Compare commits

...

96 Commits

Author SHA1 Message Date
Andrey Melnikov
c984ff34d5 Merge pull request #961 from Vafilor/feat/remove.community.restrictions
fix: remove namespace creation restriction
2021-10-28 16:12:59 -07:00
Andrey Melnikov
5283b7beb6 fix: add missing manifests and incorrect cvat_1.6.0 version name in metadata 2021-10-28 16:08:31 -07:00
Andrey Melnikov
2cddf4a88a fix: remove namespace creation restriction 2021-10-28 15:50:39 -07:00
Andrey Melnikov
dd3d7f6632 Merge pull request #960 from Vafilor/feat/new.cvat
feat: cvat 1.6.0 workspace migration
2021-10-28 14:47:57 -07:00
Andrey Melnikov
4d1aff5c5b fix: method comments 2021-10-28 14:45:55 -07:00
Andrey Melnikov
719613ecd4 feat: cvat 1.6.0 workspace migration 2021-10-28 14:44:29 -07:00
Andrey Melnikov
09b854a434 Merge pull request #959 from Vafilor/feat/create.namespace.stub
feat: stub out create namespace
2021-10-27 10:09:19 -07:00
Andrey Melnikov
493ca51682 fix: docs for CreateNamespace 2021-10-27 09:31:07 -07:00
Andrey Melnikov
6407c2a7b4 feat: add create namespace code 2021-10-27 09:24:28 -07:00
Andrey Melnikov
62896b2f52 fix: Deny create namespace permission in community edition 2021-10-26 15:47:13 -07:00
Andrey Melnikov
d934163fc8 fix: code formatting and docs 2021-10-26 15:37:21 -07:00
Andrey Melnikov
e991102d85 Merge pull request #958 from Vafilor/feat/cache.values
feat: cache artifactRepositoryType
2021-10-26 15:32:59 -07:00
Andrey Melnikov
467f7f71dd fix: add missing comment 2021-10-26 15:29:12 -07:00
Andrey Melnikov
f1c0f0d31e feat: stub out create namespace and add supporting methods from enterprise version 2021-10-26 15:26:23 -07:00
Andrey Melnikov
11fc055ee3 feat: cache artifactRepositoryType 2021-10-26 15:23:47 -07:00
Andrey Melnikov
d9c79370e9 Merge pull request #957 from Vafilor/feat/update.migrations
feat: updated go migration data to have metadata
2021-10-26 15:19:19 -07:00
Andrey Melnikov
98f78d453a feat: updated go migration data to have metadata to make it easier to get all of the information from one file 2021-10-26 15:14:43 -07:00
Andrey Melnikov
700b3bd512 Merge pull request #955 from Vafilor/feat/add.serving.variables
feat: add onepanel serving url to workspaces
2021-10-07 12:29:05 -07:00
Andrey Melnikov
3abdc54d3c feat: add onepanel serving url to workspaces 2021-10-07 12:24:01 -07:00
Rush Tehrani
f570a710ba Update README.md 2021-09-17 09:40:54 -07:00
Rush Tehrani
c922b708fc Merge pull request #953 from Vafilor/fix/workflow.volumes
fix: workflow volumes don't delete on failed workflow
2021-09-08 12:57:56 -07:00
Andrey Melnikov
fc9669d757 fix: add PodCompletion volume claim gc by default to workflows. This will clean up the volumes if the workflow fails 2021-09-08 12:47:23 -07:00
rushtehrani
8eeb90d3f1 update features image in README 2021-08-19 12:22:57 -07:00
rushtehrani
c25dfce84f Update features image 2021-08-18 11:09:48 -07:00
Andrey Melnikov
5705bfa47f Merge pull request #943 from Vafilor/feat/model.deployment
feat: Inference Service API
2021-08-12 10:58:15 -07:00
Andrey Melnikov
44a78effed feat: Create response for inference service now returns information about the status 2021-08-12 10:05:04 -07:00
Andrey Melnikov
a8985a7878 chore: codacy docs 2021-08-11 17:08:24 -07:00
Andrey Melnikov
69006309b4 feat: allow onepanel-access-token in addition to the onepanel-auth-token 2021-08-11 16:29:37 -07:00
Andrey Melnikov
22b3d984ec clean: simplify marshaling of InferenceService 2021-08-11 16:29:10 -07:00
Andrey Melnikov
4528927463 feat: updated endpoint to get the status to include predictor url 2021-08-11 11:40:18 -07:00
Andrey Melnikov
edf7a30f64 feat: support both resource requests and limits for InferenceService 2021-08-10 14:47:32 -07:00
Andrey Melnikov
51fb86e3fe feat: simplify API for model services and rename it to inferenceservice 2021-08-10 13:36:44 -07:00
Andrey Melnikov
d8e0e5c968 feat: add defaults for model deployment and add get status and delete endpoints 2021-08-10 09:54:17 -07:00
Andrey Melnikov
75719caec9 feat: model deployment API 2021-08-06 16:07:27 -07:00
Andrey Melnikov
147c937252 Merge pull request #940 from Vafilor/feat/full.node.resources
feat: add optional logic to capture the entire node
2021-08-03 09:01:52 -07:00
Andrey Melnikov
e0f3f81563 feat: add optional logic to capture the entire node 2021-08-02 16:43:12 -07:00
Andrey Melnikov
0021249464 Merge pull request #938 from Vafilor/feat/expose.minio
feat: separate files api and support presigned urls
2021-08-02 15:11:34 -07:00
Andrey Melnikov
7235951ec2 chore: codacy docs 2021-08-02 15:08:09 -07:00
Andrey Melnikov
f843074a3f chore: codacy - Url -> URL 2021-07-30 14:21:15 -07:00
Andrey Melnikov
8e6ef8d3eb feat: updated presigned url response to include the file size so client can decide if it can be displayed or not 2021-07-30 14:01:38 -07:00
Andrey Melnikov
d226028b33 feat: separate files from workflow and add endpoint to get pre-signed url 2021-07-30 12:52:50 -07:00
Andrey Melnikov
82585d1011 Merge pull request #936 from Vafilor/fix/wrong.namespace
fix: issue where wrong namespace was parsed in certain cases
2021-07-27 11:10:34 -07:00
Andrey Melnikov
193dbe156e fix: issue where wrong namespace was obtained from certain urls for workspaces/models 2021-07-27 11:05:26 -07:00
Rush Tehrani
5ebccbd811 Update summary and Argo link 2021-07-22 11:05:43 -07:00
Andrey Melnikov
023fb50046 Merge pull request #934 from Vafilor/fix/s3.files
fix: s3 not listing files in file browser
2021-07-20 13:18:13 -07:00
Andrey Melnikov
abd8d3cde0 Merge pull request #933 from Vafilor/feat/filesyncer.update.migrations
feat: added migrations to update filesyncer to version 1.0.0
2021-07-20 13:13:58 -07:00
Andrey Melnikov
64d6dde1aa Merge branch 'fix/s3.files' of github.com:Vafilor/core into fix/s3.files 2021-07-20 13:08:21 -07:00
Andrey Melnikov
d0d68470dd fix: issue where s3 storage would not list files (but would list folders) 2021-07-20 13:07:38 -07:00
Andrey Melnikov
6f8e3f56e7 chore: documenting migrations 2021-07-20 13:07:17 -07:00
Andrey Melnikov
2b47ad7092 fix: issue where s3 storage would not list files (but would list folders) 2021-07-20 13:01:14 -07:00
Andrey Melnikov
66e2418424 feat: added migrations to update filesyncer to version 1.0.0 2021-07-20 13:00:41 -07:00
Andrey Melnikov
5b6979302e Merge pull request #930 from Vafilor/feat/storage.pagination
feat: added pagination to listing files
2021-07-16 16:02:22 -07:00
Andrey Melnikov
afb98c295b feat: added pagination to listing files 2021-07-16 15:33:09 -07:00
Andrey Melnikov
1fb0d10b7c Merge pull request #925 from Vafilor/feat/service.availability
feat: check if kfserving is set up
2021-07-12 15:27:16 -07:00
Andrey Melnikov
c4438bfe0d feat: check if kfserving is set up 2021-07-12 12:46:11 -07:00
Rush Tehrani
8329706f22 Update README.md 2021-07-08 14:01:22 -07:00
Andrey Melnikov
09be35b2d6 fix: don't publish image on any md file changes or github workflow changes 2021-07-08 12:23:21 -07:00
Andrey Melnikov
e4d83903c7 fix: don't publish image on README changess 2021-07-08 12:15:19 -07:00
Rush Tehrani
69bc6e3df1 Update README.md 2021-07-08 12:04:47 -07:00
Andrey Melnikov
bfee6c2e34 Merge pull request #921 from Vafilor/feat/auth.updates
feat: auth updates
2021-05-25 11:53:37 -07:00
Andrey Melnikov
47e03d7e7c Merge pull request #922 from Vafilor/fix/in.cluster.api.url
fix: use in-cluster url for ONEPANEL_API_URL
2021-05-25 11:51:08 -07:00
Andrey Melnikov
bcf78b54a0 fix: no 400 response returned from bad token 2021-05-25 11:49:35 -07:00
Andrey Melnikov
96b8f522b3 fix: use in-cluster url for ONEPANEL_API_URL so workspaces can access it in-cluster 2021-05-21 15:41:26 -07:00
Andrey Melnikov
98766cdc41 feat: auth updates 2021-05-19 13:40:43 -07:00
Rush Tehrani
378850f591 Merge pull request #919 from rushtehrani/master
chore: Add feature highlights video
2021-04-28 17:52:52 -07:00
Rush Tehrani
e27361466f Update feature highlights video 2021-04-28 17:47:49 -07:00
Rush Tehrani
daabf17078 Update features overview video 2021-04-27 11:11:15 -07:00
Rush Tehrani
73385ad779 Update README.md 2021-04-27 11:05:55 -07:00
Andrey Melnikov
c92c848134 Merge pull request #912 from inohmonton99/feat/description
feat: add description for workflow templates
2021-04-19 12:44:12 -07:00
Andrey Melnikov
82424605f6 chore: version bump to 0.22.0 2021-04-19 12:41:22 -07:00
Andrey Melnikov
9f05ab150a Merge pull request #913 from Vafilor/feat/add.deep.learning.desktop
feat: added deep learning desktop workspace
2021-04-14 11:01:56 -07:00
Andrey Melnikov
81de77d88b feat: added description to deep learning workspace 2021-04-14 10:58:22 -07:00
Andrey Melnikov
ea47eaf49d feat: added deep learning desktop workspace 2021-04-14 10:22:24 -07:00
inohmonton99
42e99f0ac4 updated api to match correct settings with new feature 2021-04-10 00:44:53 +08:00
inohmonton99
ae702c474c removed unnecessary commits and description migration for workflow_templates db 2021-04-08 00:28:20 +08:00
inohmonton99
cfd63a3ef9 description feature wip 2021-04-06 04:34:47 +08:00
Andrey Melnikov
1b2d5623b4 Merge pull request #908 from Vafilor/fix/release.command.repo
fix: updated repo in generate release notes as the name has changed
2021-04-01 16:31:42 -07:00
Andrey Melnikov
86895a9dfe Update README.md 2021-04-01 14:44:37 -07:00
Andrey Melnikov
ec94a13cd9 fix: updated repo in generate release notes as the name has changed 2021-04-01 10:53:26 -07:00
Andrey Melnikov
22836c85e1 Merge pull request #907 from Vafilor/feat/pns.updates
fix: don't use port 80 for host port
2021-04-01 10:29:23 -07:00
Andrey Melnikov
a3ab4a86b0 fjx: don't use port 80 for host port so it doesn't take it 2021-04-01 09:08:36 -07:00
Andrey Melnikov
b6ef84a0aa Merge pull request #906 from Vafilor/feat/pns.updates
fix: wrong onepanel/dl version
2021-03-31 19:21:58 -07:00
Andrey Melnikov
9f513dda9b fix: wrong onepanel/dl version 2021-03-31 18:59:21 -07:00
Andrey Melnikov
1bb3e7506d Merge pull request #905 from Vafilor/feat/pns.updates
fix: bug with remove hyperparam tuning migration
2021-03-30 15:13:02 -07:00
Andrey Melnikov
0f19e4d618 fix: bug with remove hyperparam tuning migration 2021-03-30 14:02:08 -07:00
Rush Tehrani
6c251761f5 Merge pull request #904 from Vafilor/feat/pns.updates
feat: Update code to work better with PNS executor
2021-03-30 12:47:54 -07:00
Andrey Melnikov
2cad065778 chore: codacy fixes 2021-03-29 16:23:31 -07:00
Andrey Melnikov
2fe0a239c5 feat: remove hyperparameter tuning workflow if there are no workflow executions ran by it 2021-03-29 16:18:41 -07:00
Andrey Melnikov
8287e178b5 fix: wrong onepanel/dl version for updated jupyterlab template 2021-03-29 12:35:11 -07:00
Andrey Melnikov
b869f2eb22 Merge branch 'feat/pns.updates' of github.com:Vafilor/core into feat/pns.updates 2021-03-29 12:09:54 -07:00
Andrey Melnikov
c4893ed0d7 feat: updated migrations and updated code to better work with pns executor based on Long Nguyen's suggestions. 2021-03-29 12:08:38 -07:00
Andrey Melnikov
4882671b52 feat: updated migrations and updated code to better work with pns executor based on Long Nguyen's suggestions. 2021-03-29 12:03:12 -07:00
Andrey Melnikov
a2009de7b1 Merge pull request #903 from Vafilor/fix/contributing.commands
fix: bash missing character in contributing guide
2021-03-26 13:06:22 -07:00
Andrey Melnikov
75680ee621 Merge pull request #902 from Vafilor/fix/contributing.commands
fix: windows sections of contribution guide
2021-03-26 12:59:57 -07:00
Andrey Melnikov
948f61da13 Merge pull request #892 from lnguyen/master
fix: fixes stability issue with pns executor
2021-03-26 12:09:17 -07:00
Long Nguyen
50dd0b9264 fixes stability issue with pns executor 2021-03-05 10:20:50 -05:00
147 changed files with 16011 additions and 7002 deletions

