Merge pull request #964 from Vafilor/feat/remove.links

fix: remove slack link

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

@@ -6,7 +6,6 @@
 [![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)
 
@@ -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).
 
@@ -42,7 +36,4 @@ Onepanel seamlessly integrates the following open source projects under the hood
 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"
@@ -4184,6 +4184,9 @@
       "properties": {
         "name": {
           "type": "string"
+        },
+        "sourceName": {
+          "type": "string"
         }
       }
     },

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/proto/namespace.proto

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

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/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

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": {}
+  }
+}

manifest/role-onepanel-defaultnamespace.json

@@ -0,0 +1,167 @@
+{
+  "apiVersion": "rbac.authorization.k8s.io/v1beta1",
+  "kind": "Role",
+  "metadata": {
+    "labels": {
+      "app": "onepanel"
+    },
+    "name": "onepanel",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "rules": [
+    {
+      "apiGroups": [
+        ""
+      ],
+      "resources": [
+        "configmaps"
+      ],
+      "verbs": [
+        "get"
+      ]
+    },
+    {
+      "apiGroups": [
+        ""
+      ],
+      "resources": [
+        "pods",
+        "pods/log"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "patch"
+      ]
+    },
+    {
+      "apiGroups": [
+        ""
+      ],
+      "resources": [
+        "persistentvolumeclaims",
+        "services",
+        "secrets"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "list",
+        "create",
+        "update",
+        "patch",
+        "delete"
+      ]
+    },
+    {
+      "apiGroups": [
+        "apps"
+      ],
+      "resources": [
+        "statefulsets",
+        "deployments"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "list",
+        "create",
+        "update",
+        "patch",
+        "delete"
+      ]
+    },
+    {
+      "apiGroups": [
+        "networking.istio.io"
+      ],
+      "resources": [
+        "virtualservices"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "list",
+        "create",
+        "update",
+        "patch",
+        "delete"
+      ]
+    },
+    {
+      "apiGroups": [
+        "argoproj.io"
+      ],
+      "resources": [
+        "workflows",
+        "workflowtemplates",
+        "cronworkflows"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "list",
+        "create",
+        "update",
+        "patch",
+        "delete"
+      ]
+    },
+    {
+      "apiGroups": [
+        "onepanel.io"
+      ],
+      "resources": [
+        "workspaces"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "list",
+        "create",
+        "update",
+        "patch",
+        "delete"
+      ]
+    },
+    {
+      "apiGroups": [
+        "onepanel.io"
+      ],
+      "resources": [
+        "services"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "list",
+        "create",
+        "update",
+        "patch",
+        "delete"
+      ]
+    },
+    {
+      "apiGroups": [
+        "serving.kubeflow.org"
+      ],
+      "resources": [
+        "inferenceservices"
+      ],
+      "verbs": [
+        "get",
+        "watch",
+        "list",
+        "create",
+        "update",
+        "patch",
+        "delete"
+      ]
+    },
+    {
+      "apiGroups": [""],
+      "resources": ["onepanel-service"],
+      "verbs": ["get", "watch", "list"]
+    }
+  ]
+}

manifest/rolebinding-onepanel-defaultnamespace.json

@@ -0,0 +1,28 @@
+{
+  "apiVersion": "rbac.authorization.k8s.io/v1beta1",
+  "kind": "RoleBinding",
+  "metadata": {
+    "labels": {
+      "app": "onepanel"
+    },
+    "name": "onepanel",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "roleRef": {
+    "apiGroup": "rbac.authorization.k8s.io",
+    "kind": "Role",
+    "name": "onepanel"
+  },
+  "subjects": [
+    {
+      "kind": "ServiceAccount",
+      "name": "default",
+      "namespace": "$(applicationDefaultNamespace)"
+    },
+    {
+      "kind": "ServiceAccount",
+      "name": "$(applicationDefaultNamespace)",
+      "namespace": "$(applicationDefaultNamespace)"
+    }
+  ]
+}

manifest/secret-onepanel-default-env-defaultnamespace.json

@@ -0,0 +1,9 @@
+{
+  "apiVersion": "v1",
+  "kind": "Secret",
+  "metadata": {
+    "name": "onepanel-default-env",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "type": "Opaque"
+}

manifest/secret-onepanel-defaultnamespace.json

@@ -0,0 +1,21 @@
+{
+  "apiVersion": "v1",
+  "kind": "Secret",
+  "metadata": {
+    "name": "onepanel",
+    "namespace": "$(applicationDefaultNamespace)",
+    "labels": {
+      "app.kubernetes.io/component": "onepanel",
+      "app.kubernetes.io/instance": "onepanel-v0.5.0",
+      "app.kubernetes.io/managed-by": "onepanel-cli",
+      "app.kubernetes.io/name": "onepanel",
+      "app.kubernetes.io/part-of": "onepanel",
+      "app.kubernetes.io/version": "v0.5.0"
+    }
+  },
+  "data": {
+    "artifactRepositoryS3AccessKey": "$(artifactRepositoryS3AccessKey)",
+    "artifactRepositoryS3SecretKey": "$(artifactRepositoryS3SecretKey)"
+  },
+  "type": "Opaque"
+}

