deng/test_mlflow
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test_mlflow
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train a simple Pytorch model to test the MLflow lib
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README.md

Abstract

Try to use MLflow platform to log PyTorch model training, and pull production model from model registry to run inference⛩

Requirements

  • MacOS 12.5
  • Docker 20.10

Dir

  • service
    • House MLflow service data, including MLflow artifacts, backend store and model registry

Files

  • conda.yaml
    • conda env yaml to run this repo
  • start_mlflow_server.sh
    • a script to start MLflow server with basic configuration
  • test_pytorch_m1.py
    • a script to test PyTorch on Apple M1 platform with GPU acceleration
  • train.py
    • a sample code to apply PyTorch to train a small neural network to predict fortune with MLflow logging
  • predict.py
    • a sample code to call registered model to predict testing data and save model to local file system
  • get_registered_model_via_rest_api.py
    • a script to test MLflow REST api
tags: MLOps