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@@ -1,6 +1,10 @@
name: Publish dev docker image name: Publish dev docker image
on: on:
push: push:
paths-ignore:
- LICENSE
- ".github/**"
- "*.md"
branches: branches:
- master - master
jobs: jobs:

View File

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

View File

@@ -1,6 +1,6 @@
<img width="200px" src="img/logo.png"> <img width="200px" src="img/logo.png">
![build](https://img.shields.io/github/workflow/status/onepanelio/core/Publish%20dev%20docker%20image/master?color=01579b) ![build](https://img.shields.io/github/workflow/status/onepanelio/onepanel/Publish%20dev%20docker%20image/master?color=01579b)
![code](https://img.shields.io/codacy/grade/d060fc4d1ac64b85b78f85c691ead86a?color=01579b) ![code](https://img.shields.io/codacy/grade/d060fc4d1ac64b85b78f85c691ead86a?color=01579b)
[![release](https://img.shields.io/github/v/release/onepanelio/core?color=01579b)](https://github.com/onepanelio/core/releases) [![release](https://img.shields.io/github/v/release/onepanelio/core?color=01579b)](https://github.com/onepanelio/core/releases)
[![sdk](https://img.shields.io/pypi/v/onepanel-sdk?color=01579b&label=sdk)](https://pypi.org/project/onepanel-sdk/) [![sdk](https://img.shields.io/pypi/v/onepanel-sdk?color=01579b&label=sdk)](https://pypi.org/project/onepanel-sdk/)
@@ -10,9 +10,10 @@
[![lfai](https://img.shields.io/badge/link-LFAI-01579b)](https://landscape.lfai.foundation/?selected=onepanel) [![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) [![license](https://img.shields.io/github/license/onepanelio/core?color=01579b)](https://opensource.org/licenses/Apache-2.0)
The open and extensible integrated development environment (IDE) for computer vision with built-in modules for model building, automated labeling, data processing, model training, hyperparameter tuning and workflow orchestration. ## End-to-end computer vision platform
Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
<img width="100%" src="img/onepanel.gif"> https://user-images.githubusercontent.com/1211823/116489376-afc60000-a849-11eb-8e8b-b0c64c07c144.mp4
## Why Onepanel? ## Why Onepanel?
<img width="100%" src="img/features.png"> <img width="100%" src="img/features.png">
@@ -20,9 +21,6 @@ The open and extensible integrated development environment (IDE) for computer vi
## Quick start ## Quick start
See [quick start guide](https://docs.onepanel.ai/docs/getting-started/quickstart) to get started. 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 ## 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). 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).
@@ -36,12 +34,12 @@ See [contribution guide](https://docs.onepanel.ai/docs/getting-started/contribut
## Acknowledgments ## Acknowledgments
Onepanel seamlessly integrates the following open source projects under the hood: Onepanel seamlessly integrates the following open source projects under the hood:
[Argo](https://github.com/argoproj/argo) | [Couler](https://github.com/couler-proj/couler) | [CVAT](https://github.com/opencv/cvat) | [JupyterLab](https://github.com/jupyterlab/jupyterlab) | [NNI](https://github.com/microsoft/nni) [Argo](https://github.com/argoproj/argo-workflows) | [Couler](https://github.com/couler-proj/couler) | [CVAT](https://github.com/opencv/cvat) | [JupyterLab](https://github.com/jupyterlab/jupyterlab) | [NNI](https://github.com/microsoft/nni)
We are grateful for the support these communities provide and do our best to contribute back as much as possible. We are grateful for the support these communities provide and do our best to contribute back as much as possible.
## License ## License
Onepanel is licensed under [Apache 2.0](https://github.com/onepanelio/core/blob/master/LICENSE). Onepanel is licensed under [Apache 2.0](https://github.com/onepanelio/core/blob/master/LICENSE).
## For organizations ## Enterprise support
Visit our [website](https://www.onepanel.ai/) for more information on support options and enterprise solution. Need enterprise features and support? Visit our [website](https://www.onepanel.ai/) for more information.

View File

@@ -3,7 +3,7 @@
"info": { "info": {
"title": "Onepanel", "title": "Onepanel",
"description": "Onepanel API", "description": "Onepanel API",
"version": "0.19.0", "version": "1.0.2",
"contact": { "contact": {
"name": "Onepanel project", "name": "Onepanel project",
"url": "https://github.com/onepanelio/core" "url": "https://github.com/onepanelio/core"
@@ -22,6 +22,36 @@
"application/octet-stream" "application/octet-stream"
], ],
"paths": { "paths": {
"/apis/v1beta/service/{name}": {
"get": {
"operationId": "HasService",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"$ref": "#/definitions/HasServiceResponse"
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "name",
"in": "path",
"required": true,
"type": "string"
}
],
"tags": [
"ServiceService"
]
}
},
"/apis/v1beta/{namespace}/field/workflow_executions/{fieldName}": { "/apis/v1beta/{namespace}/field/workflow_executions/{fieldName}": {
"get": { "get": {
"operationId": "ListWorkflowExecutionsField", "operationId": "ListWorkflowExecutionsField",
@@ -647,6 +677,200 @@
] ]
} }
}, },
"/apis/v1beta1/{namespace}/files/list/{path}": {
"get": {
"operationId": "ListFiles",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"$ref": "#/definitions/ListFilesResponse"
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "namespace",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "path",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "page",
"in": "query",
"required": false,
"type": "integer",
"format": "int32"
},
{
"name": "perPage",
"in": "query",
"required": false,
"type": "integer",
"format": "int32"
}
],
"tags": [
"FileService"
]
}
},
"/apis/v1beta1/{namespace}/files/presigned-url/{key}": {
"get": {
"operationId": "GetObjectDownloadPresignedURL",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"$ref": "#/definitions/GetPresignedUrlResponse"
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "namespace",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "key",
"in": "path",
"required": true,
"type": "string"
}
],
"tags": [
"FileService"
]
}
},
"/apis/v1beta1/{namespace}/inferenceservice": {
"post": {
"operationId": "CreateInferenceService",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"$ref": "#/definitions/GetInferenceServiceResponse"
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "namespace",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "body",
"in": "body",
"required": true,
"schema": {
"$ref": "#/definitions/CreateInferenceServiceRequest"
}
}
],
"tags": [
"InferenceService"
]
}
},
"/apis/v1beta1/{namespace}/inferenceservice/{name}": {
"get": {
"operationId": "GetInferenceService",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"$ref": "#/definitions/GetInferenceServiceResponse"
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "namespace",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "name",
"in": "path",
"required": true,
"type": "string"
}
],
"tags": [
"InferenceService"
]
},
"delete": {
"operationId": "DeleteInferenceService",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"properties": {}
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "namespace",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "name",
"in": "path",
"required": true,
"type": "string"
}
],
"tags": [
"InferenceService"
]
}
},
"/apis/v1beta1/{namespace}/secrets": { "/apis/v1beta1/{namespace}/secrets": {
"get": { "get": {
"operationId": "ListSecrets", "operationId": "ListSecrets",
@@ -1245,48 +1469,6 @@
] ]
} }
}, },
"/apis/v1beta1/{namespace}/workflow_executions/{uid}/artifacts/{key}": {
"get": {
"operationId": "GetArtifact",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"$ref": "#/definitions/ArtifactResponse"
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "namespace",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "uid",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "key",
"in": "path",
"required": true,
"type": "string"
}
],
"tags": [
"WorkflowService"
]
}
},
"/apis/v1beta1/{namespace}/workflow_executions/{uid}/cron_start_statistics": { "/apis/v1beta1/{namespace}/workflow_executions/{uid}/cron_start_statistics": {
"post": { "post": {
"operationId": "CronStartWorkflowExecutionStatistic", "operationId": "CronStartWorkflowExecutionStatistic",
@@ -1331,48 +1513,6 @@
] ]
} }
}, },
"/apis/v1beta1/{namespace}/workflow_executions/{uid}/files/{path}": {
"get": {
"operationId": "ListFiles",
"responses": {
"200": {
"description": "A successful response.",
"schema": {
"$ref": "#/definitions/ListFilesResponse"
}
},
"default": {
"description": "An unexpected error response.",
"schema": {
"$ref": "#/definitions/google.rpc.Status"
}
}
},
"parameters": [
{
"name": "namespace",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "uid",
"in": "path",
"required": true,
"type": "string"
},
{
"name": "path",
"in": "path",
"required": true,
"type": "string"
}
],
"tags": [
"WorkflowService"
]
}
},
"/apis/v1beta1/{namespace}/workflow_executions/{uid}/metric": { "/apis/v1beta1/{namespace}/workflow_executions/{uid}/metric": {
"post": { "post": {
"operationId": "AddWorkflowExecutionMetrics", "operationId": "AddWorkflowExecutionMetrics",
@@ -3228,12 +3368,40 @@
} }
} }
}, },
"ArtifactResponse": { "Container": {
"type": "object", "type": "object",
"properties": { "properties": {
"data": { "image": {
"type": "string", "type": "string"
"format": "byte" },
"name": {
"type": "string"
},
"env": {
"type": "array",
"items": {
"$ref": "#/definitions/Env"
}
}
}
},
"CreateInferenceServiceRequest": {
"type": "object",
"properties": {
"namespace": {
"type": "string"
},
"name": {
"type": "string"
},
"defaultTransformerImage": {
"type": "string"
},
"predictor": {
"$ref": "#/definitions/InferenceServicePredictor"
},
"transformer": {
"$ref": "#/definitions/InferenceServiceTransformer"
} }
} }
}, },
@@ -3282,6 +3450,9 @@
"items": { "items": {
"$ref": "#/definitions/KeyValue" "$ref": "#/definitions/KeyValue"
} }
},
"captureNode": {
"type": "boolean"
} }
} }
}, },
@@ -3336,6 +3507,17 @@
} }
} }
}, },
"Env": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"value": {
"type": "string"
}
}
},
"File": { "File": {
"type": "object", "type": "object",
"properties": { "properties": {
@@ -3405,6 +3587,23 @@
} }
} }
}, },
"GetInferenceServiceResponse": {
"type": "object",
"properties": {
"ready": {
"type": "boolean"
},
"conditions": {
"type": "array",
"items": {
"$ref": "#/definitions/InferenceServiceCondition"
}
},
"predictUrl": {
"type": "string"
}
}
},
"GetLabelsResponse": { "GetLabelsResponse": {
"type": "object", "type": "object",
"properties": { "properties": {
@@ -3424,6 +3623,18 @@
} }
} }
}, },
"GetPresignedUrlResponse": {
"type": "object",
"properties": {
"url": {
"type": "string"
},
"size": {
"type": "string",
"format": "int64"
}
}
},
"GetWorkflowExecutionMetricsResponse": { "GetWorkflowExecutionMetricsResponse": {
"type": "object", "type": "object",
"properties": { "properties": {
@@ -3451,6 +3662,80 @@
} }
} }
}, },
"HasServiceResponse": {
"type": "object",
"properties": {
"hasService": {
"type": "boolean"
}
}
},
"InferenceServiceCondition": {
"type": "object",
"properties": {
"lastTransitionTime": {
"type": "string"
},
"status": {
"type": "string"
},
"type": {
"type": "string"
}
}
},
"InferenceServicePredictor": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"runtimeVersion": {
"type": "string"
},
"storageUri": {
"type": "string"
},
"nodeSelector": {
"type": "string"
},
"minCpu": {
"type": "string"
},
"minMemory": {
"type": "string"
},
"maxCpu": {
"type": "string"
},
"maxMemory": {
"type": "string"
}
}
},
"InferenceServiceTransformer": {
"type": "object",
"properties": {
"containers": {
"type": "array",
"items": {
"$ref": "#/definitions/Container"
}
},
"minCpu": {
"type": "string"
},
"minMemory": {
"type": "string"
},
"maxCpu": {
"type": "string"
},
"maxMemory": {
"type": "string"
}
}
},
"IsAuthorized": { "IsAuthorized": {
"type": "object", "type": "object",
"properties": { "properties": {
@@ -3556,6 +3841,22 @@
"ListFilesResponse": { "ListFilesResponse": {
"type": "object", "type": "object",
"properties": { "properties": {
"count": {
"type": "integer",
"format": "int32"
},
"totalCount": {
"type": "integer",
"format": "int32"
},
"page": {
"type": "integer",
"format": "int32"
},
"pages": {
"type": "integer",
"format": "int32"
},
"files": { "files": {
"type": "array", "type": "array",
"items": { "items": {
@@ -3883,6 +4184,9 @@
"properties": { "properties": {
"name": { "name": {
"type": "string" "type": "string"
},
"sourceName": {
"type": "string"
} }
} }
}, },
@@ -4195,6 +4499,9 @@
"items": { "items": {
"$ref": "#/definitions/Parameter" "$ref": "#/definitions/Parameter"
} }
},
"description": {
"type": "string"
} }
} }
}, },

