Adding automated tests and README for SDK v2 tutorials (#1903)
* Adding test for AML in a day * Update tutorials-azureml-in-a-day-azureml-in-a-day.yml * Update tutorials-azureml-in-a-day-azureml-in-a-day.yml * Update tutorials-azureml-in-a-day-azureml-in-a-day.yml * Update azureml-in-a-day.ipynb * Adding tests for more tutorials * Update azureml-in-a-day.ipynb * Adding README files * Update readme.py * Update azureml-in-a-day.ipynb * Added Description to all files * Update README.md * Update readme.py
This commit is contained in:
Bala P V
GitHub
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50eee837bc
Коммит
539bf6257d
96
.github/workflows/tutorials-azureml-getting-started-azureml-getting-started-studio.yml
поставляемый
Normal file
96
.github/workflows/tutorials-azureml-getting-started-azureml-getting-started-studio.yml
поставляемый
Normal file
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@ -0,0 +1,96 @@
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# This code is autogenerated.
|
||||
# Code is generated by running custom script: python3 readme.py
|
||||
# Any manual changes to this file may cause incorrect behavior.
|
||||
# Any manual changes will be overwritten if the code is regenerated.
|
||||
|
||||
name: tutorials-azureml-getting-started-azureml-getting-started-studio
|
||||
# This file is created by tutorials/readme.py.
|
||||
# Please do not edit directly.
|
||||
on:
|
||||
workflow_dispatch:
|
||||
schedule:
|
||||
- cron: "0 */8 * * *"
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- tutorials/azureml-getting-started/**
|
||||
- .github/workflows/tutorials-azureml-getting-started-azureml-getting-started-studio.yml
|
||||
- sdk/python/dev-requirements.txt
|
||||
- infra/**
|
||||
- sdk/python/setup.sh
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: check out repo
|
||||
uses: actions/checkout@v2
|
||||
- name: setup python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: "3.8"
|
||||
- name: pip install notebook reqs
|
||||
run: pip install -r sdk/python/dev-requirements.txt
|
||||
- name: pip install mlflow reqs
|
||||
run: pip install -r sdk/python/mlflow-requirements.txt
|
||||
- name: azure login
|
||||
uses: azure/login@v1
|
||||
with:
|
||||
creds: ${{secrets.AZUREML_CREDENTIALS}}
|
||||
- name: bootstrap resources
|
||||
run: |
|
||||
echo '${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}';
|
||||
bash bootstrap.sh
|
||||
working-directory: infra
|
||||
continue-on-error: false
|
||||
- name: setup SDK
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: sdk/python
|
||||
continue-on-error: true
|
||||
- name: setup-cli
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: cli
|
||||
continue-on-error: true
|
||||
- name: run azureml-getting-started/azureml-getting-started-studio.ipynb
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" replace_template_values "azureml-getting-started-studio.ipynb";
|
||||
[ -f "../../.azureml/config" ] && cat "../../.azureml/config";
|
||||
papermill -k python azureml-getting-started-studio.ipynb azureml-getting-started-studio.output.ipynb
|
||||
working-directory: tutorials/azureml-getting-started
|
||||
- name: upload notebook's working folder as an artifact
|
||||
if: ${{ always() }}
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: azureml-getting-started-studio
|
||||
path: tutorials/azureml-getting-started
|
||||
|
||||
- name: Send IcM on failure
|
||||
if: ${{ failure() && github.ref_type == 'branch' && (github.ref_name == 'main' || contains(github.ref_name, 'release')) }}
|
||||
uses: ./.github/actions/generate-icm
|
||||
with:
|
||||
host: ${{ secrets.AZUREML_ICM_CONNECTOR_HOST_NAME }}
|
||||
connector_id: ${{ secrets.AZUREML_ICM_CONNECTOR_CONNECTOR_ID }}
|
||||
certificate: ${{ secrets.AZUREML_ICM_CONNECTOR_CERTIFICATE }}
|
||||
private_key: ${{ secrets.AZUREML_ICM_CONNECTOR_PRIVATE_KEY }}
|
||||
args: |
|
||||
incident:
|
||||
Title: "[azureml-examples] Notebook validation failed on branch '${{ github.ref_name }}' for notebook 'azureml-getting-started/azureml-getting-started-studio.ipynb'"
|
||||
Summary: |
|
||||
Notebook 'azureml-getting-started/azureml-getting-started-studio.ipynb' is failing on branch '${{ github.ref_name }}': ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
|
||||
Severity: 4
|
||||
RoutingId: "github://azureml-examples"
|
||||
Status: Active
|
||||
Source:
|
||||
IncidentId: "azureml-getting-started/azureml-getting-started-studio.ipynb[${{ github.ref_name }}]"
