6armz5eXlNoLmJcl4F1QuKu7sr+mFQ0byX7Ew=
-k8s.io/utils v0.0.0-20200729134348-d5654de09c73 h1:uJmqzgNWG7XyClnU/mLPBWwfKKF1K8Hf8whTseBgJcg=
-k8s.io/utils v0.0.0-20200729134348-d5654de09c73/go.mod h1:jPW/WVKK9YHAvNhRxK0md/EJ228hCsBRufyofKtW8HA=
 modernc.org/cc v1.0.0/go.mod h1:1Sk4//wdnYJiUIxnW8ddKpaOJCF37yAdqYnkxUpaYxw=
 modernc.org/golex v1.0.0/go.mod h1:b/QX9oBD/LhixY6NDh+IdGv17hgB+51fET1i2kPSmvk=
 modernc.org/mathutil v1.0.0/go.mod h1:wU0vUrJsVWBZ4P6e7xtFJEhFSNsfRLJ8H458uRjg03k=
@@ -1141,14 +1133,9 @@ rsc.io/quote/v3 v3.1.0/go.mod h1:yEA65RcK8LyAZtP9Kv3t0HmxON59tX3rD+tICJqUlj0=
 rsc.io/sampler v1.3.0/go.mod h1:T1hPZKmBbMNahiBKFy5HrXp6adAjACjK9JXDnKaTXpA=
 sigs.k8s.io/apiserver-network-proxy/konnectivity-client v0.0.7/go.mod h1:PHgbrJT7lCHcxMU+mDHEm+nx46H4zuuHZkDP6icnhu0=
 sigs.k8s.io/controller-tools v0.3.0/go.mod h1:enhtKGfxZD1GFEoMgP8Fdbu+uKQ/cq1/WGJhdVChfvI=
-sigs.k8s.io/structured-merge-diff v0.0.0-20190525122527-15d366b2352e h1:4Z09Hglb792X0kfOBBJUPFEyvVfQWrYT/l8h5EKA6JQ=
-sigs.k8s.io/structured-merge-diff v0.0.0-20190525122527-15d366b2352e/go.mod h1:wWxsB5ozmmv/SG7nM11ayaAW51xMvak/t1r0CSlcokI=
 sigs.k8s.io/structured-merge-diff/v2 v2.0.1/go.mod h1:Wb7vfKAodbKgf6tn1Kl0VvGj7mRH6DGaRcixXEJXTsE=
 sigs.k8s.io/structured-merge-diff/v3 v3.0.0-20200116222232-67a7b8c61874/go.mod h1:PlARxl6Hbt/+BC80dRLi1qAmnMqwqDg62YvvVkZjemw=
-sigs.k8s.io/structured-merge-diff/v3 v3.0.0 h1:dOmIZBMfhcHS09XZkMyUgkq5trg3/jRyJYFZUiaOp8E=
 sigs.k8s.io/structured-merge-diff/v3 v3.0.0/go.mod h1:PlARxl6Hbt/+BC80dRLi1qAmnMqwqDg62YvvVkZjemw=
-sigs.k8s.io/structured-merge-diff/v4 v4.0.1 h1:YXTMot5Qz/X1iBRJhAt+vI+HVttY0WkSqqhKxQ0xVbA=
-sigs.k8s.io/structured-merge-diff/v4 v4.0.1/go.mod h1:bJZC9H9iH24zzfZ/41RGcq60oK1F7G282QMXDPYydCw=
 sigs.k8s.io/yaml v1.1.0/go.mod h1:UJmg0vDUVViEyp3mgSv9WPwZCDxu4rQW1olrI1uml+o=
 sigs.k8s.io/yaml v1.2.0 h1:kr/MCeFWJWTwyaHoR9c8EjH9OumOmoF9YGiZd7lFm/Q=
 sigs.k8s.io/yaml v1.2.0/go.mod h1:yfXDCHCao9+ENCvLSE62v9VSji2MKu5jeNfTrofGhJc=

main.go

@@ -157,6 +157,8 @@ func startRPCServer(db *v1.DB, kubeConfig *v1.Config, sysConfig v1.SystemConfig,
 	api.RegisterWorkspaceServiceServer(s, server.NewWorkspaceServer())
 	api.RegisterConfigServiceServer(s, server.NewConfigServer())
 	api.RegisterServiceServiceServer(s, server.NewServiceServer())
+	api.RegisterFileServiceServer(s, server.NewFileServer())
+	api.RegisterInferenceServiceServer(s, server.NewInferenceService())
 