580
api/gen/files.pb.go Normal file
View File

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

342
api/gen/files.pb.gw.go Normal file
View File

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

133
api/gen/files_grpc.pb.go Normal file
View File

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

View File

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

View File

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

View File

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

View File

@@ -220,7 +220,8 @@ type Namespace struct {
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields 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() { func (x *Namespace) Reset() {
@@ -262,6 +263,13 @@ func (x *Namespace) GetName() string {
return "" return ""
} }
func (x *Namespace) GetSourceName() string {
if x != nil {
return x.SourceName
}
return ""
}
var File_namespace_proto protoreflect.FileDescriptor var File_namespace_proto protoreflect.FileDescriptor
var file_namespace_proto_rawDesc = []byte{ var file_namespace_proto_rawDesc = []byte{
@@ -289,9 +297,11 @@ var file_namespace_proto_rawDesc = []byte{
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View File

@@ -136,6 +136,100 @@ func (x *GetServiceRequest) GetName() string {
return "" return ""
} }
type HasServiceRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
}
func (x *HasServiceRequest) Reset() {
*x = HasServiceRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_services_proto_msgTypes[2]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *HasServiceRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*HasServiceRequest) ProtoMessage() {}
func (x *HasServiceRequest) ProtoReflect() protoreflect.Message {
mi := &file_services_proto_msgTypes[2]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use HasServiceRequest.ProtoReflect.Descriptor instead.
func (*HasServiceRequest) Descriptor() ([]byte, []int) {
return file_services_proto_rawDescGZIP(), []int{2}
}
func (x *HasServiceRequest) GetName() string {
if x != nil {
return x.Name
}
return ""
}
type HasServiceResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
HasService bool `protobuf:"varint,1,opt,name=hasService,proto3" json:"hasService,omitempty"`
}
func (x *HasServiceResponse) Reset() {
*x = HasServiceResponse{}
if protoimpl.UnsafeEnabled {
mi := &file_services_proto_msgTypes[3]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *HasServiceResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*HasServiceResponse) ProtoMessage() {}
func (x *HasServiceResponse) ProtoReflect() protoreflect.Message {
mi := &file_services_proto_msgTypes[3]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use HasServiceResponse.ProtoReflect.Descriptor instead.
func (*HasServiceResponse) Descriptor() ([]byte, []int) {
return file_services_proto_rawDescGZIP(), []int{3}
}
func (x *HasServiceResponse) GetHasService() bool {
if x != nil {
return x.HasService
}
return false
}
type ListServicesRequest struct { type ListServicesRequest struct {
state protoimpl.MessageState state protoimpl.MessageState
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
@@ -149,7 +243,7 @@ type ListServicesRequest struct {
func (x *ListServicesRequest) Reset() { func (x *ListServicesRequest) Reset() {
*x = ListServicesRequest{} *x = ListServicesRequest{}
if protoimpl.UnsafeEnabled { if protoimpl.UnsafeEnabled {
mi := &file_services_proto_msgTypes[2] mi := &file_services_proto_msgTypes[4]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi) ms.StoreMessageInfo(mi)
} }
@@ -162,7 +256,7 @@ func (x *ListServicesRequest) String() string {
func (*ListServicesRequest) ProtoMessage() {} func (*ListServicesRequest) ProtoMessage() {}
func (x *ListServicesRequest) ProtoReflect() protoreflect.Message { func (x *ListServicesRequest) ProtoReflect() protoreflect.Message {
mi := &file_services_proto_msgTypes[2] mi := &file_services_proto_msgTypes[4]
if protoimpl.UnsafeEnabled && x != nil { if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil { if ms.LoadMessageInfo() == nil {
@@ -175,7 +269,7 @@ func (x *ListServicesRequest) ProtoReflect() protoreflect.Message {
// Deprecated: Use ListServicesRequest.ProtoReflect.Descriptor instead. // Deprecated: Use ListServicesRequest.ProtoReflect.Descriptor instead.
func (*ListServicesRequest) Descriptor() ([]byte, []int) { func (*ListServicesRequest) Descriptor() ([]byte, []int) {
return file_services_proto_rawDescGZIP(), []int{2} return file_services_proto_rawDescGZIP(), []int{4}
} }
func (x *ListServicesRequest) GetNamespace() string { func (x *ListServicesRequest) GetNamespace() string {
@@ -214,7 +308,7 @@ type ListServicesResponse struct {
func (x *ListServicesResponse) Reset() { func (x *ListServicesResponse) Reset() {
*x = ListServicesResponse{} *x = ListServicesResponse{}
if protoimpl.UnsafeEnabled { if protoimpl.UnsafeEnabled {
mi := &file_services_proto_msgTypes[3] mi := &file_services_proto_msgTypes[5]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi) ms.StoreMessageInfo(mi)
} }
@@ -227,7 +321,7 @@ func (x *ListServicesResponse) String() string {
func (*ListServicesResponse) ProtoMessage() {} func (*ListServicesResponse) ProtoMessage() {}
func (x *ListServicesResponse) ProtoReflect() protoreflect.Message { func (x *ListServicesResponse) ProtoReflect() protoreflect.Message {
mi := &file_services_proto_msgTypes[3] mi := &file_services_proto_msgTypes[5]
if protoimpl.UnsafeEnabled && x != nil { if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil { if ms.LoadMessageInfo() == nil {
@@ -240,7 +334,7 @@ func (x *ListServicesResponse) ProtoReflect() protoreflect.Message {
// Deprecated: Use ListServicesResponse.ProtoReflect.Descriptor instead. // Deprecated: Use ListServicesResponse.ProtoReflect.Descriptor instead.
func (*ListServicesResponse) Descriptor() ([]byte, []int) { func (*ListServicesResponse) Descriptor() ([]byte, []int) {
return file_services_proto_rawDescGZIP(), []int{3} return file_services_proto_rawDescGZIP(), []int{5}
} }
func (x *ListServicesResponse) GetCount() int32 { func (x *ListServicesResponse) GetCount() int32 {
@@ -291,41 +385,53 @@ var file_services_proto_rawDesc = []byte{
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} }
var ( var (
@@ -340,21 +446,25 @@ func file_services_proto_rawDescGZIP() []byte {
return file_services_proto_rawDescData return file_services_proto_rawDescData
} }
var file_services_proto_msgTypes = make([]protoimpl.MessageInfo, 4) var file_services_proto_msgTypes = make([]protoimpl.MessageInfo, 6)
var file_services_proto_goTypes = []interface{}{ var file_services_proto_goTypes = []interface{}{
(*Service)(nil), // 0: api.Service (*Service)(nil), // 0: api.Service
(*GetServiceRequest)(nil), // 1: api.GetServiceRequest (*GetServiceRequest)(nil), // 1: api.GetServiceRequest
(*ListServicesRequest)(nil), // 2: api.ListServicesRequest (*HasServiceRequest)(nil), // 2: api.HasServiceRequest
(*ListServicesResponse)(nil), // 3: api.ListServicesResponse (*HasServiceResponse)(nil), // 3: api.HasServiceResponse
(*ListServicesRequest)(nil), // 4: api.ListServicesRequest
(*ListServicesResponse)(nil), // 5: api.ListServicesResponse
} }
var file_services_proto_depIdxs = []int32{ var file_services_proto_depIdxs = []int32{
0, // 0: api.ListServicesResponse.services:type_name -> api.Service 0, // 0: api.ListServicesResponse.services:type_name -> api.Service
1, // 1: api.ServiceService.GetService:input_type -> api.GetServiceRequest 1, // 1: api.ServiceService.GetService:input_type -> api.GetServiceRequest
2, // 2: api.ServiceService.ListServices:input_type -> api.ListServicesRequest 4, // 2: api.ServiceService.ListServices:input_type -> api.ListServicesRequest
0, // 3: api.ServiceService.GetService:output_type -> api.Service 2, // 3: api.ServiceService.HasService:input_type -> api.HasServiceRequest
3, // 4: api.ServiceService.ListServices:output_type -> api.ListServicesResponse 0, // 4: api.ServiceService.GetService:output_type -> api.Service
3, // [3:5] is the sub-list for method output_type 5, // 5: api.ServiceService.ListServices:output_type -> api.ListServicesResponse
1, // [1:3] is the sub-list for method input_type 3, // 6: api.ServiceService.HasService:output_type -> api.HasServiceResponse
4, // [4:7] is the sub-list for method output_type
1, // [1:4] is the sub-list for method input_type
1, // [1:1] is the sub-list for extension type_name 1, // [1:1] is the sub-list for extension type_name
1, // [1:1] is the sub-list for extension extendee 1, // [1:1] is the sub-list for extension extendee
0, // [0:1] is the sub-list for field type_name 0, // [0:1] is the sub-list for field type_name
@@ -391,7 +501,7 @@ func file_services_proto_init() {
} }
} }
file_services_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { file_services_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*ListServicesRequest); i { switch v := v.(*HasServiceRequest); i {
case 0: case 0:
return &v.state return &v.state
case 1: case 1:
@@ -403,6 +513,30 @@ func file_services_proto_init() {
} }
} }
file_services_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} { file_services_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*HasServiceResponse); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_services_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*ListServicesRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_services_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*ListServicesResponse); i { switch v := v.(*ListServicesResponse); i {
case 0: case 0:
return &v.state return &v.state
@@ -421,7 +555,7 @@ func file_services_proto_init() {
GoPackagePath: reflect.TypeOf(x{}).PkgPath(), GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
RawDescriptor: file_services_proto_rawDesc, RawDescriptor: file_services_proto_rawDesc,
NumEnums: 0, NumEnums: 0,
NumMessages: 4, NumMessages: 6,
NumExtensions: 0, NumExtensions: 0,
NumServices: 1, NumServices: 1,
}, },

