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TensorFlow (tf.keras) Fashion MNIST Tutorial

This tutorial shows how to build a simple CNN on the MNIST dataset using Determined's tf.keras API. This example is adapted from this Keras image classification tutorial.

Files

  • model_def.py: The core code for the model. This includes building and compiling the model.
  • data.py: The data loading and preparation code for the model.

Configuration Files

  • const.yaml: Train the model with constant hyperparameter values.
  • distributed.yaml: Same as const.yaml, but trains the model with multiple GPUs (distributed training).
  • adaptive.yaml: Perform a hyperparameter search using Determined's state-of-the-art adaptive hyperparameter tuning algorithm.

Data

The current implementation downloads the Fashion MNIST data from here.

To Run

If you have not yet installed Determined, installation instructions can be found under docs/install-admin.html or at https://docs.determined.ai/latest/index.html

Run the following command: det -m <master host:port> experiment create -f const.yaml .. The other configurations can be run by specifying the appropriate configuration file in place of const.yaml.

Results

Training the model with the hyperparameter settings in const.yaml should yield a validation accuracy of ~85%.