|
||||
|
|
@ -0,0 +1,96 @@
|
|||
# This code is autogenerated.
|
||||
# Code is generated by running custom script: python3 readme.py
|
||||
# Any manual changes to this file may cause incorrect behavior.
|
||||
# Any manual changes will be overwritten if the code is regenerated.
|
||||
|
||||
name: tutorials-azureml-in-a-day-azureml-in-a-day
|
||||
# This file is created by tutorials/readme.py.
|
||||
# Please do not edit directly.
|
||||
on:
|
||||
workflow_dispatch:
|
||||
schedule:
|
||||
- cron: "0 */8 * * *"
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- tutorials/azureml-in-a-day/**
|
||||
- .github/workflows/tutorials-azureml-in-a-day-azureml-in-a-day.yml
|
||||
- sdk/python/dev-requirements.txt
|
||||
- infra/**
|
||||
- sdk/python/setup.sh
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: check out repo
|
||||
uses: actions/checkout@v2
|
||||
- name: setup python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: "3.8"
|
||||
- name: pip install notebook reqs
|
||||
run: pip install -r sdk/python/dev-requirements.txt
|
||||
- name: pip install mlflow reqs
|
||||
run: pip install -r sdk/python/mlflow-requirements.txt
|
||||
- name: azure login
|
||||
uses: azure/login@v1
|
||||
with:
|
||||
creds: ${{secrets.AZUREML_CREDENTIALS}}
|
||||
- name: bootstrap resources
|
||||
run: |
|
||||
echo '${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}';
|
||||
bash bootstrap.sh
|
||||
working-directory: infra
|
||||
continue-on-error: false
|
||||
- name: setup SDK
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: sdk/python
|
||||
continue-on-error: true
|
||||
- name: setup-cli
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: cli
|
||||
continue-on-error: true
|
||||
- name: run azureml-in-a-day/azureml-in-a-day.ipynb
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" replace_template_values "azureml-in-a-day.ipynb";
|
||||
[ -f "../../.azureml/config" ] && cat "../../.azureml/config";
|
||||
papermill -k python azureml-in-a-day.ipynb azureml-in-a-day.output.ipynb
|
||||
working-directory: tutorials/azureml-in-a-day
|
||||
- name: upload notebook's working folder as an artifact
|
||||
if: ${{ always() }}
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: azureml-in-a-day
|
||||
path: tutorials/azureml-in-a-day
|
||||
|
||||
- name: Send IcM on failure
|
||||
if: ${{ failure() && github.ref_type == 'branch' && (github.ref_name == 'main' || contains(github.ref_name, 'release')) }}
|
||||
uses: ./.github/actions/generate-icm
|
||||
with:
|
||||
host: ${{ secrets.AZUREML_ICM_CONNECTOR_HOST_NAME }}
|
||||
connector_id: ${{ secrets.AZUREML_ICM_CONNECTOR_CONNECTOR_ID }}
|
||||
certificate: ${{ secrets.AZUREML_ICM_CONNECTOR_CERTIFICATE }}
|
||||
private_key: ${{ secrets.AZUREML_ICM_CONNECTOR_PRIVATE_KEY }}
|
||||
args: |
|
||||
incident:
|
||||
Title: "[azureml-examples] Notebook validation failed on branch '${{ github.ref_name }}' for notebook 'azureml-in-a-day/azureml-in-a-day.ipynb'"
|
||||
Summary: |
|
||||
Notebook 'azureml-in-a-day/azureml-in-a-day.ipynb' is failing on branch '${{ github.ref_name }}': ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
|
||||
Severity: 4
|
||||
RoutingId: "github://azureml-examples"
|
||||
Status: Active
|
||||
Source:
|
||||
IncidentId: "azureml-in-a-day/azureml-in-a-day.ipynb[${{ github.ref_name }}]"
|
||||
96
.github/workflows/tutorials-e2e-distributed-pytorch-image-e2e-object-classification-distributed-pytorch.yml
поставляемый
Normal file
96
.github/workflows/tutorials-e2e-distributed-pytorch-image-e2e-object-classification-distributed-pytorch.yml
поставляемый
Normal file
|
|
@ -0,0 +1,96 @@
|
|||
# This code is autogenerated.
|
||||
# Code is generated by running custom script: python3 readme.py
|
||||
# Any manual changes to this file may cause incorrect behavior.
|
||||
# Any manual changes will be overwritten if the code is regenerated.
|
||||
|
||||
name: tutorials-e2e-distributed-pytorch-image-e2e-object-classification-distributed-pytorch