View File

@@ -173,6 +173,58 @@ func local_request_ServiceService_ListServices_0(ctx context.Context, marshaler
} }
func request_ServiceService_HasService_0(ctx context.Context, marshaler runtime.Marshaler, client ServiceServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
var protoReq HasServiceRequest
var metadata runtime.ServerMetadata
var (
val string
ok bool
err error
_ = err
)
val, ok = pathParams["name"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "name")
}
protoReq.Name, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "name", err)
}
msg, err := client.HasService(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
return msg, metadata, err
}
func local_request_ServiceService_HasService_0(ctx context.Context, marshaler runtime.Marshaler, server ServiceServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
var protoReq HasServiceRequest
var metadata runtime.ServerMetadata
var (
val string
ok bool
err error
_ = err
)
val, ok = pathParams["name"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "name")
}
protoReq.Name, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "name", err)
}
msg, err := server.HasService(ctx, &protoReq)
return msg, metadata, err
}
// RegisterServiceServiceHandlerServer registers the http handlers for service ServiceService to "mux". // RegisterServiceServiceHandlerServer registers the http handlers for service ServiceService to "mux".
// UnaryRPC :call ServiceServiceServer directly. // UnaryRPC :call ServiceServiceServer directly.
// StreamingRPC :currently unsupported pending https://github.com/grpc/grpc-go/issues/906. // StreamingRPC :currently unsupported pending https://github.com/grpc/grpc-go/issues/906.
@@ -225,6 +277,29 @@ func RegisterServiceServiceHandlerServer(ctx context.Context, mux *runtime.Serve
}) })
mux.Handle("GET", pattern_ServiceService_HasService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context())
defer cancel()
var stream runtime.ServerTransportStream
ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.ServiceService/HasService")
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
resp, md, err := local_request_ServiceService_HasService_0(rctx, inboundMarshaler, server, req, pathParams)
md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
ctx = runtime.NewServerMetadataContext(ctx, md)
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
forward_ServiceService_HasService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
})
return nil return nil
} }
@@ -306,6 +381,26 @@ func RegisterServiceServiceHandlerClient(ctx context.Context, mux *runtime.Serve
}) })
mux.Handle("GET", pattern_ServiceService_HasService_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context())
defer cancel()
inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.ServiceService/HasService")
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
resp, md, err := request_ServiceService_HasService_0(rctx, inboundMarshaler, client, req, pathParams)
ctx = runtime.NewServerMetadataContext(ctx, md)
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
forward_ServiceService_HasService_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
})
return nil return nil
} }
@@ -313,10 +408,14 @@ var (
pattern_ServiceService_GetService_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4}, []string{"apis", "v1beta1", "namespace", "service", "name"}, "")) pattern_ServiceService_GetService_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4}, []string{"apis", "v1beta1", "namespace", "service", "name"}, ""))
pattern_ServiceService_ListServices_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3}, []string{"apis", "v1beta1", "namespace", "service"}, "")) pattern_ServiceService_ListServices_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3}, []string{"apis", "v1beta1", "namespace", "service"}, ""))
pattern_ServiceService_HasService_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 2, 2, 1, 0, 4, 1, 5, 3}, []string{"apis", "v1beta", "service", "name"}, ""))
) )
var ( var (
forward_ServiceService_GetService_0 = runtime.ForwardResponseMessage forward_ServiceService_GetService_0 = runtime.ForwardResponseMessage
forward_ServiceService_ListServices_0 = runtime.ForwardResponseMessage forward_ServiceService_ListServices_0 = runtime.ForwardResponseMessage
forward_ServiceService_HasService_0 = runtime.ForwardResponseMessage
) )

View File

@@ -19,6 +19,7 @@ const _ = grpc.SupportPackageIsVersion7
type ServiceServiceClient interface { type ServiceServiceClient interface {
GetService(ctx context.Context, in *GetServiceRequest, opts ...grpc.CallOption) (*Service, error) GetService(ctx context.Context, in *GetServiceRequest, opts ...grpc.CallOption) (*Service, error)
ListServices(ctx context.Context, in *ListServicesRequest, opts ...grpc.CallOption) (*ListServicesResponse, error) ListServices(ctx context.Context, in *ListServicesRequest, opts ...grpc.CallOption) (*ListServicesResponse, error)
HasService(ctx context.Context, in *HasServiceRequest, opts ...grpc.CallOption) (*HasServiceResponse, error)
} }
type serviceServiceClient struct { type serviceServiceClient struct {
@@ -47,12 +48,22 @@ func (c *serviceServiceClient) ListServices(ctx context.Context, in *ListService
return out, nil return out, nil
} }
func (c *serviceServiceClient) HasService(ctx context.Context, in *HasServiceRequest, opts ...grpc.CallOption) (*HasServiceResponse, error) {
out := new(HasServiceResponse)
err := c.cc.Invoke(ctx, "/api.ServiceService/HasService", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
// ServiceServiceServer is the server API for ServiceService service. // ServiceServiceServer is the server API for ServiceService service.
// All implementations must embed UnimplementedServiceServiceServer // All implementations must embed UnimplementedServiceServiceServer
// for forward compatibility // for forward compatibility
type ServiceServiceServer interface { type ServiceServiceServer interface {
GetService(context.Context, *GetServiceRequest) (*Service, error) GetService(context.Context, *GetServiceRequest) (*Service, error)
ListServices(context.Context, *ListServicesRequest) (*ListServicesResponse, error) ListServices(context.Context, *ListServicesRequest) (*ListServicesResponse, error)
HasService(context.Context, *HasServiceRequest) (*HasServiceResponse, error)
mustEmbedUnimplementedServiceServiceServer() mustEmbedUnimplementedServiceServiceServer()
} }
@@ -66,6 +77,9 @@ func (UnimplementedServiceServiceServer) GetService(context.Context, *GetService
func (UnimplementedServiceServiceServer) ListServices(context.Context, *ListServicesRequest) (*ListServicesResponse, error) { func (UnimplementedServiceServiceServer) ListServices(context.Context, *ListServicesRequest) (*ListServicesResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method ListServices not implemented") return nil, status.Errorf(codes.Unimplemented, "method ListServices not implemented")
} }
func (UnimplementedServiceServiceServer) HasService(context.Context, *HasServiceRequest) (*HasServiceResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method HasService not implemented")
}
func (UnimplementedServiceServiceServer) mustEmbedUnimplementedServiceServiceServer() {} func (UnimplementedServiceServiceServer) mustEmbedUnimplementedServiceServiceServer() {}
// UnsafeServiceServiceServer may be embedded to opt out of forward compatibility for this service. // UnsafeServiceServiceServer may be embedded to opt out of forward compatibility for this service.
@@ -115,6 +129,24 @@ func _ServiceService_ListServices_Handler(srv interface{}, ctx context.Context,
return interceptor(ctx, in, info, handler) return interceptor(ctx, in, info, handler)
} }
func _ServiceService_HasService_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(HasServiceRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(ServiceServiceServer).HasService(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/api.ServiceService/HasService",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(ServiceServiceServer).HasService(ctx, req.(*HasServiceRequest))
}
return interceptor(ctx, in, info, handler)
}
var _ServiceService_serviceDesc = grpc.ServiceDesc{ var _ServiceService_serviceDesc = grpc.ServiceDesc{
ServiceName: "api.ServiceService", ServiceName: "api.ServiceService",
HandlerType: (*ServiceServiceServer)(nil), HandlerType: (*ServiceServiceServer)(nil),
@@ -127,6 +159,10 @@ var _ServiceService_serviceDesc = grpc.ServiceDesc{
MethodName: "ListServices", MethodName: "ListServices",
Handler: _ServiceService_ListServices_Handler, Handler: _ServiceService_ListServices_Handler,
}, },
{
MethodName: "HasService",
Handler: _ServiceService_HasService_Handler,
},
}, },
Streams: []grpc.StreamDesc{}, Streams: []grpc.StreamDesc{},
Metadata: "services.proto", Metadata: "services.proto",

