pipelinelocalrun 0.2.0

Package to support pipeline local run

AML Pipeline Local Run Guide

This repository contains sdk code to run aml pipeline locally. So far there are 2 job running modes supported in pipeline local run:

• Native: this mode means run the job in native process
• Container: this mode the local pipeline executor will help building the container based on the environment defined in pipeline job component.

limitations:

• Only support CommandJob (SweepJob and DistributedJob are not supported)
• Pure local run with local metrics/UI support (need to run local server container if want to see ui)

project structure

• piprunengine: main pkg for pipeline local executor
• tests: unit test to run all sample pipelines (defined in notebookxx)
• notebookxx: unit test pipeline definition and related resources.

prerequisites

• Docker
• azure ml devplat-v2 sdk
• python version > 3.7

How to run it

1.1 clone this repo to local

1.2 create a new python env with conda

conda create -n <local_run_env> python=3.9

1.3 install the local run sdk

find the latest wheel in release folder and install it in the new created env

pip install pipelinelocalrun==0.1.9

1.4 install jupyter if want to run in notebook

pip install jupyter

1.5 start local web server if want to try local ui & mlflow (optional)

docker run -e AML_LOCAL_RUN_DB_PATH="/metadata/localrun.db" -e LOCALUI_START=true -p 127.0.0.1:4999:80/tcp -p 127.0.0.1:8080:8080/tcp -p 127.0.0.1:3001:3001/tcp -p 127.0.0.1:5000:5000/tcp --mount type=bind,source='<current-user-home-path>\.azureml\piprun',target=/metadata <image_name:tag>

<current-user-home-path>:

• for windows: C:\Users\<username>
• for linux: /home/<username>

<image_name:tag> is the image built in step 2.4

1.6 how to use in code/notebook

• import the local run func from the install pkg

  from piprunengine import run
  

• following the normal steps in the notebook to build your pipeline(you can ignore all steps which need interaction with aml workspace)

• start pipeline local run

  output_root_dir = "./local-run-output/notebook_1a_native"
  # set pipeline name
  pipeline.name="test-pipeline"
  run(output_root_dir=output_root_dir, job=pipeline, experiment_name="test")
  

  note: by default it runs in CONTAINER mode and it will build the curated container locally and run in container mode.

1.7 try with notebook demo

• notebook1a/pipeline_with_components_from_yaml.ipynb
• notebook1b/pipeline_with_python_function_components.ipynb
• notebook2c/nyc_taxi_data_regression.ipynb
• notebook1d/pipeline_with_non_python_components.ipynb

Contributing

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [e-mail] with any additional questions or comments.

Trademarks

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