|
||||
# This file is created by tutorials/readme.py.
|
||||
# Please do not edit directly.
|
||||
on:
|
||||
workflow_dispatch:
|
||||
schedule:
|
||||
- cron: "0 */8 * * *"
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- tutorials/e2e-distributed-pytorch-image/**
|
||||
- .github/workflows/tutorials-e2e-distributed-pytorch-image-e2e-object-classification-distributed-pytorch.yml
|
||||
- sdk/python/dev-requirements.txt
|
||||
- infra/**
|
||||
- sdk/python/setup.sh
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: check out repo
|
||||
uses: actions/checkout@v2
|
||||
- name: setup python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: "3.8"
|
||||
- name: pip install notebook reqs
|
||||
run: pip install -r sdk/python/dev-requirements.txt
|
||||
- name: pip install mlflow reqs
|
||||
run: pip install -r sdk/python/mlflow-requirements.txt
|
||||
- name: azure login
|
||||
uses: azure/login@v1
|
||||
with:
|
||||
creds: ${{secrets.AZUREML_CREDENTIALS}}
|
||||
- name: bootstrap resources
|
||||
run: |
|
||||
echo '${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}';
|
||||
bash bootstrap.sh
|
||||
working-directory: infra
|
||||
continue-on-error: false
|
||||
- name: setup SDK
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: sdk/python
|
||||
continue-on-error: true
|
||||
- name: setup-cli
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: cli
|
||||
continue-on-error: true
|
||||
- name: run e2e-distributed-pytorch-image/e2e-object-classification-distributed-pytorch.ipynb
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" replace_template_values "e2e-object-classification-distributed-pytorch.ipynb";
|
||||
[ -f "../../.azureml/config" ] && cat "../../.azureml/config";
|
||||
papermill -k python e2e-object-classification-distributed-pytorch.ipynb e2e-object-classification-distributed-pytorch.output.ipynb
|
||||
working-directory: tutorials/e2e-distributed-pytorch-image
|
||||
- name: upload notebook's working folder as an artifact
|
||||
if: ${{ always() }}
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: e2e-object-classification-distributed-pytorch
|
||||
path: tutorials/e2e-distributed-pytorch-image
|
||||
|
||||
- name: Send IcM on failure
|
||||
if: ${{ failure() && github.ref_type == 'branch' && (github.ref_name == 'main' || contains(github.ref_name, 'release')) }}
|
||||
uses: ./.github/actions/generate-icm
|
||||
with:
|
||||
host: ${{ secrets.AZUREML_ICM_CONNECTOR_HOST_NAME }}
|
||||
connector_id: ${{ secrets.AZUREML_ICM_CONNECTOR_CONNECTOR_ID }}
|
||||
certificate: ${{ secrets.AZUREML_ICM_CONNECTOR_CERTIFICATE }}
|
||||
private_key: ${{ secrets.AZUREML_ICM_CONNECTOR_PRIVATE_KEY }}
|
||||
args: |
|
||||
incident:
|
||||
Title: "[azureml-examples] Notebook validation failed on branch '${{ github.ref_name }}' for notebook 'e2e-distributed-pytorch-image/e2e-object-classification-distributed-pytorch.ipynb'"
|
||||
Summary: |
|
||||
Notebook 'e2e-distributed-pytorch-image/e2e-object-classification-distributed-pytorch.ipynb' is failing on branch '${{ github.ref_name }}': ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
|
||||
Severity: 4
|
||||
RoutingId: "github://azureml-examples"
|
||||
Status: Active
|
||||
Source:
|
||||
IncidentId: "e2e-distributed-pytorch-image/e2e-object-classification-distributed-pytorch.ipynb[${{ github.ref_name }}]"
|
||||
|
|
@ -0,0 +1,96 @@
|
|||
# This code is autogenerated.
|
||||
# Code is generated by running custom script: python3 readme.py
|
||||
# Any manual changes to this file may cause incorrect behavior.
|
||||
# Any manual changes will be overwritten if the code is regenerated.
|
||||
|
||||
name: tutorials-e2e-ds-experience-e2e-ml-workflow
|
||||
# This file is created by tutorials/readme.py.
|
||||
# Please do not edit directly.
|
||||
on:
|
||||
workflow_dispatch:
|
||||
schedule:
|
||||
- cron: "0 */8 * * *"
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- tutorials/e2e-ds-experience/**
|
||||
- .github/workflows/tutorials-e2e-ds-experience-e2e-ml-workflow.yml
|
||||
- sdk/python/dev-requirements.txt
|
||||
- infra/**
|
||||
- sdk/python/setup.sh
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: check out repo
|
||||
uses: actions/checkout@v2
|
||||
- name: setup python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: "3.8"
|
||||
- name: pip install notebook reqs
|
||||
run: pip install -r sdk/python/dev-requirements.txt
|
||||
- name: pip install mlflow reqs
|
||||
run: pip install -r sdk/python/mlflow-requirements.txt
|
||||
- name: azure login
|
||||
uses: azure/login@v1
|
||||
with:
|
||||
creds: ${{secrets.AZUREML_CREDENTIALS}}
|
||||
- name: bootstrap resources
|
||||
run: |
|
||||
echo '${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}';
|
||||
bash bootstrap.sh
|
||||
working-directory: infra
|
||||
continue-on-error: false
|
||||
- name: setup SDK
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: sdk/python
|
||||
continue-on-error: true
|
||||
- name: setup-cli
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: cli
|
||||
continue-on-error: true
|
||||
- name: run e2e-ds-experience/e2e-ml-workflow.ipynb
|
||||
run: |
|
||||
source "${{ github.workspace }}/infra/sdk_helpers.sh";
|
||||
source "${{ github.workspace }}/infra/init_environment.sh";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
|
||||
bash "${{ github.workspace }}/infra/sdk_helpers.sh" replace_template_values "e2e-ml-workflow.ipynb";
|
||||
[ -f "../../.azureml/config" ] && cat "../../.azureml/config";
|
||||
papermill -k python e2e-ml-workflow.ipynb e2e-ml-workflow.output.ipynb
|
||||
working-directory: tutorials/e2e-ds-experience
|
||||
- name: upload notebook's working folder as an artifact
|
||||
if: ${{ always() }}
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: e2e-ml-workflow
|
||||
path: tutorials/e2e-ds-experience
|
||||
|
||||
- name: Send IcM on failure
|
||||
if: ${{ failure() && github.ref_type == 'branch' && (github.ref_name == 'main' || contains(github.ref_name, 'release')) }}
|
||||
uses: ./.github/actions/generate-icm
|
||||
with:
|
||||
host: ${{ secrets.AZUREML_ICM_CONNECTOR_HOST_NAME }}
|
||||
connector_id: ${{ secrets.AZUREML_ICM_CONNECTOR_CONNECTOR_ID }}
|
||||
certificate: ${{ secrets.AZUREML_ICM_CONNECTOR_CERTIFICATE }}
|
||||
private_key: ${{ secrets.AZUREML_ICM_CONNECTOR_PRIVATE_KEY }}
|
||||
args: |
|
||||
incident:
|
||||
Title: "[azureml-examples] Notebook validation failed on branch '${{ github.ref_name }}' for notebook 'e2e-ds-experience/e2e-ml-workflow.ipynb'"
|
||||
Summary: |
|
||||
Notebook 'e2e-ds-experience/e2e-ml-workflow.ipynb' is failing on branch '${{ github.ref_name }}': ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
|
||||
Severity: 4
|
||||
RoutingId: "github://azureml-examples"
|
||||
Status: Active
|
||||
Source:
|
||||
IncidentId: "e2e-ds-experience/e2e-ml-workflow.ipynb[${{ github.ref_name }}]"
|
||||
|
|
@ -0,0 +1,54 @@
|
|||
---
|
||||
page_type: sample
|
||||
languages:
|
||||
- python
|
||||
products:
|
||||
- azure-machine-learning
|
||||
description: Top-level directory for official Azure Machine Learning Python SDK v2 tutorials.