File diff suppressed because it is too large Load Diff

View File

@@ -709,190 +709,6 @@ func local_request_WorkflowService_TerminateWorkflowExecution_0(ctx context.Cont
} }
func request_WorkflowService_GetArtifact_0(ctx context.Context, marshaler runtime.Marshaler, client WorkflowServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
var protoReq GetArtifactRequest
var metadata runtime.ServerMetadata
var (
val string
ok bool
err error
_ = err
)
val, ok = pathParams["namespace"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
}
protoReq.Namespace, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
}
val, ok = pathParams["uid"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
}
protoReq.Uid, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
}
val, ok = pathParams["key"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "key")
}
protoReq.Key, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "key", err)
}
msg, err := client.GetArtifact(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
return msg, metadata, err
}
func local_request_WorkflowService_GetArtifact_0(ctx context.Context, marshaler runtime.Marshaler, server WorkflowServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
var protoReq GetArtifactRequest
var metadata runtime.ServerMetadata
var (
val string
ok bool
err error
_ = err
)
val, ok = pathParams["namespace"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
}
protoReq.Namespace, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
}
val, ok = pathParams["uid"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
}
protoReq.Uid, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
}
val, ok = pathParams["key"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "key")
}
protoReq.Key, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "key", err)
}
msg, err := server.GetArtifact(ctx, &protoReq)
return msg, metadata, err
}
func request_WorkflowService_ListFiles_0(ctx context.Context, marshaler runtime.Marshaler, client WorkflowServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
var protoReq ListFilesRequest
var metadata runtime.ServerMetadata
var (
val string
ok bool
err error
_ = err
)
val, ok = pathParams["namespace"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
}
protoReq.Namespace, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
}
val, ok = pathParams["uid"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
}
protoReq.Uid, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
}
val, ok = pathParams["path"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "path")
}
protoReq.Path, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "path", err)
}
msg, err := client.ListFiles(ctx, &protoReq, grpc.Header(&metadata.HeaderMD), grpc.Trailer(&metadata.TrailerMD))
return msg, metadata, err
}
func local_request_WorkflowService_ListFiles_0(ctx context.Context, marshaler runtime.Marshaler, server WorkflowServiceServer, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
var protoReq ListFilesRequest
var metadata runtime.ServerMetadata
var (
val string
ok bool
err error
_ = err
)
val, ok = pathParams["namespace"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "namespace")
}
protoReq.Namespace, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "namespace", err)
}
val, ok = pathParams["uid"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "uid")
}
protoReq.Uid, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "uid", err)
}
val, ok = pathParams["path"]
if !ok {
return nil, metadata, status.Errorf(codes.InvalidArgument, "missing parameter %s", "path")
}
protoReq.Path, err = runtime.String(val)
if err != nil {
return nil, metadata, status.Errorf(codes.InvalidArgument, "type mismatch, parameter: %s, error: %v", "path", err)
}
msg, err := server.ListFiles(ctx, &protoReq)
return msg, metadata, err
}
func request_WorkflowService_AddWorkflowExecutionStatistics_0(ctx context.Context, marshaler runtime.Marshaler, client WorkflowServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) { func request_WorkflowService_AddWorkflowExecutionStatistics_0(ctx context.Context, marshaler runtime.Marshaler, client WorkflowServiceClient, req *http.Request, pathParams map[string]string) (proto.Message, runtime.ServerMetadata, error) {
var protoReq AddWorkflowExecutionStatisticRequest var protoReq AddWorkflowExecutionStatisticRequest
var metadata runtime.ServerMetadata var metadata runtime.ServerMetadata
@@ -1609,52 +1425,6 @@ func RegisterWorkflowServiceHandlerServer(ctx context.Context, mux *runtime.Serv
}) })
mux.Handle("GET", pattern_WorkflowService_GetArtifact_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context())
defer cancel()
var stream runtime.ServerTransportStream
ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.WorkflowService/GetArtifact")
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
resp, md, err := local_request_WorkflowService_GetArtifact_0(rctx, inboundMarshaler, server, req, pathParams)
md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
ctx = runtime.NewServerMetadataContext(ctx, md)
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
forward_WorkflowService_GetArtifact_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
})
mux.Handle("GET", pattern_WorkflowService_ListFiles_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context())
defer cancel()
var stream runtime.ServerTransportStream
ctx = grpc.NewContextWithServerTransportStream(ctx, &stream)
inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
rctx, err := runtime.AnnotateIncomingContext(ctx, mux, req, "/api.WorkflowService/ListFiles")
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
resp, md, err := local_request_WorkflowService_ListFiles_0(rctx, inboundMarshaler, server, req, pathParams)
md.HeaderMD, md.TrailerMD = metadata.Join(md.HeaderMD, stream.Header()), metadata.Join(md.TrailerMD, stream.Trailer())
ctx = runtime.NewServerMetadataContext(ctx, md)
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
forward_WorkflowService_ListFiles_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
})
mux.Handle("POST", pattern_WorkflowService_AddWorkflowExecutionStatistics_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) { mux.Handle("POST", pattern_WorkflowService_AddWorkflowExecutionStatistics_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context()) ctx, cancel := context.WithCancel(req.Context())
defer cancel() defer cancel()
@@ -2034,46 +1804,6 @@ func RegisterWorkflowServiceHandlerClient(ctx context.Context, mux *runtime.Serv
}) })
mux.Handle("GET", pattern_WorkflowService_GetArtifact_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context())
defer cancel()
inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.WorkflowService/GetArtifact")
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
resp, md, err := request_WorkflowService_GetArtifact_0(rctx, inboundMarshaler, client, req, pathParams)
ctx = runtime.NewServerMetadataContext(ctx, md)
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
forward_WorkflowService_GetArtifact_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
})
mux.Handle("GET", pattern_WorkflowService_ListFiles_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context())
defer cancel()
inboundMarshaler, outboundMarshaler := runtime.MarshalerForRequest(mux, req)
rctx, err := runtime.AnnotateContext(ctx, mux, req, "/api.WorkflowService/ListFiles")
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
resp, md, err := request_WorkflowService_ListFiles_0(rctx, inboundMarshaler, client, req, pathParams)
ctx = runtime.NewServerMetadataContext(ctx, md)
if err != nil {
runtime.HTTPError(ctx, mux, outboundMarshaler, w, req, err)
return
}
forward_WorkflowService_ListFiles_0(ctx, mux, outboundMarshaler, w, req, resp, mux.GetForwardResponseOptions()...)
})
mux.Handle("POST", pattern_WorkflowService_AddWorkflowExecutionStatistics_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) { mux.Handle("POST", pattern_WorkflowService_AddWorkflowExecutionStatistics_0, func(w http.ResponseWriter, req *http.Request, pathParams map[string]string) {
ctx, cancel := context.WithCancel(req.Context()) ctx, cancel := context.WithCancel(req.Context())
defer cancel() defer cancel()
@@ -2218,10 +1948,6 @@ var (
pattern_WorkflowService_TerminateWorkflowExecution_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "terminate"}, "")) pattern_WorkflowService_TerminateWorkflowExecution_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "terminate"}, ""))
pattern_WorkflowService_GetArtifact_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5, 3, 0, 4, 1, 5, 6}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "artifacts", "key"}, ""))
pattern_WorkflowService_ListFiles_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5, 3, 0, 4, 1, 5, 6}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "files", "path"}, ""))
pattern_WorkflowService_AddWorkflowExecutionStatistics_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "statistics"}, "")) pattern_WorkflowService_AddWorkflowExecutionStatistics_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "statistics"}, ""))
pattern_WorkflowService_CronStartWorkflowExecutionStatistic_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "cron_start_statistics"}, "")) pattern_WorkflowService_CronStartWorkflowExecutionStatistic_0 = runtime.MustPattern(runtime.NewPattern(1, []int{2, 0, 2, 1, 1, 0, 4, 1, 5, 2, 2, 3, 1, 0, 4, 1, 5, 4, 2, 5}, []string{"apis", "v1beta1", "namespace", "workflow_executions", "uid", "cron_start_statistics"}, ""))
@@ -2256,10 +1982,6 @@ var (
forward_WorkflowService_TerminateWorkflowExecution_0 = runtime.ForwardResponseMessage forward_WorkflowService_TerminateWorkflowExecution_0 = runtime.ForwardResponseMessage
forward_WorkflowService_GetArtifact_0 = runtime.ForwardResponseMessage
forward_WorkflowService_ListFiles_0 = runtime.ForwardResponseMessage
forward_WorkflowService_AddWorkflowExecutionStatistics_0 = runtime.ForwardResponseMessage forward_WorkflowService_AddWorkflowExecutionStatistics_0 = runtime.ForwardResponseMessage
forward_WorkflowService_CronStartWorkflowExecutionStatistic_0 = runtime.ForwardResponseMessage forward_WorkflowService_CronStartWorkflowExecutionStatistic_0 = runtime.ForwardResponseMessage

View File

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

View File

@@ -842,19 +842,20 @@ type WorkflowTemplate struct {
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields unknownFields protoimpl.UnknownFields
CreatedAt string `protobuf:"bytes,1,opt,name=createdAt,proto3" json:"createdAt,omitempty"` CreatedAt string `protobuf:"bytes,1,opt,name=createdAt,proto3" json:"createdAt,omitempty"`
ModifiedAt string `protobuf:"bytes,2,opt,name=modifiedAt,proto3" json:"modifiedAt,omitempty"` ModifiedAt string `protobuf:"bytes,2,opt,name=modifiedAt,proto3" json:"modifiedAt,omitempty"`
Uid string `protobuf:"bytes,3,opt,name=uid,proto3" json:"uid,omitempty"` Uid string `protobuf:"bytes,3,opt,name=uid,proto3" json:"uid,omitempty"`
Name string `protobuf:"bytes,4,opt,name=name,proto3" json:"name,omitempty"` Name string `protobuf:"bytes,4,opt,name=name,proto3" json:"name,omitempty"`
Version int64 `protobuf:"varint,5,opt,name=version,proto3" json:"version,omitempty"` Version int64 `protobuf:"varint,5,opt,name=version,proto3" json:"version,omitempty"`
Versions int64 `protobuf:"varint,6,opt,name=versions,proto3" json:"versions,omitempty"` Versions int64 `protobuf:"varint,6,opt,name=versions,proto3" json:"versions,omitempty"`
Manifest string `protobuf:"bytes,7,opt,name=manifest,proto3" json:"manifest,omitempty"` Manifest string `protobuf:"bytes,7,opt,name=manifest,proto3" json:"manifest,omitempty"`
IsLatest bool `protobuf:"varint,8,opt,name=isLatest,proto3" json:"isLatest,omitempty"` IsLatest bool `protobuf:"varint,8,opt,name=isLatest,proto3" json:"isLatest,omitempty"`
IsArchived bool `protobuf:"varint,9,opt,name=isArchived,proto3" json:"isArchived,omitempty"` IsArchived bool `protobuf:"varint,9,opt,name=isArchived,proto3" json:"isArchived,omitempty"`
Labels []*KeyValue `protobuf:"bytes,10,rep,name=labels,proto3" json:"labels,omitempty"` Labels []*KeyValue `protobuf:"bytes,10,rep,name=labels,proto3" json:"labels,omitempty"`
Stats *WorkflowExecutionStatisticReport `protobuf:"bytes,11,opt,name=stats,proto3" json:"stats,omitempty"` Stats *WorkflowExecutionStatisticReport `protobuf:"bytes,11,opt,name=stats,proto3" json:"stats,omitempty"`
CronStats *CronWorkflowStatisticsReport `protobuf:"bytes,12,opt,name=cronStats,proto3" json:"cronStats,omitempty"` CronStats *CronWorkflowStatisticsReport `protobuf:"bytes,12,opt,name=cronStats,proto3" json:"cronStats,omitempty"`
Parameters []*Parameter `protobuf:"bytes,13,rep,name=parameters,proto3" json:"parameters,omitempty"` Parameters []*Parameter `protobuf:"bytes,13,rep,name=parameters,proto3" json:"parameters,omitempty"`
Description string `protobuf:"bytes,14,opt,name=description,proto3" json:"description,omitempty"`
} }
func (x *WorkflowTemplate) Reset() { func (x *WorkflowTemplate) Reset() {
@@ -980,6 +981,13 @@ func (x *WorkflowTemplate) GetParameters() []*Parameter {
return nil return nil
} }
func (x *WorkflowTemplate) GetDescription() string {
if x != nil {
return x.Description
}
return ""
}
type GetWorkflowTemplateLabelsRequest struct { type GetWorkflowTemplateLabelsRequest struct {
state protoimpl.MessageState state protoimpl.MessageState
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
@@ -1267,7 +1275,7 @@ var file_workflow_template_proto_rawDesc = []byte{
0x74, 0x65, 0x64, 0x22, 0x34, 0x0a, 0x1c, 0x43, 0x72, 0x6f, 0x6e, 0x57, 0x6f, 0x72, 0x6b, 0x66, 0x74, 0x65, 0x64, 0x22, 0x34, 0x0a, 0x1c, 0x43, 0x72, 0x6f, 0x6e, 0x57, 0x6f, 0x72, 0x6b, 0x66,
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} }
var ( var (