manifest/service-account.json

@@ -0,0 +1,8 @@
+{
+  "kind": "ServiceAccount",
+  "apiVersion": "v1",
+  "metadata": {
+    "name": "$(applicationDefaultNamespace)",
+    "namespace": "$(applicationDefaultNamespace)"
+  }
+}

manifest/service-minio-onepanel.json

@@ -0,0 +1,37 @@
+{
+  "apiVersion": "networking.istio.io/v1alpha3",
+  "kind": "VirtualService",
+  "metadata": {
+    "name": "minio",
+    "namespace": "$(applicationDefaultNamespace)"
+  },
+  "spec": {
+    "hosts": [
+      "sys-storage-$(applicationDefaultNamespace).$(applicationDomain)"
+    ],
+    "gateways": [
+      "istio-system/ingressgateway"
+    ],
+    "http": [
+      {
+        "match": [
+          {
+            "uri": {
+              "prefix": "/"
+            }
+          }
+        ],
+        "route": [
+          {
+            "destination": {
+              "port": {
+                "number": 9000
+              },
+              "host": "minio-gateway.$(applicationDefaultNamespace).svc.cluster.local"
+            }
+          }
+        ]
+      }
+    ]
+  }
+}

pkg/client.go

@@ -5,14 +5,17 @@ import (
 	sq "github.com/Masterminds/squirrel"
 	argoprojv1alpha1 "github.com/argoproj/argo/pkg/client/clientset/versioned/typed/workflow/v1alpha1"
 	"github.com/jmoiron/sqlx"
+	"github.com/onepanelio/core/pkg/util"
 	"github.com/onepanelio/core/pkg/util/env"
 	"github.com/onepanelio/core/pkg/util/gcs"
 	"github.com/onepanelio/core/pkg/util/router"
 	"github.com/onepanelio/core/pkg/util/s3"
 	log "github.com/sirupsen/logrus"
+	"google.golang.org/grpc/codes"
 	"k8s.io/client-go/kubernetes"
 	"k8s.io/client-go/rest"
 	"k8s.io/client-go/tools/clientcmd"
+	"sigs.k8s.io/yaml"
 	"strconv"
 	"time"
 )
@@ -27,6 +30,7 @@ type Client struct {
 	argoprojV1alpha1 argoprojv1alpha1.ArgoprojV1alpha1Interface
 	*DB
 	systemConfig SystemConfig
+	cache        map[string]interface{}
 }
 
 func (c *Client) ArgoprojV1alpha1() argoprojv1alpha1.ArgoprojV1alpha1Interface {
@@ -102,6 +106,7 @@ func NewClient(config *Config, db *DB, systemConfig SystemConfig) (client *Clien
 		argoprojV1alpha1: argoClient,
 		DB:               db,
 		systemConfig:     systemConfig,
+		cache:            make(map[string]interface{}),
 	}, nil
 }
 
@@ -175,7 +180,12 @@ func (c *Client) GetWebRouter() (router.Web, error) {
 // GetArtifactRepositoryType returns the configured artifact repository type for the given namespace.
 // possible return values are: "s3", "gcs"
 func (c *Client) GetArtifactRepositoryType(namespace string) (string, error) {
-	artifactRepositoryType := "s3"
+	artifactRepositoryType, ok := c.cache["artifactRepositoryType"]
+	if ok {
+		return artifactRepositoryType.(string), nil
+	}
+
+	artifactRepositoryType = "s3"
 	nsConfig, err := c.GetNamespaceConfig(namespace)
 	if err != nil {
 		return "", err
@@ -184,7 +194,38 @@ func (c *Client) GetArtifactRepositoryType(namespace string) (string, error) {
 		artifactRepositoryType = "gcs"
 	}
 
-	return artifactRepositoryType, nil
+	c.cache["artifactRepositoryType"] = artifactRepositoryType
+
+	return artifactRepositoryType.(string), nil
+}
+
+// GetArtifactRepositorySource returns the original source for the artifact repository
+// This can be s3, abs, gcs, etc. Since everything goes through an S3 compatible API,
+// it is sometimes useful to know the source.
+func (c *Client) GetArtifactRepositorySource(namespace string) (string, error) {
+	configMap, err := c.getConfigMap(namespace, "onepanel")
+	if err != nil {
+		log.WithFields(log.Fields{
+			"Namespace": namespace,
+			"Error":     err.Error(),
+		}).Error("getArtifactRepositorySource failed getting config map.")
+		return "", err
+	}
+
+	config := &NamespaceConfig{
+		ArtifactRepository: ArtifactRepositoryProvider{},
+	}
+
+	err = yaml.Unmarshal([]byte(configMap.Data["artifactRepository"]), &config.ArtifactRepository)
+	if err != nil || (config.ArtifactRepository.S3 == nil && config.ArtifactRepository.GCS == nil) {
+		return "", util.NewUserError(codes.NotFound, "Artifact repository config not found.")
+	}
+
+	if config.ArtifactRepository.S3 != nil {
+		return config.ArtifactRepository.S3.Source, nil
+	}
+
+	return config.ArtifactRepository.GCS.Source, nil
 }
 