|
||||
---
|
||||
|
||||
# Azure Machine Learning SDK (v2) end to end tutorials
|
||||
|
||||
[](https://github.com/psf/black)
|
||||
[](../LICENSE)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
1. An Azure subscription. If you don't have an Azure subscription, [create a free account](https://aka.ms/AMLFree) before you begin.
|
||||
|
||||
## Getting started
|
||||
|
||||
1. Install the SDK v2
|
||||
|
||||
```terminal
|
||||
pip install azure-ai-ml
|
||||
```
|
||||
|
||||
## Clone examples repository
|
||||
|
||||
```terminal
|
||||
git clone https://github.com/Azure/azureml-examples
|
||||
cd azureml-examples/tutorials
|
||||
```
|
||||
|
||||
## Examples available
|
||||
|
||||
Test Status is for branch - **_main_**
|
||||
|Title|Notebook|Description|Status|
|
||||
|--|--|--|--|
|
||||
|azureml-getting-started|[azureml-getting-started-studio](azureml-getting-started/azureml-getting-started-studio.ipynb)|A quickstart tutorial to train and deploy an image classification model on Azure Machine Learning studio|[](https://github.com/Azure/azureml-examples/actions/workflows/tutorials-azureml-getting-started-azureml-getting-started-studio.yml)|
|
||||
|azureml-in-a-day|[azureml-in-a-day](azureml-in-a-day/azureml-in-a-day.ipynb)|Learn how a data scientist uses Azure Machine Learning (Azure ML) to train a model, then use the model for prediction. This tutorial will help you become familiar with the core concepts of Azure ML and their most common usage.|[](https://github.com/Azure/azureml-examples/actions/workflows/tutorials-azureml-in-a-day-azureml-in-a-day.yml)|
|
||||
|e2e-distributed-pytorch-image|[e2e-object-classification-distributed-pytorch](e2e-distributed-pytorch-image/e2e-object-classification-distributed-pytorch.ipynb)|Prepare data, test and run a multi-node multi-gpu pytorch job. Use mlflow to analyze your metrics|[](https://github.com/Azure/azureml-examples/actions/workflows/tutorials-e2e-distributed-pytorch-image-e2e-object-classification-distributed-pytorch.yml)|
|
||||
|e2e-ds-experience|[e2e-ml-workflow](e2e-ds-experience/e2e-ml-workflow.ipynb)|Create production ML pipelines with Python SDK v2 in a Jupyter notebook|[](https://github.com/Azure/azureml-examples/actions/workflows/tutorials-e2e-ds-experience-e2e-ml-workflow.yml)|
|
||||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions and suggestions! Please see the [contributing guidelines](../CONTRIBUTING.mdCONTRIBUTING.md) for details.
|
||||
|
||||
## Code of Conduct
|
||||
|
||||
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). Please see the [code of conduct](../CODE_OF_CONDUCT.md) for details.
|
||||
|
||||
## Reference
|
||||
|
||||
* [Documentation](https://docs.microsoft.com/azure/machine-learning)
|
||||
|
|
@ -456,10 +456,13 @@
|
|||
}
|
||||
],
|
||||
"metadata": {
|
||||
"description": {
|
||||
"description": "A quickstart tutorial to train and deploy an image classification model on Azure Machine Learning studio"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.8 - AzureML",
|
||||
"display_name": "Python 3.10 - SDK V2",
|
||||
"language": "python",
|
||||
"name": "python38-azureml"
|
||||
"name": "python310-sdkv2"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
|
|
@ -482,4 +485,4 @@
|
|||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -192,7 +192,7 @@
|
|||
"source": [
|
||||
"## Create a job environment\n",
|
||||
"\n",
|
||||
"To run your AzureML job on your compute resource, you'll need an [environment](https://docs.microsoft.com/azure/machine-learning/concept-environments). An environment lists the software runtime and libraries that you want installed on the compute where you\u2019ll be training. It's similar to your python environment on your local machine.\n",
|
||||
"To run your AzureML job on your compute resource, you'll need an [environment](https://docs.microsoft.com/azure/machine-learning/concept-environments). An environment lists the software runtime and libraries that you want installed on the compute where you’ll be training. It's similar to your python environment on your local machine.\n",
|
||||
"\n",
|
||||
"AzureML provides many curated or ready-made environments, which are useful for common training and inference scenarios. You can also create your own custom environments using a docker image, or a conda configuration.\n",
|
||||
"\n",
|
||||
|
|
@ -611,7 +611,7 @@
|
|||
" },\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"endpoint = ml_client.begin_create_or_update(endpoint)\n",
|
||||
"endpoint = ml_client.online_endpoints.begin_create_or_update(endpoint).result()\n",
|
||||
"\n",
|
||||
"print(f\"Endpoint {endpoint.name} provisioning state: {endpoint.provisioning_state}\")"
|
||||
]
|
||||
|
|
@ -694,7 +694,7 @@
|
|||
" instance_count=1,\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"blue_deployment = ml_client.begin_create_or_update(blue_deployment)"
|
||||
"blue_deployment = ml_client.begin_create_or_update(blue_deployment).result()"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -792,10 +792,13 @@
|
|||
}
|
||||
],
|
||||
"metadata": {
|
||||
"description": {
|
||||
"description": "Learn how a data scientist uses Azure Machine Learning (Azure ML) to train a model, then use the model for prediction. This tutorial will help you become familiar with the core concepts of Azure ML and their most common usage."