View File

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

56
api/proto/files.proto Normal file
View File

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

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

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

View File

@@ -17,6 +17,12 @@ service ServiceService {
get: "/apis/v1beta1/{namespace}/service" get: "/apis/v1beta1/{namespace}/service"
}; };
} }
rpc HasService(HasServiceRequest) returns (HasServiceResponse) {
option (google.api.http) = {
get: "/apis/v1beta/service/{name}"
};
}
} }
message Service { message Service {
@@ -29,6 +35,14 @@ message GetServiceRequest {
string name = 2; string name = 2;
} }
message HasServiceRequest {
string name = 1;
}
message HasServiceResponse {
bool hasService= 1;
}
message ListServicesRequest { message ListServicesRequest {
string namespace = 1; string namespace = 1;
int32 pageSize = 2; int32 pageSize = 2;

View File

@@ -74,18 +74,6 @@ service WorkflowService {
}; };
} }
rpc GetArtifact (GetArtifactRequest) returns (ArtifactResponse) {
option (google.api.http) = {
get: "/apis/v1beta1/{namespace}/workflow_executions/{uid}/artifacts/{key=**}"
};
}
rpc ListFiles (ListFilesRequest) returns (ListFilesResponse) {
option (google.api.http) = {
get: "/apis/v1beta1/{namespace}/workflow_executions/{uid}/files/{path=**}"
};
}
rpc AddWorkflowExecutionStatistics (AddWorkflowExecutionStatisticRequest) returns (google.protobuf.Empty) { rpc AddWorkflowExecutionStatistics (AddWorkflowExecutionStatisticRequest) returns (google.protobuf.Empty) {
option (google.api.http) = { option (google.api.http) = {
post: "/apis/v1beta1/{namespace}/workflow_executions/{uid}/statistics" post: "/apis/v1beta1/{namespace}/workflow_executions/{uid}/statistics"
@@ -235,31 +223,6 @@ message WorkflowExecution {
repeated Metric metrics = 12; repeated Metric metrics = 12;
} }
message ArtifactResponse {
bytes data = 1;
}
message File {
string path = 1;
string name = 2;
string extension = 3;
int64 size = 4;
string contentType = 5;
string lastModified = 6;
bool directory = 7;
}
message ListFilesRequest {
string namespace = 1;
string uid = 2;
string path = 3;
}
message ListFilesResponse {
repeated File files = 1;
string parentPath = 2;
}
message Statistics { message Statistics {
string workflowStatus = 1; string workflowStatus = 1;
int64 workflowTemplateId = 2; int64 workflowTemplateId = 2;

View File

@@ -166,6 +166,7 @@ message WorkflowTemplate {
WorkflowExecutionStatisticReport stats = 11; WorkflowExecutionStatisticReport stats = 11;
CronWorkflowStatisticsReport cronStats = 12; CronWorkflowStatisticsReport cronStats = 12;
repeated Parameter parameters = 13; repeated Parameter parameters = 13;
string description = 14;
} }
message GetWorkflowTemplateLabelsRequest { message GetWorkflowTemplateLabelsRequest {

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

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@@ -52,7 +52,7 @@ See https://docs.onepanel.ai
` + "```" + ` ` + "```" + `
# Download the binary # Download the binary
curl -sLO https://github.com/onepanelio/core/releases/download/v%s/opctl-linux-amd64 curl -sLO https://github.com/onepanelio/onepanel/releases/download/v%s/opctl-linux-amd64
# Make binary executable # Make binary executable
chmod +x opctl-linux-amd64 chmod +x opctl-linux-amd64
@@ -68,7 +68,7 @@ opctl version
` + "```" + ` ` + "```" + `
# Download the binary # Download the binary
curl -sLO https://github.com/onepanelio/core/releases/download/v%s/opctl-macos-amd64 curl -sLO https://github.com/onepanelio/onepanel/releases/download/v%s/opctl-macos-amd64
# Make binary executable # Make binary executable
chmod +x opctl-macos-amd64 chmod +x opctl-macos-amd64
@@ -82,7 +82,7 @@ opctl version
## Windows ## Windows
Download the [attached executable](https://github.com/onepanelio/core/releases/download/v%s/opctl-windows-amd64.exe), rename it to "opctl" and move it to a folder that is in your PATH environment variable. Download the [attached executable](https://github.com/onepanelio/onepanel/releases/download/v%s/opctl-windows-amd64.exe), rename it to "opctl" and move it to a folder that is in your PATH environment variable.
` `
var repositories = []string{ var repositories = []string{

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@@ -0,0 +1,58 @@
package migration
import (
"database/sql"
"github.com/pressly/goose"
"path/filepath"
)
func initialize20210323175655() {
if _, ok := initializedMigrations[20210323175655]; !ok {
goose.AddMigration(Up20210323175655, Down20210323175655)
initializedMigrations[20210323175655] = true
}
}
// Up20210323175655 update workflows to support new PNS mode
func Up20210323175655(tx *sql.Tx) error {
// This code is executed when the migration is applied.
if err := updateWorkflowTemplateManifest(
filepath.Join("workflows", "pytorch-mnist-training", "20210323175655.yaml"),
pytorchWorkflowTemplateName,
map[string]string{
"created-by": "system",
"framework": "pytorch",
}); err != nil {
return err
}
return updateWorkflowTemplateManifest(
filepath.Join("workflows", "tensorflow-mnist-training", "20210323175655.yaml"),
tensorflowWorkflowTemplateName,
map[string]string{
"created-by": "system",
"framework": "tensorflow",
})
}
// Down20210323175655 reverts updating workflows to support PNS
func Down20210323175655(tx *sql.Tx) error {
// This code is executed when the migration is rolled back.
if err := updateWorkflowTemplateManifest(
filepath.Join("workflows", "tensorflow-mnist-training", "20210118175809.yaml"),
tensorflowWorkflowTemplateName,
map[string]string{
"created-by": "system",
"framework": "tensorflow",
}); err != nil {
return err
}
return updateWorkflowTemplateManifest(
filepath.Join("workflows", "pytorch-mnist-training", "20210118175809.yaml"),
pytorchWorkflowTemplateName,
map[string]string{
"created-by": "system",
"framework": "pytorch",
})
}

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@@ -0,0 +1,55 @@
package migration
import (
"database/sql"
"github.com/pressly/goose"
"path/filepath"
)
func initialize20210329171739() {
if _, ok := initializedMigrations[20210329171739]; !ok {
goose.AddMigration(Up20210329171739, Down20210329171739)
initializedMigrations[20210329171739] = true
}
}
// Up20210329171739 updates workspaces to use new images
func Up20210329171739(tx *sql.Tx) error {
// This code is executed when the migration is applied.
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "cvat", "20210323175655.yaml"),
cvatTemplateName); err != nil {
return err
}
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "jupyterlab", "20210323175655.yaml"),
jupyterLabTemplateName); err != nil {
return err
}
return updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "vscode", "20210323175655.yaml"),
vscodeWorkspaceTemplateName)
}
// Down20210329171739 rolls back image updates for workspaces
func Down20210329171739(tx *sql.Tx) error {
// This code is executed when the migration is rolled back.
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "cvat", "20210224180017.yaml"),
cvatTemplateName); err != nil {
return err
}
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "jupyterlab", "20210224180017.yaml"),
jupyterLabTemplateName); err != nil {
return err
}
return updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "vscode", "20210224180017.yaml"),
vscodeWorkspaceTemplateName)
}

View File

@@ -0,0 +1,109 @@
package migration
import (
"database/sql"
uid2 "github.com/onepanelio/core/pkg/util/uid"
"github.com/pressly/goose"
"path/filepath"
)
func initialize20210329194731() {
if _, ok := initializedMigrations[20210329194731]; !ok {
goose.AddMigration(Up20210329194731, Down20210329194731)
initializedMigrations[20210329194731] = true
}
}
// Up20210329194731 removes the hyperparameter-tuning workflow if there are no executions
func Up20210329194731(tx *sql.Tx) error {
// This code is executed when the migration is applied.
client, err := getClient()
if err != nil {
return err
}
defer client.DB.Close()
namespaces, err := client.ListOnepanelEnabledNamespaces()
if err != nil {
return err
}
uid, err := uid2.GenerateUID(hyperparameterTuningTemplateName, 30)
if err != nil {
return err
}
for _, namespace := range namespaces {
workflowTemplate, err := client.GetWorkflowTemplateRaw(namespace.Name, uid)
if err != nil {
return err
}
if workflowTemplate == nil {
continue
}
workflowExecutionsCount, err := client.CountWorkflowExecutionsForWorkflowTemplate(workflowTemplate.ID)
if err != nil {
return err
}
cronWorkflowsCount, err := client.CountCronWorkflows(namespace.Name, uid)
if err != nil {
return err
}
// Archive the template if we have no resources associated with it
if workflowExecutionsCount == 0 && cronWorkflowsCount == 0 {
if _, err := client.ArchiveWorkflowTemplate(namespace.Name, uid); err != nil {
return err
}
}
}
return nil
}
// Down20210329194731 returns the hyperparameter-tuning workflow if it was deleted
func Down20210329194731(tx *sql.Tx) error {
// This code is executed when the migration is rolled back.
client, err := getClient()
if err != nil {
return err
}
defer client.DB.Close()
namespaces, err := client.ListOnepanelEnabledNamespaces()
if err != nil {
return err
}
uid, err := uid2.GenerateUID("hyperparameter-tuning", 30)
if err != nil {
return err
}
for _, namespace := range namespaces {
workflowTemplate, err := client.GetWorkflowTemplateRaw(namespace.Name, uid)
if err != nil {
return err
}
if workflowTemplate == nil {
err := createWorkflowTemplate(
filepath.Join("workflows", "hyperparameter-tuning", "20210118175809.yaml"),
hyperparameterTuningTemplateName,
map[string]string{
"framework": "tensorflow",
"tuner": "TPE",
"created-by": "system",
},
)
if err != nil {
return err
}
}
}
return nil
}

View File

@@ -0,0 +1,31 @@
package migration
import (
"database/sql"
"github.com/pressly/goose"
"path/filepath"
)
var deepLearningDesktopTemplateName = "Deep Learning Desktop"
func initialize20210414165510() {
if _, ok := initializedMigrations[20210414165510]; !ok {
goose.AddMigration(Up20210414165510, Down20210414165510)
initializedMigrations[20210414165510] = true
}
}
// Up20210414165510 creates the Deep Learning Desktop Workspace Template
func Up20210414165510(tx *sql.Tx) error {
// This code is executed when the migration is applied.
return createWorkspaceTemplate(
filepath.Join("workspaces", "vnc", "20210414165510.yaml"),
deepLearningDesktopTemplateName,
"Deep learning desktop with VNC")
}
// Down20210414165510 removes the Deep Learning Desktop Workspace Template
func Down20210414165510(tx *sql.Tx) error {
// This code is executed when the migration is rolled back.
return archiveWorkspaceTemplate(deepLearningDesktopTemplateName)
}