 // getKubernetesTimeout returns the timeout for kubernetes requests.

pkg/config.go

@@ -26,6 +26,7 @@ func (c *Client) getConfigMap(namespace, name string) (configMap *ConfigMap, err
 // GetSystemConfig will pull it from the resources
 func (c *Client) ClearSystemConfigCache() {
 	c.systemConfig = nil
+	c.cache = make(map[string]interface{})
 }
 
 // GetSystemConfig loads various system configurations and bundles them into a map.
@@ -90,17 +91,14 @@ func (c *Client) GetNamespaceConfig(namespace string) (config *NamespaceConfig,
 		return
 	}
 
-	switch {
-	case config.ArtifactRepository.S3 != nil:
-		{
-			accessKey, _ := base64.StdEncoding.DecodeString(secret.Data[config.ArtifactRepository.S3.AccessKeySecret.Key])
-			config.ArtifactRepository.S3.AccessKey = string(accessKey)
-			secretKey, _ := base64.StdEncoding.DecodeString(secret.Data[config.ArtifactRepository.S3.SecretKeySecret.Key])
-			config.ArtifactRepository.S3.Secretkey = string(secretKey)
-		}
-	default:
+	if config.ArtifactRepository.S3 == nil {
 		return nil, util.NewUserError(codes.NotFound, "Artifact repository config not found.")
 	}
 
+	accessKey, _ := base64.StdEncoding.DecodeString(secret.Data[config.ArtifactRepository.S3.AccessKeySecret.Key])
+	config.ArtifactRepository.S3.AccessKey = string(accessKey)
+	secretKey, _ := base64.StdEncoding.DecodeString(secret.Data[config.ArtifactRepository.S3.SecretKeySecret.Key])
+	config.ArtifactRepository.S3.Secretkey = string(secretKey)
+
 	return
 }

pkg/config_types.go

@@ -174,6 +174,11 @@ func (s SystemConfig) DatabaseDriverName() *string {
 	return s.GetValue("databaseDriverName")
 }
 
+// Provider gets the ONEPANEL_PROVIDER value, or nil.
+func (s SystemConfig) Provider() *string {
+	return s.GetValue("ONEPANEL_PROVIDER")
+}
+
 // DatabaseConnection returns system config information to connect to a database
 func (s SystemConfig) DatabaseConnection() (driverName, dataSourceName string) {
 	dataSourceName = fmt.Sprintf("host=%v user=%v password=%v dbname=%v sslmode=disable",
@@ -243,6 +248,7 @@ func (s SystemConfig) HMACKey() []byte {
 // by the CLI. CLI will marshal this struct into the correct
 // YAML structure for k8s configmap / secret.
 type ArtifactRepositoryS3Provider struct {
+	Source          string
 	KeyFormat       string `yaml:"keyFormat"`
 	Bucket          string
 	Endpoint        string
@@ -260,6 +266,7 @@ type ArtifactRepositoryS3Provider struct {
 // by the CLI. CLI will marshal this struct into the correct
 // YAML structure for k8s configmap / secret.
 type ArtifactRepositoryGCSProvider struct {
+	Source                  string
 	KeyFormat               string `yaml:"keyFormat"`
 	Bucket                  string
 	Endpoint                string