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.8 - AzureML",
|
||||
"display_name": "Python 3.10 - SDK V2",
|
||||
"language": "python",
|
||||
"name": "python38-azureml"
|
||||
"name": "python310-sdkv2"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
|
|
@ -818,4 +821,4 @@
|
|||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -676,10 +676,13 @@
|
|||
}
|
||||
],
|
||||
"metadata": {
|
||||
"description": {
|
||||
"description": "Prepare data, test and run a multi-node multi-gpu pytorch job. Use mlflow to analyze your metrics"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.8 - AzureML",
|
||||
"display_name": "Python 3.10 - SDK V2",
|
||||
"language": "python",
|
||||
"name": "python38-azureml"
|
||||
"name": "python310-sdkv2"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
|
|
@ -696,4 +699,4 @@
|
|||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1322,10 +1322,13 @@
|
|||
],
|
||||
"metadata": {
|
||||
"celltoolbar": "Edit Metadata",
|
||||
"description": {
|
||||
"description": "Create production ML pipelines with Python SDK v2 in a Jupyter notebook"
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.8.13 ('sdkv2')",
|
||||
"display_name": "Python 3.10 - SDK V2",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
"name": "python310-sdkv2"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
|
|
|
|||
|
|
@ -0,0 +1,35 @@
|
|||
---
|
||||
page_type: sample
|
||||
languages:
|
||||
- python
|
||||
products:
|
||||
- azure-machine-learning
|
||||
description: Top-level directory for official Azure Machine Learning Python SDK v2 tutorials.
|
||||
---
|
||||
|
||||
# Azure Machine Learning SDK (v2) end to end tutorials
|
||||
|
||||
[](https://github.com/psf/black)
|
||||
[](../LICENSE)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
1. An Azure subscription. If you don't have an Azure subscription, [create a free account](https://aka.ms/AMLFree) before you begin.
|
||||
|
||||
## Getting started
|
||||
|
||||
1. Install the SDK v2
|
||||
|
||||
```terminal
|
||||
pip install azure-ai-ml
|
||||
```
|
||||
|
||||
## Clone examples repository
|
||||
|
||||
```terminal
|
||||
git clone https://github.com/Azure/azureml-examples
|
||||
cd azureml-examples/tutorials
|
||||
```
|
||||
|
||||
## Examples available
|
||||
|
||||
|
|
@ -0,0 +1,398 @@
|
|||
# imports
|
||||
import contextlib
|
||||
import os
|
||||
import json
|
||||
import glob
|
||||
import argparse
|
||||
|
||||
from configparser import ConfigParser
|
||||
|
||||
# define constants
|
||||
ENABLE_MANUAL_CALLING = True # defines whether the workflow can be invoked or not
|
||||
NOT_TESTED_NOTEBOOKS = [] # cannot automate lets exclude
|
||||
NOT_SCHEDULED_NOTEBOOKS = [] # these are too expensive, lets not run everyday
|
||||
# define branch where we need this
|
||||
# use if running on a release candidate, else make it empty
|
||||
READONLY_HEADER = "# This code is autogenerated.\
|
||||
\n# Code is generated by running custom script: python3 readme.py\
|
||||
\n# Any manual changes to this file may cause incorrect behavior.\
|
||||
\n# Any manual changes will be overwritten if the code is regenerated.\n"
|
||||
BRANCH = "main" # default - do not change
|
||||
# BRANCH = "sdk-preview" # this should be deleted when this branch is merged to main
|
||||
GITHUB_CONCURRENCY_GROUP = (
|
||||
"${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}"
|
||||
)
|
||||
USE_FORECAST_REQUIREMENTS = "USE_FORECAST_REQUIREMENTS"
|
||||
COMPUTE_NAMES = "COMPUTE_NAMES"
|
||||
|
||||
|
||||
def main(args):
|
||||
|
||||
# get list of notebooks
|
||||
notebooks = sorted(glob.glob("**/*.ipynb", recursive=True))
|
||||
|
||||
for n in notebooks:
|
||||
print(n)
|
||||
|
||||
# write workflows
|
||||
write_workflows(notebooks)
|
||||
|
||||
# modify notebooks
|
||||
modify_notebooks(notebooks)
|
||||
|
||||
# write readme
|
||||
write_readme(notebooks)
|
||||
|
||||
# # write pipeline readme
|
||||
# pipeline_dir = "jobs" + os.sep + "pipelines" + os.sep
|
||||
# with change_working_dir(pipeline_dir):
|
||||
# pipeline_notebooks = sorted(glob.glob("**/*.ipynb", recursive=True))
|
||||
# pipeline_notebooks = [
|
||||
# f"{pipeline_dir}{notebook}" for notebook in pipeline_notebooks
|
||||
# ]
|
||||
# write_readme(pipeline_notebooks, pipeline_folder=pipeline_dir)
|
||||
|
||||
|
||||
def write_workflows(notebooks):
|
||||
print("writing .github/workflows...")
