Abstract

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

Requirements

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

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