pkg/data.go

@@ -0,0 +1,135 @@
+package v1
+
+import (
+	"github.com/onepanelio/core/pkg/util/data"
+	"github.com/onepanelio/core/pkg/util/extensions"
+)
+
+// createWorkspaceTemplateFromGenericFile will create the workspace template given by {{templateName}} with the contents
+// given by {{filename}} for the input {{namespace}}
+func (c *Client) createWorkspaceTemplateFromGenericManifest(namespace string, manifestFile *data.ManifestFile) (err error) {
+	manifest, err := manifestFile.SpecString()
+	if err != nil {
+		return err
+	}
+	templateName := manifestFile.Metadata.Name
+	description := manifestFile.Metadata.Description
+
+	artifactRepositoryType, err := c.GetArtifactRepositoryType(namespace)
+	if err != nil {
+		return err
+	}
+
+	replaceMap := map[string]string{
+		"{{.ArtifactRepositoryType}}": artifactRepositoryType,
+	}
+	manifest = extensions.ReplaceMapValues(manifest, replaceMap)
+
+	workspaceTemplate, err := CreateWorkspaceTemplate(templateName)
+	if err != nil {
+		return err
+	}
+	workspaceTemplate.Manifest = manifest
+
+	if description != nil {
+		workspaceTemplate.Description = *description
+	}
+
+	_, err = c.CreateWorkspaceTemplate(namespace, workspaceTemplate)
+
+	return
+}
+
+// updateWorkspaceTemplateManifest will update the workspace template given by {{templateName}} with the contents
+// given by {{filename}}
+func (c *Client) updateWorkspaceTemplateManifest(namespace string, manifestFile *data.ManifestFile) (err error) {
+	manifest, err := manifestFile.SpecString()
+	if err != nil {
+		return err
+	}
+	templateName := manifestFile.Metadata.Name
+
+	artifactRepositoryType, err := c.GetArtifactRepositoryType(namespace)
+	if err != nil {
+		return err
+	}
+
+	replaceMap := map[string]string{
+		"{{.ArtifactRepositoryType}}": artifactRepositoryType,
+	}
+	manifest = extensions.ReplaceMapValues(manifest, replaceMap)
+
+	workspaceTemplate, err := CreateWorkspaceTemplate(templateName)
+	if err != nil {
+		return err
+	}
+	workspaceTemplate.Manifest = manifest
+
+	_, err = c.UpdateWorkspaceTemplateManifest(namespace, workspaceTemplate.UID, workspaceTemplate.Manifest)
+
+	return
+}
+
+// createWorkflowTemplate will create the workflow template given by {{templateName}} with the contents
+// given by {{filename}}
+func (c *Client) createWorkflowTemplateFromGenericManifest(namespace string, manifestFile *data.ManifestFile) (err error) {
+	manifest, err := manifestFile.SpecString()
+	if err != nil {
+		return err
+	}
+	templateName := manifestFile.Metadata.Name
+	labels := manifestFile.Metadata.Labels
+
+	artifactRepositoryType, err := c.GetArtifactRepositoryType(namespace)
+	if err != nil {
+		return err
+	}
+
+	replaceMap := map[string]string{
+		"{{.ArtifactRepositoryType}}": artifactRepositoryType,
+	}
+	manifest = extensions.ReplaceMapValues(manifest, replaceMap)
+
+	workflowTemplate, err := CreateWorkflowTemplate(templateName)
+	if err != nil {
+		return
+	}
+	workflowTemplate.Manifest = manifest
+	workflowTemplate.Labels = labels
+
+	_, err = c.CreateWorkflowTemplate(namespace, workflowTemplate)
+
+	return
+}
+
+// updateWorkflowTemplateManifest will update the workflow template given by {{templateName}} with the contents
+// given by {{filename}}
+func (c *Client) updateWorkflowTemplateManifest(namespace string, manifestFile *data.ManifestFile) (err error) {
+	manifest, err := manifestFile.SpecString()
+	if err != nil {
+		return err
+	}
+	templateName := manifestFile.Metadata.Name
+	labels := manifestFile.Metadata.Labels
+
+	artifactRepositoryType, err := c.GetArtifactRepositoryType(namespace)
+	if err != nil {
+		return err
+	}
+
+	replaceMap := map[string]string{
+		"{{.ArtifactRepositoryType}}": artifactRepositoryType,
+	}
+	manifest = extensions.ReplaceMapValues(manifest, replaceMap)
+
+	workflowTemplate, err := CreateWorkflowTemplate(templateName)
+	if err != nil {
+		return
+	}
+	workflowTemplate.Manifest = manifest
+	workflowTemplate.Labels = labels
+
+	_, err = c.CreateWorkflowTemplateVersion(namespace, workflowTemplate)
+
+	return
+}

pkg/istio.go

@@ -0,0 +1,43 @@
+package v1
+
+import (
+	"fmt"
+	"github.com/onepanelio/core/pkg/util"
+	"google.golang.org/grpc/codes"
+	"k8s.io/apimachinery/pkg/runtime/schema"
+	"k8s.io/client-go/kubernetes/scheme"
+	"k8s.io/client-go/rest"
+	"strings"
+)
+
+const istioVirtualServiceResource = "VirtualServices"
+
+func istioModelRestClient() (*rest.RESTClient, error) {
+	config := *NewConfig()
+	config.GroupVersion = &schema.GroupVersion{Group: "networking.istio.io", Version: "v1alpha3"}
+	config.APIPath = "/apis"
+	config.NegotiatedSerializer = scheme.Codecs.WithoutConversion()
+
+	return rest.RESTClientFor(&config)
+}
+
+// CreateVirtualService creates an istio virtual service
+func (c *Client) CreateVirtualService(namespace string, data interface{}) error {
+	restClient, err := istioModelRestClient()
+	if err != nil {
+		return err
+	}
+
+	err = restClient.Post().
+		Namespace(namespace).
+		Resource(istioVirtualServiceResource).
+		Body(data).
+		Do().
+		Error()
+
+	if err != nil && strings.Contains(err.Error(), "already exists") {
+		return util.NewUserError(codes.AlreadyExists, fmt.Sprintf("VirtualService already exists"))
+	}
+
+	return err
+}