|
||||
cfg = ConfigParser()
|
||||
cfg.read(os.path.join("notebooks_config.ini"))
|
||||
for notebook in notebooks:
|
||||
if not any(excluded in notebook for excluded in NOT_TESTED_NOTEBOOKS):
|
||||
# get notebook name
|
||||
name = os.path.basename(notebook).replace(".ipynb", "")
|
||||
folder = os.path.dirname(notebook)
|
||||
classification = folder.replace(os.sep, "-")
|
||||
|
||||
enable_scheduled_runs = True
|
||||
if any(excluded in notebook for excluded in NOT_SCHEDULED_NOTEBOOKS):
|
||||
enable_scheduled_runs = False
|
||||
|
||||
# write workflow file
|
||||
write_notebook_workflow(
|
||||
notebook, name, classification, folder, enable_scheduled_runs, cfg
|
||||
)
|
||||
print("finished writing .github/workflows")
|
||||
|
||||
|
||||
def get_additional_requirements(req_name, req_path):
|
||||
return f"""
|
||||
- name: pip install {req_name} reqs
|
||||
run: pip install -r {req_path}"""
|
||||
|
||||
|
||||
def get_mlflow_import(notebook):
|
||||
with open(notebook, "r", encoding="utf-8") as f:
|
||||
if "import mlflow" in f.read():
|
||||
return get_additional_requirements(
|
||||
"mlflow", "sdk/python/mlflow-requirements.txt"
|
||||
)
|
||||
else:
|
||||
return ""
|
||||
|
||||
|
||||
def get_forecast_reqs(notebook_name, nb_config):
|
||||
is_required = int(
|
||||
nb_config.get(
|
||||
section=notebook_name, option=USE_FORECAST_REQUIREMENTS, fallback=0
|
||||
)
|
||||
)
|
||||
if is_required:
|
||||
return get_additional_requirements(
|
||||
"forecasting", "sdk/python/forecasting-requirements.txt"
|
||||
)
|
||||
else:
|
||||
return ""
|
||||
|
||||
|
||||
def write_notebook_workflow(
|
||||
notebook, name, classification, folder, enable_scheduled_runs, nb_config
|
||||
):
|
||||
is_pipeline_notebook = ("jobs-pipelines" in classification) or (
|
||||
"assets-component" in classification
|
||||
)
|
||||
creds = "${{secrets.AZUREML_CREDENTIALS}}"
|
||||
# Duplicate name in working directory during checkout
|
||||
# https://github.com/actions/checkout/issues/739
|
||||
github_workspace = "${{ github.workspace }}"
|
||||
mlflow_import = get_mlflow_import(notebook)
|
||||
forecast_import = get_forecast_reqs(name, nb_config)
|
||||
posix_folder = folder.replace(os.sep, "/")
|
||||
posix_notebook = notebook.replace(os.sep, "/")
