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MegEngine

The megengine_mnist.py example demonstrates the integration of ClearML into code that uses MegEngine and TensorBoardX. ClearML automatically captures models saved with megengine.

The example script does the following:

  • Trains a simple deep neural network on MegEngine's built-in MNIST dataset.
  • Creates a TensorBoardX SummaryWriter object to log scalars during training.
  • Creates a ClearML experiment named megengine mnist train, which is associated with the examples project.

Hyperparameters

ClearML automatically logs command line options defined with argparse. They appear in the experiment's CONFIGURATION tab under HYPER PARAMETERS > Args.

Configuration tab

Scalars

The example script's train function calls TensorBoardX's SummaryWriter.add_scalar method to report loss. ClearML automatically captures the data that is added to the SummaryWriter object.

These scalars can be visualized in plots, which appear in the ClearML WebApp, in the experiment's SCALARS tab.

Scalars tab

Models

ClearML automatically captures the model logged using the megengine.save method, and saves it as an artifact.

View saved snapshots in the experiment's ARTIFACTS tab.

Artifacts tab

To view the model details, click the model name in the ARTIFACTS page, which will open the model's info tab. Alternatively, download the model.

The model info panel contains the model details, including:

  • Model URL
  • Framework
  • Snapshot locations.

Model info panel

Console

All console output during the script’s execution appears in the experiment’s CONSOLE page. Console tab