pkg/namespace.go

@@ -1,14 +1,39 @@
 package v1
 
 import (
+	"encoding/base64"
 	"fmt"
+	"github.com/onepanelio/core/pkg/util"
+	"github.com/onepanelio/core/pkg/util/data"
+	"google.golang.org/grpc/codes"
+	"io/ioutil"
+	vapps "k8s.io/api/apps/v1"
 	v1 "k8s.io/api/core/v1"
-
+	vnet "k8s.io/api/networking/v1"
+	v1rbac "k8s.io/api/rbac/v1"
 	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
+	"k8s.io/apimachinery/pkg/util/json"
+	"os"
+	"path/filepath"
+	"strings"
 )
 
 var onepanelEnabledLabelKey = "onepanel.io/enabled"
 
+func replaceVariables(filepath string, replacements map[string]string) (string, error) {
+	data, err := ioutil.ReadFile(filepath)
+	if err != nil {
+		return "", err
+	}
+
+	dataStr := string(data)
+	for key, value := range replacements {
+		dataStr = strings.ReplaceAll(dataStr, key, value)
+	}
+
+	return dataStr, nil
+}
+
 func (c *Client) ListOnepanelEnabledNamespaces() (namespaces []*Namespace, err error) {
 	namespaceList, err := c.CoreV1().Namespaces().List(metav1.ListOptions{
 		LabelSelector: fmt.Sprintf("%s=%s", onepanelEnabledLabelKey, "true"),
@@ -42,6 +67,7 @@ func (c *Client) GetNamespace(name string) (namespace *Namespace, err error) {
 	return
 }
 
+// ListNamespaces lists all of the onepanel enabled namespaces
 func (c *Client) ListNamespaces() (namespaces []*Namespace, err error) {
 	namespaceList, err := c.CoreV1().Namespaces().List(metav1.ListOptions{
 		LabelSelector: fmt.Sprintf("%s=%s", onepanelEnabledLabelKey, "true"),
@@ -60,25 +86,433 @@ func (c *Client) ListNamespaces() (namespaces []*Namespace, err error) {
 	return
 }
 
-func (c *Client) CreateNamespace(name string) (namespace *Namespace, err error) {
-	createNamespace := &v1.Namespace{
-		ObjectMeta: metav1.ObjectMeta{
-			Name: name,
-			Labels: map[string]string{
-				"istio-injection":       "enabled",
-				onepanelEnabledLabelKey: "true",
-			},
-		},
+// CreateNamespace creates a namespace named {{ name }} assuming the {{ sourceNamespace }} created it
+func (c *Client) CreateNamespace(sourceNamespace, name string) (namespace *Namespace, err error) {
+	newNamespace := name
+	domain := *c.systemConfig.Domain()
+	artifactRepositorySource, err := c.GetArtifactRepositorySource(sourceNamespace)
+	if err != nil {
+		return nil, err
 	}
 
-	k8Namespace, err := c.CoreV1().Namespaces().Create(createNamespace)
+	config, err := c.GetNamespaceConfig(sourceNamespace)
 	if err != nil {
-		return
+		return nil, err
+	}
+	if config.ArtifactRepository.S3 == nil {
+		return nil, util.NewUserError(codes.Internal, "S3 compatible artifact repository not set")
+	}
+
+	accessKey := config.ArtifactRepository.S3.AccessKey
+	secretKey := config.ArtifactRepository.S3.Secretkey
+
+	if err := c.createK8sNamespace(name); err != nil {
+		return nil, err
+	}
+
+	if err := c.createNetworkPolicy(newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createIstioVirtualService(newNamespace, domain); err != nil {
+		return nil, err
+	}
+
+	if err := c.createRole(newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createDefaultSecret(newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createSecretOnepanelDefaultNamespace(newNamespace, accessKey, secretKey); err != nil {
+		return nil, err
+	}
+
+	if err := c.createProviderDependentMinioDeployment(newNamespace, artifactRepositorySource); err != nil {
+		return nil, err
+	}
+
+	if err := c.createProviderDependentMinioService(newNamespace, artifactRepositorySource); err != nil {
+		return nil, err
+	}
+
+	if err := c.createNamespaceConfigMap(sourceNamespace, newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createNamespaceClusterRoleBinding(newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createNamespaceRoleBinding(newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createNamespaceServiceAccount(newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createNamespaceModelClusterRoleBinding(newNamespace); err != nil {
+		return nil, err
+	}
+
+	if err := c.createNamespaceTemplates(newNamespace); err != nil {
+		return nil, err
 	}
 
