MLflow and PyTorch

PyTorch is a Python package that provides GPU accelerated tensor computation and high level functionalities for building deep learning networks.

The following notebook fits a neural network on MNIST handwritten digit recognition data. The run results are logged to an MLflow server. Training metrics and weights in TensorFlow event format are logged locally and then uploaded to the MLflow run’s artifact directory.

TensorBoard is started and reads the events logged locally. If you want TensorBoard to read the artifacts uploaded to S3, follow the instructions in How to run TensorFlow on S3.