 	go func() {
 		if err := s.Serve(lis); err != nil {
@@ -192,6 +194,8 @@ func startHTTPProxy() {
 	registerHandler(api.RegisterWorkspaceServiceHandlerFromEndpoint, ctx, mux, endpoint, opts)
 	registerHandler(api.RegisterConfigServiceHandlerFromEndpoint, ctx, mux, endpoint, opts)
 	registerHandler(api.RegisterServiceServiceHandlerFromEndpoint, ctx, mux, endpoint, opts)
+	registerHandler(api.RegisterFileServiceHandlerFromEndpoint, ctx, mux, endpoint, opts)
+	registerHandler(api.RegisterInferenceServiceHandlerFromEndpoint, ctx, mux, endpoint, opts)
 
 	log.Printf("Starting HTTP proxy on port %v", *httpPort)
 
@@ -284,6 +288,8 @@ func customHeaderMatcher(key string) (string, bool) {
 	switch lowerCaseKey {
 	case "onepanel-auth-token":
 		return lowerCaseKey, true
+	case "onepanel-access-token":
+		return lowerCaseKey, true
 	case "cookie":
 		return lowerCaseKey, true
 	default:

manifest/abs/deployment.json

@@ -0,0 +1,63 @@
+{
+  "apiVersion": "apps/v1",
+  "kind": "Deployment",
+  "metadata": {
+    "name": "minio-gateway",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "spec": {
+    "replicas": 1,
+    "selector": {
+      "matchLabels": {
+        "app": "minio-gateway"
+      }
+    },
+    "template": {
+      "metadata": {
+        "labels": {
+          "app": "minio-gateway"
+        },
+        "annotations": {
+          "sidecar.istio.io/inject": "false"
+        }
+      },
+      "spec": {
+        "containers": [
+          {
+            "name": "minio-gateway",
+            "image": "minio/minio:RELEASE.2021-06-17T00-10-46Z.hotfix.49f6035b1",
+            "args": [
+                "gateway",
+                "azure"
+            ],
+            "env": [
+              {
+                "name": "MINIO_ACCESS_KEY",
+                "valueFrom": {
+                  "secretKeyRef": {
+                    "name": "onepanel",
+                    "key": "artifactRepositoryS3AccessKey"
+                  }
+                }
+              },
+              {
+                "name": "MINIO_SECRET_KEY",
+                "valueFrom": {
+                  "secretKeyRef": {
+                    "name": "onepanel",
+                    "key": "artifactRepositoryS3SecretKey"
+                  }
+                }
+              }
+            ],
+            "ports": [
+              {
+                "containerPort": 9000
+              }
+            ]
+          }
+        ]
+      }
+    }
+  }
+}

manifest/abs/service.json

@@ -0,0 +1,19 @@
+{
+  "apiVersion": "v1",
+  "kind": "Service",
+  "metadata": {
+    "name": "minio-gateway",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "spec": {
+    "selector": {
+      "app": "minio-gateway"
+    },
+    "ports": [
+      {
+        "port": 9000,
+        "targetPort": 9000
+      }
+    ]
+  }
+}

manifest/clusterrolebinding-models.json

@@ -0,0 +1,19 @@
+{
+  "apiVersion": "rbac.authorization.k8s.io/v1",
+  "kind": "ClusterRoleBinding",
+  "metadata": {
+    "name": "onepanel-kfserving-$(applicationDefaultNamespace)"
+  },
+  "subjects": [
+    {
+      "kind": "ServiceAccount",
+      "name": "$(applicationDefaultNamespace)",
+      "namespace": "$(applicationDefaultNamespace)"
+    }
+  ],
+  "roleRef": {
+    "apiGroup": "rbac.authorization.k8s.io",
+    "kind": "ClusterRole",
+    "name": "onepanel-models"
+  }
+}

manifest/clusterrolebinding-onepanel-namespaces-defaultnamespace.json

@@ -0,0 +1,22 @@
+{
+  "apiVersion": "rbac.authorization.k8s.io/v1beta1",
+  "kind": "ClusterRoleBinding",
+  "metadata": {
+    "labels": {
+      "app": "onepanel"
+    },
+    "name": "onepanel-namespaces"
+  },
+  "roleRef": {
+    "apiGroup": "rbac.authorization.k8s.io",
+    "kind": "ClusterRole",
+    "name": "onepanel-namespaces"
+  },
+  "subjects": [
+    {
+      "kind": "ServiceAccount",
+      "name": "$(applicationDefaultNamespace)",
+      "namespace": "$(applicationDefaultNamespace)"
+    }
+  ]
+}