 	namespace = &Namespace{
-		Name: k8Namespace.Name,
+		Name: name,
 	}
 
 	return
 }
+
+func (c *Client) createK8sNamespace(name string) error {
+	createNamespace := &v1.Namespace{
+		ObjectMeta: metav1.ObjectMeta{
+			Name: name,
+			Labels: map[string]string{
+				"istio-injection":              "enabled",
+				onepanelEnabledLabelKey:        "true",
+				"app.kubernetes.io/component":  "onepanel",
+				"app.kubernetes.io/instance":   "onepanel-v0.5.0",
+				"app.kubernetes.io/managed-by": "onepanel-cli",
+				"app.kubernetes.io/name":       "onepanel",
+				"app.kubernetes.io/part-of":    "onepanel",
+				"app.kubernetes.io/version":    "v0.5.0",
+			},
+		},
+	}
+
+	_, err := c.CoreV1().Namespaces().Create(createNamespace)
+	if err != nil && strings.Contains(err.Error(), "already exists") {
+		return util.NewUserError(codes.AlreadyExists, "Namespace '"+name+"' already exists")
+	}
+
+	return err
+}
+
+func (c *Client) createNetworkPolicy(namespace string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "networkpolicy-onepanel-defaultnamespace.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	networkPolicy := &vnet.NetworkPolicy{}
+	if err := json.Unmarshal(data, networkPolicy); err != nil {
+		return err
+	}
+
+	_, err = c.NetworkingV1().NetworkPolicies(namespace).Create(networkPolicy)
+
+	return err
+}
+
+func (c *Client) createIstioVirtualService(namespace, domain string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+		"$(applicationDomain)":           domain,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "service-minio-onepanel.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	return c.CreateVirtualService(namespace, data)
+}
+
+func (c *Client) createRole(namespace string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "role-onepanel-defaultnamespace.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	role := &v1rbac.Role{}
+	if err := json.Unmarshal(data, role); err != nil {
+		return err
+	}
+
+	_, err = c.RbacV1().Roles(namespace).Create(role)
+
+	return err
+}
+
+func (c *Client) createDefaultSecret(namespace string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "secret-onepanel-default-env-defaultnamespace.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	secret := &v1.Secret{}
+	if err := json.Unmarshal(data, secret); err != nil {
+		return err
+	}
+
+	_, err = c.CoreV1().Secrets(namespace).Create(secret)
+
+	return err
+}
+
+func (c *Client) createSecretOnepanelDefaultNamespace(namespace, accessKey, secretKey string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)":   namespace,
+		"$(artifactRepositoryS3AccessKey)": base64.StdEncoding.EncodeToString([]byte(accessKey)),
+		"$(artifactRepositoryS3SecretKey)": base64.StdEncoding.EncodeToString([]byte(secretKey)),
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "secret-onepanel-defaultnamespace.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	secret := &v1.Secret{}
+	if err := json.Unmarshal(data, secret); err != nil {
+		return err
+	}
+
+	_, err = c.CoreV1().Secrets(namespace).Create(secret)
+
+	return err
+}
+
+func (c *Client) createProviderDependentMinioDeployment(namespace, artifactRepositoryProvider string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	//// AWS S3 doesn't require a specific artifactRepositoryProvider
+	if artifactRepositoryProvider == "s3" {
+		return nil
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", artifactRepositoryProvider, "deployment.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	deployment := &vapps.Deployment{}
+	if err := json.Unmarshal(data, deployment); err != nil {
+		return err
+	}
+
+	_, err = c.AppsV1().Deployments(namespace).Create(deployment)
+
+	return err
+}
+
+func (c *Client) createProviderDependentMinioService(namespace, artifactRepositoryProvider string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	// AWS S3 doesn't require a specific artifactRepositoryProvider
+	if artifactRepositoryProvider == "s3" {
+		return nil
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", artifactRepositoryProvider, "service.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	service := &v1.Service{}
+	if err := json.Unmarshal(data, service); err != nil {
+		return err
+	}
+
+	_, err = c.CoreV1().Services(namespace).Create(service)
+
+	return err
+}
+
+func (c *Client) createNamespaceClusterRoleBinding(namespace string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "clusterrolebinding-onepanel-namespaces-defaultnamespace.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	resource := &v1rbac.ClusterRoleBinding{}
+	if err := json.Unmarshal(data, resource); err != nil {
+		return err
+	}
+
+	resource.Name += "-" + namespace
+
+	_, err = c.RbacV1().ClusterRoleBindings().Create(resource)
+
+	return err
+}
+
+func (c *Client) createNamespaceRoleBinding(namespace string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "rolebinding-onepanel-defaultnamespace.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	resource := &v1rbac.RoleBinding{}
+	if err := json.Unmarshal(data, resource); err != nil {
+		return err
+	}
+
+	_, err = c.RbacV1().RoleBindings(namespace).Create(resource)
+
+	return err
+}
+
+func (c *Client) createNamespaceServiceAccount(namespace string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "service-account.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	resource := &v1.ServiceAccount{}
+	if err := json.Unmarshal(data, resource); err != nil {
+		return err
+	}
+
+	_, err = c.CoreV1().ServiceAccounts(namespace).Create(resource)
+
+	return err
+}
+
+func (c *Client) createNamespaceConfigMap(sourceNamespace, namespace string) error {
+	sourceConfigMap, err := c.CoreV1().ConfigMaps(sourceNamespace).Get("onepanel", metav1.GetOptions{})
+	if err != nil {
+		return err
+	}
+
+	data := sourceConfigMap.Data["artifactRepository"]
+	sourceKey := "minio-gateway." + sourceNamespace + ".svc.cluster.local:9000"
+	replaceKey := "minio-gateway." + namespace + ".svc.cluster.local:9000"
+	data = strings.ReplaceAll(data, sourceKey, replaceKey)
+	sourceConfigMap.Data["artifactRepository"] = data
+
+	configMap := &v1.ConfigMap{
+		ObjectMeta: metav1.ObjectMeta{
+			Name:      "onepanel",
+			Namespace: namespace,
+		},
+		Data: sourceConfigMap.Data,
+	}
+
+	configMap.Namespace = namespace
+
+	_, err = c.CoreV1().ConfigMaps(namespace).Create(configMap)
+
+	return err
+}
+
+func (c *Client) createNamespaceModelClusterRoleBinding(namespace string) error {
+	replacements := map[string]string{
+		"$(applicationDefaultNamespace)": namespace,
+	}
+
+	dataStr, err := replaceVariables(filepath.Join("manifest", "clusterrolebinding-models.json"), replacements)
+	if err != nil {
+		return err
+	}
+	data := []byte(dataStr)
+
+	resource := &v1rbac.ClusterRoleBinding{}
+	if err := json.Unmarshal(data, resource); err != nil {
+		return err
+	}
+
+	_, err = c.RbacV1().ClusterRoleBindings().Create(resource)
+
+	return err
+}
+
+func (c *Client) createNamespaceTemplates(namespace string) error {
+	wd, err := os.Getwd()
+	if err != nil {
+		return err
+	}
+
+	workflowDir := filepath.Join(wd, "db", "yaml")
+
+	filepaths := make([]string, 0)
+
+	err = filepath.Walk(workflowDir,
+		func(path string, info os.FileInfo, err error) error {
+			if !info.IsDir() {
+				filepaths = append(filepaths, path)
+			}
+
+			return nil
+		},
+	)
+	if err != nil {
+		return err
+	}
+
+	for _, filename := range filepaths {
+		manifest, err := data.ManifestFileFromFile(filename)
+		if err != nil {
+			return err
+		}
+
+		if manifest.Metadata.Kind == "Workflow" {
+			if manifest.Metadata.Action == "create" {
+				if err := c.createWorkflowTemplateFromGenericManifest(namespace, manifest); err != nil {
+					return err
+				}
+			} else {
+				if err := c.updateWorkflowTemplateManifest(namespace, manifest); err != nil {
+					return err
+				}
+			}
+		} else if manifest.Metadata.Kind == "Workspace" {
+			if manifest.Metadata.Action == "create" {
+				if err := c.createWorkspaceTemplateFromGenericManifest(namespace, manifest); err != nil {
+					return err
+				}
+			} else {
+				if err := c.updateWorkspaceTemplateManifest(namespace, manifest); err != nil {
+					return err
+				}
+			}
+		} else {
+			return fmt.Errorf("unknown manifest type for file %v", filename)
+		}
+	}
+
+	return nil
+}

