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TensorFlow MNIST

The tensorflow_mnist.py example demonstrates the integration of ClearML into code that uses TensorFlow and Keras to train a neural network on the Keras built-in MNIST handwritten digits dataset.

When the script runs, it creates an experiment named Tensorflow v2 mnist with summaries in the examples project.

Scalars

The loss and accuracy metric scalar plots appear in the experiment's page in the ClearML web UI under SCALARS. Resource utilization plots, which are titled :monitor: machine, also appear in the SCALARS tab.

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Hyperparameters

ClearML automatically logs TensorFlow Definitions. They appear in CONFIGURATION > HYPER PARAMETERS > TF_DEFINE.

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Console

All console output appears in CONSOLE.

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Artifacts

Models created by the experiment appear in the experiment’s ARTIFACTS tab. ClearML automatically logs and tracks models and any snapshots created using TensorFlow.

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Clicking on a model’s name takes you to the model’s page, where you can view the model’s details and access the model.

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