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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 > HYPERPARAMETERS > 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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