pkg/util/data/migration.go

@@ -0,0 +1,49 @@
+package data
+
+import (
+	"gopkg.in/yaml.v3"
+	"io/ioutil"
+)
+
+// ManifestFile represents a file that contains information about a workflow or workspace template
+type ManifestFile struct {
+	Metadata ManifestFileMetadata `yaml:"metadata"`
+	Spec     interface{}          `yaml:"spec"`
+}
+
+// ManifestFileMetadata represents information about the tempalte we are working with
+type ManifestFileMetadata struct {
+	Name        string
+	Kind        string // {Workflow, Workspace}
+	Version     uint64
+	Action      string // {create,update}
+	Description *string
+	Labels      map[string]string
+	Deprecated  *bool
+	Source      *string
+}
+
+// SpecString returns the spec of a manifest file as a string
+func (m *ManifestFile) SpecString() (string, error) {
+	data, err := yaml.Marshal(m.Spec)
+	if err != nil {
+		return "", err
+	}
+
+	return string(data), err
+}
+
+// ManifestFileFromFile loads a manifest from a yaml file.
+func ManifestFileFromFile(path string) (*ManifestFile, error) {
+	fileData, err := ioutil.ReadFile(path)
+	if err != nil {
+		return nil, err
+	}
+
+	manifest := &ManifestFile{}
+	if err := yaml.Unmarshal(fileData, manifest); err != nil {
+		return nil, err
+	}
+
+	return manifest, nil
+}