View File

@@ -0,0 +1,66 @@
package migration
import (
"database/sql"
"github.com/pressly/goose"
"path/filepath"
)
func initialize20210719190719() {
if _, ok := initializedMigrations[20210719190719]; !ok {
goose.AddMigration(Up20210719190719, Down20210719190719)
initializedMigrations[20210719190719] = true
}
}
// Up20210719190719 updates the workspace templates to use new v1.0.0 of filesyncer
func Up20210719190719(tx *sql.Tx) error {
// This code is executed when the migration is applied.
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "cvat", "20210719190719.yaml"),
cvatTemplateName); err != nil {
return err
}
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "jupyterlab", "20210719190719.yaml"),
jupyterLabTemplateName); err != nil {
return err
}
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "vnc", "20210719190719.yaml"),
deepLearningDesktopTemplateName); err != nil {
return err
}
return updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "vscode", "20210719190719.yaml"),
vscodeWorkspaceTemplateName)
}
// Down20210719190719 rolls back the change to update filesyncer
func Down20210719190719(tx *sql.Tx) error {
// This code is executed when the migration is rolled back.
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "cvat", "20210323175655.yaml"),
cvatTemplateName); err != nil {
return err
}
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "jupyterlab", "20210323175655.yaml"),
jupyterLabTemplateName); err != nil {
return err
}
if err := updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "vnc", "20210414165510.yaml"),
deepLearningDesktopTemplateName); err != nil {
return err
}
return updateWorkspaceTemplateManifest(
filepath.Join("workspaces", "vscode", "20210323175655.yaml"),
vscodeWorkspaceTemplateName)
}

View File

@@ -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")
}

View File

@@ -91,6 +91,12 @@ func Initialize() {
initialize20210129142057() initialize20210129142057()
initialize20210129152427() initialize20210129152427()
initialize20210224180017() initialize20210224180017()
initialize20210323175655()
initialize20210329171739()
initialize20210329194731()
initialize20210414165510()
initialize20210719190719()
initialize20211028205201()
if err := client.DB.Close(); err != nil { if err := client.DB.Close(); err != nil {
log.Printf("[error] closing db %v", err) log.Printf("[error] closing db %v", err)

View File

@@ -1,14 +1,17 @@
package migration package migration
import ( import (
"fmt"
v1 "github.com/onepanelio/core/pkg" v1 "github.com/onepanelio/core/pkg"
"github.com/onepanelio/core/pkg/util/data"
uid2 "github.com/onepanelio/core/pkg/util/uid" uid2 "github.com/onepanelio/core/pkg/util/uid"
"path/filepath"
) )
// updateWorkspaceTemplateManifest will update the workspace template given by {{templateName}} with the contents // createWorkspaceTemplate will create the workspace template given by {{templateName}} with the contents
// given by {{filename}} // given by {{filename}}
// It will do so for all namespaces. // It will do so for all namespaces.
func updateWorkspaceTemplateManifest(filename, templateName string) error { func createWorkspaceTemplate(filename, templateName, description string) error {
client, err := getClient() client, err := getClient()
if err != nil { if err != nil {
return err return err
@@ -20,7 +23,101 @@ func updateWorkspaceTemplateManifest(filename, templateName string) error {
return err 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
}
uid, err := uid2.GenerateUID(templateName, 30)
if err != nil {
return err
}
for _, namespace := range namespaces {
workspaceTemplate := &v1.WorkspaceTemplate{
UID: uid,
Name: templateName,
Manifest: newManifest,
Description: description,
}
err = ReplaceArtifactRepositoryType(client, namespace, nil, workspaceTemplate)
if err != nil {
return err
}
if _, err := client.CreateWorkspaceTemplate(namespace.Name, workspaceTemplate); err != nil {
return err
}
}
return nil
}
func archiveWorkspaceTemplate(templateName string) error {
client, err := getClient()
if err != nil {
return err
}
defer client.DB.Close()
namespaces, err := client.ListOnepanelEnabledNamespaces()
if err != nil {
return err
}
uid, err := uid2.GenerateUID(templateName, 30)
if err != nil {
return err
}
for _, namespace := range namespaces {
hasRunning, err := client.WorkspaceTemplateHasRunningWorkspaces(namespace.Name, uid)
if err != nil {
return fmt.Errorf("Unable to get check running workspaces")
}
if hasRunning {
return fmt.Errorf("unable to archive workspace template. There are running workspaces that use it")
}
_, err = client.ArchiveWorkspaceTemplate(namespace.Name, uid)
if err != nil {
return err
}
}
return nil
}
// updateWorkspaceTemplateManifest will update the workspace template given by {{templateName}} with the contents
// given by {{filename}}
// It will do so for all namespaces.
func updateWorkspaceTemplateManifest(filename, templateName string) error {
client, err := getClient()
if err != nil {
return err
}
defer client.DB.Close()
filename = filepath.Join("db", "yaml", filename)
namespaces, err := client.ListOnepanelEnabledNamespaces()
if err != nil {
return err
}
manifest, err := data.ManifestFileFromFile(filename)
if err != nil {
return err
}
newManifest, err := manifest.SpecString()
if err != nil { if err != nil {
return err return err
} }
@@ -63,7 +160,14 @@ func createWorkflowTemplate(filename, templateName string, labels map[string]str
return err 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 { if err != nil {
return err return err
} }
@@ -108,7 +212,14 @@ func updateWorkflowTemplateManifest(filename, templateName string, labels map[st
return err 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 { if err != nil {
return err return err
} }

View File

@@ -0,0 +1,7 @@
-- +goose Up
-- SQL in this section is executed when the migration is applied.
ALTER TABLE workflow_template_versions ADD COLUMN description TEXT DEFAULT '';
-- +goose Down
-- SQL in this section is executed when the migration is rolled back.
ALTER TABLE workflow_template_versions DROP COLUMN description;

View File

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

View File

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

View File

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

View File

@@ -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

View File

@@ -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

View File

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

View File

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

View File

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

View File

@@ -1,208 +1,217 @@
# source: https://github.com/onepanelio/templates/blob/master/workflows/maskrcnn-training/ metadata:
arguments: name: "MaskRCNN Training"
parameters: kind: Workflow
- name: cvat-annotation-path version: 20210118175809
value: 'artifacts/{{workflow.namespace}}/annotations/' action: update
hint: Path to annotated data (COCO format) in default object storage. In CVAT, this parameter will be pre-populated. source: "https://github.com/onepanelio/templates/blob/master/workflows/maskrcnn-training/"
displayName: Dataset path labels:
visibility: internal "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 - name: val-split
value: 10 value: 10
displayName: Validation split size displayName: Validation split size
type: input.number type: input.number
visibility: public visibility: public
hint: Enter validation set size in percentage of full dataset. (0 - 100) hint: Enter validation set size in percentage of full dataset. (0 - 100)
- name: num-augmentation-cycles - name: num-augmentation-cycles
value: 1 value: 1
displayName: Number of augmentation cycles displayName: Number of augmentation cycles
type: input.number type: input.number
visibility: public visibility: public
hint: Number of augmentation cycles, zero means no data augmentation hint: Number of augmentation cycles, zero means no data augmentation
- name: preprocessing-parameters - name: preprocessing-parameters
value: |- value: |-
RandomBrightnessContrast: RandomBrightnessContrast:
p: 0.2 p: 0.2
GaussianBlur: GaussianBlur:
p: 0.3 p: 0.3
GaussNoise: GaussNoise:
p: 0.4 p: 0.4
HorizontalFlip: HorizontalFlip:
p: 0.5 p: 0.5
VerticalFlip: VerticalFlip:
p: 0.3 p: 0.3
displayName: Preprocessing parameters displayName: Preprocessing parameters
visibility: public visibility: public
type: textarea.textarea type: textarea.textarea
hint: 'See <a href="https://albumentations.ai/docs/api_reference/augmentations/transforms/" target="_blank">documentation</a> for more information on parameters.' 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 - name: cvat-num-classes
displayName: Number of classes displayName: Number of classes
hint: Number of classes. In CVAT, this parameter will be pre-populated. hint: Number of classes. In CVAT, this parameter will be pre-populated.
value: '10' value: '10'
visibility: internal visibility: internal
- name: hyperparameters - name: hyperparameters
displayName: Hyperparameters displayName: Hyperparameters
visibility: public visibility: public
type: textarea.textarea type: textarea.textarea
value: |- value: |-
stage_1_epochs: 1 # Epochs for network heads stage_1_epochs: 1 # Epochs for network heads
stage_2_epochs: 1 # Epochs for finetune layers stage_2_epochs: 1 # Epochs for finetune layers
stage_3_epochs: 1 # Epochs for all layers stage_3_epochs: 1 # Epochs for all layers
num_steps: 1000 # Num steps per epoch 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.' 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 - name: dump-format
value: cvat_coco value: cvat_coco
displayName: CVAT dump format displayName: CVAT dump format
visibility: private visibility: private
- name: cvat-finetune-checkpoint - name: cvat-finetune-checkpoint
value: '' 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. 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 displayName: Checkpoint path
visibility: public visibility: public
- displayName: Node pool - displayName: Node pool
hint: Name of node pool or group to run this workflow task hint: Name of node pool or group to run this workflow task
type: select.nodepool type: select.nodepool
visibility: public visibility: public
name: sys-node-pool name: sys-node-pool
value: {{.DefaultNodePoolOption}} value: "{{.DefaultNodePoolOption}}"
required: true required: true
entrypoint: main entrypoint: main
templates: templates:
- dag: - dag:
tasks: tasks:
- name: preprocessing - name: preprocessing
template: preprocessing template: preprocessing
- name: train-model - name: train-model
template: tensorflow template: tensorflow
dependencies: [preprocessing] dependencies: [preprocessing]
arguments: arguments:
artifacts: artifacts:
- name: data - name: data
from: "{{tasks.preprocessing.outputs.artifacts.processed-data}}" from: "{{tasks.preprocessing.outputs.artifacts.processed-data}}"
name: main name: main
- container: - container:
args: args:
- | - |
pip install pycocotools scikit-image==0.16.2 && \ pip install pycocotools scikit-image==0.16.2 && \
cd /mnt/src/train/workflows/maskrcnn-training && \ cd /mnt/src/train/workflows/maskrcnn-training && \
python -u main.py train --dataset=/mnt/data/datasets/train_set/ \ python -u main.py train --dataset=/mnt/data/datasets/train_set/ \
--model=workflow_maskrcnn \ --model=workflow_maskrcnn \
--extras="{{workflow.parameters.hyperparameters}}" \ --extras="{{workflow.parameters.hyperparameters}}" \
--ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}" \ --ref_model_path="{{workflow.parameters.cvat-finetune-checkpoint}}" \
--num_classes="{{workflow.parameters.cvat-num-classes}}" \ --num_classes="{{workflow.parameters.cvat-num-classes}}" \
--val_dataset=/mnt/data/datasets/eval_set/ \ --val_dataset=/mnt/data/datasets/eval_set/ \
--use_validation=True --use_validation=True
command: command:
- sh - sh
- -c - -c
image: onepanel/dl:0.17.0 image: onepanel/dl:v0.20.0
volumeMounts: volumeMounts:
- mountPath: /mnt/data - mountPath: /mnt/data
name: processed-data name: processed-data
- mountPath: /mnt/output - mountPath: /mnt/output
name: output name: output
workingDir: /mnt/src workingDir: /mnt/src
sidecars: sidecars:
- name: tensorboard - name: tensorboard
image: onepanel/dl:0.17.0 image: onepanel/dl:v0.20.0
command: [ sh, -c ] command: [ sh, -c ]
env: env:
- name: ONEPANEL_INTERACTIVE_SIDECAR - name: ONEPANEL_INTERACTIVE_SIDECAR
value: 'true' value: 'true'
args: [ "tensorboard --logdir /mnt/output/tensorboard" ] args: [ "tensorboard --logdir /mnt/output/tensorboard" ]
ports: ports:
- containerPort: 6006 - containerPort: 6006
name: tensorboard name: tensorboard
nodeSelector: nodeSelector:
{{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}' "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
inputs: inputs:
artifacts: artifacts:
- name: data - name: data
path: /mnt/data/datasets/ path: /mnt/data/datasets/
- name: models - name: models
path: /mnt/data/models/ path: /mnt/data/models/
optional: true optional: true
s3: s3:
key: '{{workflow.parameters.cvat-finetune-checkpoint}}' key: '{{workflow.parameters.cvat-finetune-checkpoint}}'
- git: - git:
repo: https://github.com/onepanelio/templates.git repo: https://github.com/onepanelio/templates.git
revision: v0.18.0 revision: v0.18.0
name: src name: src
path: /mnt/src/train path: /mnt/src/train
name: tensorflow name: tensorflow
outputs: outputs:
artifacts: artifacts:
- name: model - name: model
optional: true optional: true
path: /mnt/output path: /mnt/output
- container: - container:
args: args:
- | - |
pip install pycocotools && \ pip install pycocotools && \
cd /mnt/src/preprocessing/workflows/albumentations-preprocessing && \ cd /mnt/src/preprocessing/workflows/albumentations-preprocessing && \
python -u main.py \ python -u main.py \
--data_aug_params="{{workflow.parameters.preprocessing-parameters}}" \ --data_aug_params="{{workflow.parameters.preprocessing-parameters}}" \
--val_split={{workflow.parameters.val-split}} \ --val_split={{workflow.parameters.val-split}} \
--aug_steps={{workflow.parameters.num-augmentation-cycles}} --aug_steps={{workflow.parameters.num-augmentation-cycles}}
command: command:
- sh - sh
- -c - -c
image: onepanel/dl:0.17.0 image: onepanel/dl:v0.20.0
volumeMounts: volumeMounts:
- mountPath: /mnt/data - mountPath: /mnt/data
name: data name: data
- mountPath: /mnt/output - mountPath: /mnt/output
name: processed-data name: processed-data
workingDir: /mnt/src workingDir: /mnt/src
nodeSelector: nodeSelector:
{{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}' "{{.NodePoolLabel}}": '{{workflow.parameters.sys-node-pool}}'
inputs: inputs:
artifacts: artifacts:
- name: data - name: data
path: /mnt/data/datasets/ path: /mnt/data/datasets/
s3: s3:
key: '{{workflow.parameters.cvat-annotation-path}}' key: '{{workflow.parameters.cvat-annotation-path}}'
- git: - git:
repo: https://github.com/onepanelio/templates.git repo: https://github.com/onepanelio/templates.git
revision: v0.18.0 revision: v0.18.0
name: src name: src
path: /mnt/src/preprocessing path: /mnt/src/preprocessing
name: preprocessing name: preprocessing
outputs: outputs:
artifacts: artifacts:
- name: processed-data - name: processed-data
optional: true optional: true
path: /mnt/output path: /mnt/output
volumeClaimTemplates: volumeClaimTemplates:
- metadata: - metadata:
name: data name: data
spec: spec:
accessModes: accessModes:
- ReadWriteOnce - ReadWriteOnce
resources: resources:
requests: requests:
storage: 200Gi storage: 200Gi
- metadata: - metadata:
name: processed-data name: processed-data
spec: spec:
accessModes: accessModes:
- ReadWriteOnce - ReadWriteOnce
resources: resources:
requests: requests:
storage: 200Gi storage: 200Gi
- metadata: - metadata:
name: output name: output
spec: spec:
accessModes: accessModes:
- ReadWriteOnce - ReadWriteOnce
resources: resources:
requests: requests:
storage: 200Gi storage: 200Gi