|
||||
|
||||
workflow_yaml = f"""{READONLY_HEADER}
|
||||
name: tutorials-{classification}-{name}
|
||||
# This file is created by tutorials/readme.py.
|
||||
# Please do not edit directly.
|
||||
on:\n"""
|
||||
if ENABLE_MANUAL_CALLING:
|
||||
workflow_yaml += f""" workflow_dispatch:\n"""
|
||||
if enable_scheduled_runs:
|
||||
workflow_yaml += f""" schedule:
|
||||
- cron: "0 */8 * * *"\n"""
|
||||
workflow_yaml += f""" pull_request:
|
||||
branches:
|
||||
- main\n"""
|
||||
if BRANCH != "main":
|
||||
workflow_yaml += f""" - {BRANCH}\n"""
|
||||
if is_pipeline_notebook:
|
||||
workflow_yaml += " - pipeline/*\n"
|
||||
workflow_yaml += f""" paths:
|
||||
- tutorials/{posix_folder}/**
|
||||
- .github/workflows/tutorials-{classification}-{name}.yml
|
||||
- sdk/python/dev-requirements.txt
|
||||
- infra/**
|
||||
- sdk/python/setup.sh
|
||||
concurrency:
|
||||
group: {GITHUB_CONCURRENCY_GROUP}
|
||||
cancel-in-progress: true
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: check out repo
|
||||
uses: actions/checkout@v2
|
||||
- name: setup python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: "3.8"
|
||||
- name: pip install notebook reqs
|
||||
run: pip install -r sdk/python/dev-requirements.txt{mlflow_import}{forecast_import}
|
||||
- name: azure login
|
||||
uses: azure/login@v1
|
||||
with:
|
||||
creds: {creds}
|
||||
- name: bootstrap resources
|
||||
run: |
|
||||
echo '{GITHUB_CONCURRENCY_GROUP}';
|
||||
bash bootstrap.sh
|
||||
working-directory: infra
|
||||
continue-on-error: false
|
||||
- name: setup SDK
|
||||
run: |
|
||||
source "{github_workspace}/infra/sdk_helpers.sh";
|
||||
source "{github_workspace}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: sdk/python
|
||||
continue-on-error: true
|
||||
- name: setup-cli
|
||||
run: |
|
||||
source "{github_workspace}/infra/sdk_helpers.sh";
|
||||
source "{github_workspace}/infra/init_environment.sh";
|
||||
bash setup.sh
|
||||
working-directory: cli
|
||||
continue-on-error: true
|
||||
- name: run {posix_notebook}
|
||||
run: |
|
||||
source "{github_workspace}/infra/sdk_helpers.sh";
|
||||
source "{github_workspace}/infra/init_environment.sh";
|
||||
bash "{github_workspace}/infra/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
|
||||
bash "{github_workspace}/infra/sdk_helpers.sh" replace_template_values "{name}.ipynb";
|
||||
[ -f "../../.azureml/config" ] && cat "../../.azureml/config";"""
|
||||
|
||||
if name == "debug-online-endpoints-locally-in-visual-studio-code":
|
||||
workflow_yaml += f"""
|
||||
sed -i -e "s/<ENDPOINT_NAME>/localendpoint/g" {name}.ipynb
|
||||
|
||||
# Create a dummy executable for VSCode
|
||||
mkdir -p /tmp/code
|
||||
touch /tmp/code/code
|
||||
chmod +x /tmp/code/code
|
||||
export PATH="/tmp/code:$PATH"\n"""
|
||||
|
||||
if not ("automl" in folder):
|
||||
workflow_yaml += f"""
|
||||
papermill -k python {name}.ipynb {name}.output.ipynb
|
||||
working-directory: tutorials/{posix_folder}"""
|
||||
elif "nlp" in folder or "image" in folder:
|
||||
# need GPU cluster, so override the compute cluster name to dedicated
|
||||
workflow_yaml += f"""
|
||||
papermill -k python -p compute_name automl-gpu-cluster {name}.ipynb {name}.output.ipynb
|
||||
working-directory: tutorials/{posix_folder}"""
|
||||
else:
|
||||
# need CPU cluster, so override the compute cluster name to dedicated
|
||||
workflow_yaml += f"""
|
||||
papermill -k python -p compute_name automl-cpu-cluster {name}.ipynb {name}.output.ipynb
|
||||
working-directory: tutorials/{posix_folder}"""
|
||||
|
||||
workflow_yaml += f"""
|
||||
- name: upload notebook's working folder as an artifact
|
||||
if: ${{{{ always() }}}}
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: {name}
|
||||
path: tutorials/{posix_folder}\n"""
|
||||
|
||||
if nb_config.get(section=name, option=COMPUTE_NAMES, fallback=None):
|
||||
workflow_yaml += f"""
|
||||
- name: Remove the compute if notebook did not done it properly.
|
||||
run: bash "{github_workspace}/infra/remove_computes.sh" {nb_config.get(section=name, option=COMPUTE_NAMES)}\n"""
|
||||
|
||||
workflow_yaml += f"""
|
||||
- name: Send IcM on failure
|
||||
if: ${{{{ failure() && github.ref_type == 'branch' && (github.ref_name == 'main' || contains(github.ref_name, 'release')) }}}}
|
||||
uses: ./.github/actions/generate-icm
|
||||
with:
|
||||
host: ${{{{ secrets.AZUREML_ICM_CONNECTOR_HOST_NAME }}}}
|
||||
connector_id: ${{{{ secrets.AZUREML_ICM_CONNECTOR_CONNECTOR_ID }}}}
|
||||
certificate: ${{{{ secrets.AZUREML_ICM_CONNECTOR_CERTIFICATE }}}}
|
||||
private_key: ${{{{ secrets.AZUREML_ICM_CONNECTOR_PRIVATE_KEY }}}}
|
||||
args: |
|
||||
incident:
|
||||
Title: "[azureml-examples] Notebook validation failed on branch '${{{{ github.ref_name }}}}' for notebook '{posix_notebook}'"
|
||||
Summary: |
|
||||
Notebook '{posix_notebook}' is failing on branch '${{{{ github.ref_name }}}}': ${{{{ github.server_url }}}}/${{{{ github.repository }}}}/actions/runs/${{{{ github.run_id }}}}
|
||||
Severity: 4
|
||||
RoutingId: "github://azureml-examples"
|
||||
Status: Active
|
||||
Source:
|
||||
IncidentId: "{posix_notebook}[${{{{ github.ref_name }}}}]"\n"""
|
||||
|
||||
workflow_file = os.path.join(
|
||||
"..", ".github", "workflows", f"tutorials-{classification}-{name}.yml"
|
||||
)
|
||||
|
||||
workflow_before = ""
|
||||
if os.path.exists(workflow_file):
|
||||
with open(workflow_file, "r") as f:
|
||||
workflow_before = f.read()
|
||||
|
||||
if workflow_yaml != workflow_before:
|
||||
# write workflow
|
||||
with open(workflow_file, "w") as f:
|
||||
f.write(workflow_yaml)
|
||||
|
||||
|
||||
def write_readme(notebooks, pipeline_folder=None):
|
||||
prefix = "prefix.md"
|
||||
suffix = "suffix.md"
|
||||
readme_file = "README.md"
|
||||
if pipeline_folder:
|
||||
prefix = os.path.join(pipeline_folder, prefix)
|
||||
suffix = os.path.join(pipeline_folder, suffix)
|
||||
readme_file = os.path.join(pipeline_folder, readme_file)
|
||||
|
||||
if BRANCH == "":
|
||||
branch = "main"
|
||||
else:
|
||||
branch = BRANCH
|
||||
# read in prefix.md and suffix.md
|
||||
with open(prefix, "r") as f:
|
||||
prefix = f.read()
|
||||
with open(suffix, "r") as f:
|
||||
suffix = f.read()
|
||||
|
||||
# define markdown tables
|
||||
notebook_table = f"Test Status is for branch - **_{branch}_**\n|Title|Notebook|Description|Status|\n|--|--|--|--|\n"
|
||||
for notebook in notebooks:
|
||||
# get notebook name
|
||||
name = notebook.split(os.sep)[-1].replace(".ipynb", "")
|
||||
area = notebook.split(os.sep)[0]
|
||||
sub_area = notebook.split(os.sep)[1]
|
||||
folder = os.path.dirname(notebook)
|
||||
classification = folder.replace(os.sep, "-")
|
||||
|
||||
try:
|
||||
# read in notebook
|
||||
with open(notebook, "r") as f:
|
||||
data = json.load(f)
|
||||
|
||||
description = "*no description*"
|
||||
try:
|
||||
if data["metadata"]["description"] is not None:
|
||||
description = data["metadata"]["description"]["description"]
|
||||
except BaseException:
|
||||
pass
|
||||
except BaseException:
|
||||
print("Could not load", notebook)
|
||||
pass
|
||||
|
||||
if any(excluded in notebook for excluded in NOT_TESTED_NOTEBOOKS):
|
||||
description += " - _This sample is excluded from automated tests_"
|
||||
if any(excluded in notebook for excluded in NOT_SCHEDULED_NOTEBOOKS):
|
||||
description += " - _This sample is only tested on demand_"
|
||||
|
||||
if pipeline_folder:
|
||||
notebook = os.path.relpath(notebook, pipeline_folder)
|
||||
|
||||
# write workflow file
|
||||
notebook_table += (
|
||||
write_readme_row(
|
||||
branch,
|
||||
notebook.replace(os.sep, "/"),
|
||||
name,
|
||||
classification,
|
||||
area,
|
||||
sub_area,
|
||||
description,
|
||||
)
|
||||
+ "\n"
|
||||
)
|
||||
|
||||
print("writing README.md...")
|
||||
with open(readme_file, "w") as f:
|
||||
f.write(prefix + notebook_table + suffix)
|
||||
print("finished writing README.md")
|
||||
|
||||
|
||||
def write_readme_row(
|
||||
branch, notebook, name, classification, area, sub_area, description
|
||||
):
|
||||
gh_link = "https://github.com/Azure/azureml-examples/actions/workflows"
|
||||
|
||||
nb_name = f"[{name}]({notebook})"
|
||||
status = f"[]({gh_link}/tutorials-{classification}-{name}.yml)"
|
||||
|
||||
row = f"|{area}|{nb_name}|{description}|{status}|"
|
||||
return row
|
||||
|
||||
|
||||
def modify_notebooks(notebooks):
|
||||
print("modifying notebooks...")
|
||||
# setup variables
|
||||
kernelspec = {
|
||||
"display_name": "Python 3.10 - SDK V2",
|
||||
"language": "python",
|
||||
"name": "python310-sdkv2",
|
||||
}
|
||||
|
||||
# for each notebooks
|
||||
for notebook in notebooks:
|
||||
|
||||
# read in notebook
|
||||
with open(notebook, "r", encoding="utf-8") as f:
|
||||
data = json.load(f)
|
||||
|
||||
# update metadata
|
||||
data["metadata"]["kernelspec"] = kernelspec
|
||||
|
||||
# write notebook
|
||||
with open(notebook, "w", encoding="utf-8") as f:
|
||||
json.dump(data, f, indent=1, ensure_ascii=False)
|
||||
f.write("\n")
|
||||
|
||||
print("finished modifying notebooks...")
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def change_working_dir(path):
|
||||
"""Context manager for changing the current working directory"""
|
||||
|
||||
saved_path = os.getcwd()
|
||||
os.chdir(str(path))
|
||||
try:
|
||||
yield
|
||||
finally:
|
||||
os.chdir(saved_path)
|
||||
|
||||
|
||||
# run functions
|
||||
if __name__ == "__main__":
|
||||
|
||||
# setup argparse
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--check-readme", type=bool, default=False)
|
||||
args = parser.parse_args()
|
||||
|
||||
# call main
|
||||
main(args)
|
||||
|
|
@ -0,0 +1,12 @@
|
|||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions and suggestions! Please see the [contributing guidelines](../CONTRIBUTING.mdCONTRIBUTING.md) for details.
|
||||
|
||||
## Code of Conduct
|
||||
|
||||
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). Please see the [code of conduct](../CODE_OF_CONDUCT.md) for details.
|
||||
|
||||
## Reference
|
||||
|
||||
* [Documentation](https://docs.microsoft.com/azure/machine-learning)
|
||||
Загрузка…
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