pkg/util/extensions/extensions.go

@@ -213,3 +213,17 @@ func DeleteNode(node *yaml.Node, key *YamlIndex) error {
 
 	return nil
 }
+
+// ReplaceMapValues will replace strings that are keys in the input map with their values
+// the result is returned
+func ReplaceMapValues(value string, replaceMap map[string]string) string {
+	replacePairs := make([]string, 0)
+
+	for key, value := range replaceMap {
+		replacePairs = append(replacePairs, key)
+		replacePairs = append(replacePairs, value)
+	}
+
+	return strings.NewReplacer(replacePairs...).
+		Replace(value)
+}

pkg/workflow_execution.go

@@ -929,7 +929,14 @@ func (c *Client) CreateWorkflowExecution(namespace string, workflow *WorkflowExe
 		return nil, fmt.Errorf("workflow Template contained more than 1 workflow execution")
 	}
 
-	createdWorkflow, err := c.createWorkflow(namespace, workflowTemplate.ID, workflowTemplate.WorkflowTemplateVersionID, &workflows[0], opts, workflow.Labels)
+	wf := &workflows[0]
+	if wf.Spec.VolumeClaimGC == nil {
+		wf.Spec.VolumeClaimGC = &wfv1.VolumeClaimGC{
+			Strategy: wfv1.VolumeClaimGCOnCompletion,
+		}
+	}
+
+	createdWorkflow, err := c.createWorkflow(namespace, workflowTemplate.ID, workflowTemplate.WorkflowTemplateVersionID, wf, opts, workflow.Labels)
 	if err != nil {
 		log.WithFields(log.Fields{
 			"Namespace": namespace,

pkg/workflow_template_types.go

@@ -55,6 +55,22 @@ func (wt *WorkflowTemplate) GenerateUID(name string) error {
 	return nil
 }
 
+// CreateWorkflowTemplate creates a new workflow template with the given name.
+// All fields that can be generated in memory without external requests are filled out, such as the UID.
+func CreateWorkflowTemplate(name string) (*WorkflowTemplate, error) {
+	nameUID, err := uid2.GenerateUID(name, 30)
+	if err != nil {
+		return nil, err
+	}
+
+	workflowTemplate := &WorkflowTemplate{
+		Name: name,
+		UID:  nameUID,
+	}
+
+	return workflowTemplate, nil
+}
+
 // GetManifestBytes returns the manifest as []byte
 func (wt *WorkflowTemplate) GetManifestBytes() []byte {
 	return []byte(wt.Manifest)

pkg/workspace.go

@@ -350,6 +350,7 @@ func (c *Client) addRuntimeFieldsToWorkspaceTemplate(t wfv1.Template, workspace
 		env.PrependEnvVarToContainer(container, "ONEPANEL_FQDN", config["ONEPANEL_FQDN"])
 		env.PrependEnvVarToContainer(container, "ONEPANEL_DOMAIN", config["ONEPANEL_DOMAIN"])
 		env.PrependEnvVarToContainer(container, "ONEPANEL_PROVIDER", config["ONEPANEL_PROVIDER"])
+		env.PrependEnvVarToContainer(container, "ONEPANEL_SERVING_URL", "kfserving-models-web-app.kfserving-system.svc.cluster.local")
 		env.PrependEnvVarToContainer(container, "ONEPANEL_RESOURCE_NAMESPACE", "{{workflow.namespace}}")
 		env.PrependEnvVarToContainer(container, "ONEPANEL_RESOURCE_UID", "{{workflow.parameters.sys-uid}}")
 	}

pkg/workspace_template_types.go

@@ -51,6 +51,22 @@ func (wt *WorkspaceTemplate) GenerateUID(name string) error {
 	return nil
 }
 
+// CreateWorkspaceTemplate creates a new workspace template with the given name.
+// All fields that can be generated in memory without external requests are filled out, such as the UID.
+func CreateWorkspaceTemplate(name string) (*WorkspaceTemplate, error) {
+	nameUID, err := uid2.GenerateUID(name, 30)
+	if err != nil {
+		return nil, err
+	}
+
+	workspaceTemplate := &WorkspaceTemplate{
+		Name: name,
+		UID:  nameUID,
+	}
+
+	return workspaceTemplate, nil
+}
+
 // InjectRuntimeParameters will inject all runtime variables into the WorkflowTemplate's manifest.
 func (wt *WorkspaceTemplate) InjectRuntimeParameters(config SystemConfig) error {
 	if wt.WorkflowTemplate == nil {