View File

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

View File

@@ -1,207 +1,216 @@
# source: https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/ metadata:
arguments: name: "PyTorch Training"
parameters: kind: Workflow
- name: epochs version: 20201221194344
value: '10' action: update
- displayName: Node pool source: "https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/"
hint: Name of node pool or group to run this workflow task labels:
type: select.nodepool "created-by": "system"
name: sys-node-pool framework: pytorch
value: {{.DefaultNodePoolOption}} spec:
visibility: public arguments:
required: true parameters:
entrypoint: main - name: epochs
templates: value: '10'
- name: main - displayName: Node pool
dag: hint: Name of node pool or group to run this workflow task
tasks: type: select.nodepool
- name: train-model name: sys-node-pool
template: train-model value: "{{.DefaultNodePoolOption}}"
- name: train-model visibility: public
# Indicates that we want to push files in /mnt/output to object storage required: true
outputs: entrypoint: main
artifacts: templates:
- name: output - name: main
path: /mnt/output dag:
optional: true tasks:
script: - name: train-model
image: onepanel/dl:0.17.0 template: train-model
command: - name: train-model
- python # Indicates that we want to push files in /mnt/output to object storage
- '-u' outputs:
source: | artifacts:
import json - name: output
import torch path: /mnt/output
import torch.nn as nn optional: true
import torch.nn.functional as F script:
import torch.optim as optim image: onepanel/dl:0.17.0
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: command:
- sh - python
- '-c' - '-u'
env: source: |
- name: ONEPANEL_INTERACTIVE_SIDECAR import json
value: 'true' import torch
args: import torch.nn as nn
# Read logs from /mnt/output - this directory is auto-mounted from volumeMounts import torch.nn.functional as F
- tensorboard --logdir /mnt/output/tensorboard import torch.optim as optim
ports: from torchvision import datasets, transforms
- containerPort: 6006 from torch.optim.lr_scheduler import StepLR
name: tensorboard from torch.utils.tensorboard import SummaryWriter
volumeClaimTemplates:
# Provision volumes for storing data and output
- metadata: class Net(nn.Module):
name: data def __init__(self):
spec: super(Net, self).__init__()
accessModes: [ "ReadWriteOnce" ] self.conv1 = nn.Conv2d(1, 32, 3, 1)
resources: self.conv2 = nn.Conv2d(32, 64, 3, 1)
requests: self.dropout1 = nn.Dropout(0.25)
storage: 2Gi self.dropout2 = nn.Dropout(0.5)
- metadata: self.fc1 = nn.Linear(9216, 128)
name: output self.fc2 = nn.Linear(128, 10)
spec:
accessModes: [ "ReadWriteOnce" ] def forward(self, x):
resources: x = self.conv1(x)
requests: x = F.relu(x)
storage: 2Gi 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

View File

@@ -1,207 +1,216 @@
# source: https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/ metadata:
arguments: name: "PyTorch Training"
parameters: kind: Workflow
- name: epochs version: 20210118175809
value: '10' action: update
- displayName: Node pool source: "https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/"
hint: Name of node pool or group to run this workflow task labels:
type: select.nodepool "created-by": "system"
name: sys-node-pool framework: pytorch
value: {{.DefaultNodePoolOption}} spec:
visibility: public arguments:
required: true parameters:
entrypoint: main - name: epochs
templates: value: '10'
- name: main - displayName: Node pool
dag: hint: Name of node pool or group to run this workflow task
tasks: type: select.nodepool
- name: train-model name: sys-node-pool
template: train-model value: "{{.DefaultNodePoolOption}}"
- name: train-model visibility: public
# Indicates that we want to push files in /mnt/output to object storage required: true
outputs: entrypoint: main
artifacts: templates:
- name: output - name: main
path: /mnt/output dag:
optional: true tasks:
script: - name: train-model
image: onepanel/dl:0.17.0 template: train-model
command: - name: train-model
- python # Indicates that we want to push files in /mnt/output to object storage
- '-u' outputs:
source: | artifacts:
import json - name: output
import torch path: /mnt/output
import torch.nn as nn optional: true
import torch.nn.functional as F script:
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 image: onepanel/dl:0.17.0
command: command:
- sh - python
- '-c' - '-u'
env: source: |
- name: ONEPANEL_INTERACTIVE_SIDECAR import json
value: 'true' import torch
args: import torch.nn as nn
# Read logs from /mnt/output - this directory is auto-mounted from volumeMounts import torch.nn.functional as F
- tensorboard --logdir /mnt/output/tensorboard import torch.optim as optim
ports: from torchvision import datasets, transforms
- containerPort: 6006 from torch.optim.lr_scheduler import StepLR
name: tensorboard from torch.utils.tensorboard import SummaryWriter
volumeClaimTemplates:
# Provision volumes for storing data and output
- metadata: class Net(nn.Module):
name: data def __init__(self):
spec: super(Net, self).__init__()
accessModes: [ "ReadWriteOnce" ] self.conv1 = nn.Conv2d(1, 32, 3, 1)
resources: self.conv2 = nn.Conv2d(32, 64, 3, 1)
requests: self.dropout1 = nn.Dropout(0.25)
storage: 2Gi self.dropout2 = nn.Dropout(0.5)
- metadata: self.fc1 = nn.Linear(9216, 128)
name: output self.fc2 = nn.Linear(128, 10)
spec:
accessModes: [ "ReadWriteOnce" ] def forward(self, x):
resources: x = self.conv1(x)
requests: x = F.relu(x)
storage: 2Gi 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

View File

@@ -0,0 +1,216 @@
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:
- 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

View File

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

View File

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

View File

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

View File

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

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@@ -0,0 +1,127 @@
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:
- 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

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@@ -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

View File

@@ -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

View File

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

View File

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

View File

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

View File

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

View File

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

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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

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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

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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

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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

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@@ -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

View File

@@ -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

View File

@@ -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

View File

@@ -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

View File

@@ -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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@@ -0,0 +1,141 @@
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

View File

@@ -0,0 +1,141 @@
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

View File

@@ -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

View File

@@ -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

View File

@@ -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

View File

@@ -1,58 +1,65 @@
# Docker containers that are part of the Workspace metadata:
containers: name: JupyterLab
- name: jupyterlab-tensorflow kind: Workspace
image: onepanel/jupyterlab:1.0.1 version: 20200929153931
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"] action: update
env: description: "Interactive development environment for notebooks"
- name: tornado spec:
value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'" # Docker containers that are part of the Workspace
args: containers:
ports: - name: jupyterlab-tensorflow
- containerPort: 8888 image: onepanel/jupyterlab:1.0.1
name: jupyterlab 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"]
- containerPort: 6006 env:
name: tensorboard - name: tornado
volumeMounts: value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ \'self'\"}}'"
- name: data args:
mountPath: /data ports:
ports: - containerPort: 8888
- name: jupyterlab name: jupyterlab
port: 80 - containerPort: 6006
protocol: TCP name: tensorboard
targetPort: 8888 volumeMounts:
- name: tensorboard - name: data
port: 6006 mountPath: /data
protocol: TCP ports:
targetPort: 6006 - name: jupyterlab
routes: port: 80
- match: protocol: TCP
- uri: targetPort: 8888
prefix: /tensorboard - name: tensorboard
route: port: 6006
- destination: protocol: TCP
port: targetPort: 6006
number: 6006 routes:
- match: - match:
- uri: - uri:
prefix: / #jupyter runs at the default route prefix: /tensorboard
route: route:
- destination: - destination:
port: port:
number: 80 number: 6006
# DAG Workflow to be executed once a Workspace action completes (optional) - match:
#postExecutionWorkflow: - uri:
# entrypoint: main prefix: / #jupyter runs at the default route
# templates: route:
# - name: main - destination:
# dag: port:
# tasks: number: 80
# - name: slack-notify # DAG Workflow to be executed once a Workspace action completes (optional)
# template: slack-notify #postExecutionWorkflow:
# - name: slack-notify # entrypoint: main
# container: # templates:
# image: technosophos/slack-notify # - name: main
# args: # dag:
# - 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 # tasks:
# command: # - name: slack-notify
# - sh # template: slack-notify
# - -c # - 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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@@ -0,0 +1,108 @@
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

View File

@@ -0,0 +1,108 @@
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

View File

@@ -0,0 +1,64 @@
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

View File

@@ -0,0 +1,88 @@
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

View File

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

View File

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

View File

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

View File

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

View File

@@ -0,0 +1,74 @@
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

View File

@@ -0,0 +1,74 @@
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

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