manifest/configmap-onepanel-defaultnamespace.json

@@ -0,0 +1,11 @@
+{
+  "apiVersion": "v1",
+  "kind": "ConfigMap",
+  "metadata": {
+    "name": "onepanel",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "data": {
+    "artifactRepository": "archiveLogs: true\n$(artifactRepositoryProvider)\n"
+  }
+}

manifest/gcs/deployment.json

@@ -0,0 +1,83 @@
+{
+  "apiVersion": "apps/v1",
+  "kind": "Deployment",
+  "metadata": {
+    "name": "minio-gateway",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "spec": {
+    "replicas": 1,
+    "selector": {
+      "matchLabels": {
+        "app": "minio-gateway"
+      }
+    },
+    "template": {
+      "metadata": {
+        "labels": {
+          "app": "minio-gateway"
+        },
+        "annotations": {
+          "sidecar.istio.io/inject": "false"
+        }
+      },
+      "spec": {
+        "containers": [
+          {
+            "name": "minio-gateway",
+            "image": "minio/minio:RELEASE.2021-06-17T00-10-46Z.hotfix.49f6035b1",
+            "volumeMounts": [
+              {
+                "name": "gcs-credentials",
+                "mountPath": "/etc/gcs",
+                "readOnly": true
+              }
+            ],
+            "args": [
+                "gateway",
+                "gcs"
+            ],
+            "env": [
+              {
+                "name": "MINIO_ACCESS_KEY",
+                "valueFrom": {
+                  "secretKeyRef": {
+                    "name": "onepanel",
+                    "key": "artifactRepositoryS3AccessKey"
+                  }
+                }
+              },
+              {
+                "name": "MINIO_SECRET_KEY",
+                "valueFrom": {
+                  "secretKeyRef": {
+                    "name": "onepanel",
+                    "key": "artifactRepositoryS3SecretKey"
+                  }
+                }
+              },
+              {
+                "name": "GOOGLE_APPLICATION_CREDENTIALS",
+                "value": "/etc/gcs/credentials.json"
+              }
+            ]
+          }
+        ],
+        "volumes": [
+          {
+            "name": "gcs-credentials",
+            "projected": {
+              "sources": [
+                {
+                  "secret": {
+                    "name": "artifact-repository-gcs-credentials"
+                  }
+                }
+              ]
+            }
+          }
+        ]
+      }
+    }
+  }
+}

manifest/gcs/service.json

@@ -0,0 +1,19 @@
+{
+  "apiVersion": "v1",
+  "kind": "Service",
+  "metadata": {
+    "name": "minio-gateway",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "spec": {
+    "selector": {
+      "app": "minio-gateway"
+    },
+    "ports": [
+      {
+        "port": 9000,
+        "targetPort": 9000
+      }
+    ]
+  }
+}

manifest/kfserving/secret.json

@@ -0,0 +1,19 @@
+{
+  "apiVersion": "v1",
+  "kind": "Secret",
+  "metadata": {
+    "name": "kfserving-storage",
+    "namespace": "$(applicationDefaultNamespace)",
+    "annotations": {
+      "serving.kubeflow.org/s3-endpoint": "$(artifactRepositoryS3Endpoint)",
+      "serving.kubeflow.org/s3-usehttps": "0",
+      "serving.kubeflow.org/s3-region": "$(artifactRepositoryS3Region)",
+      "serving.kubeflow.org/s3-useanoncredential": "false"
+    }
+  },
+  "type": "Opaque",
+  "data": {
+    "AWS_ACCESS_KEY_ID": "$(artifactRepositoryS3AccessKey)",
+    "AWS_SECRET_ACCESS_KEY": "$(artifactRepositoryS3SecretKey)"
+  }
+}

manifest/networkpolicy-onepanel-defaultnamespace.json

@@ -0,0 +1,41 @@
+{
+  "apiVersion": "networking.k8s.io/v1",
+  "kind": "NetworkPolicy",
+  "metadata": {
+    "labels": {
+      "app": "onepanel"
+    },
+    "name": "onepanel",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "spec": {
+    "egress": [
+      {
+        "to": [
+          {
+            "ipBlock": {
+              "cidr": "0.0.0.0/0",
+              "except": [
+                  "169.254.169.254/32"
+              ]
+            }
+          }
+        ]
+      }
+    ],
+    "ingress": [
+      {
+        "from": [
+          {
+            "namespaceSelector": {
+              "matchLabels": {
+                "app.kubernetes.io/part-of": "onepanel"
+              }
+            }
+          }
+        ]
+      }
+    ],
+    "podSelector": {}
+  }
+}