message: Fix example by deleting bad steps_per_epoch value and associated TODO.
diff: @@ -103,16 +103,13 @@ def main(argv):
  fake_tiny_data=FLAGS.fast_test_mode)
  model.compile(loss=tf.keras.losses.categorical_crossentropy,
  optimizer=tf.keras.optimizers.SGD(),
  - metrics=['accuracy'],
  - # TODO(arnoegw): Remove after investigating huge allocs.
  - run_eagerly=True)
  + metrics=['accuracy'])
  print('Training on %s with %d trainable and %d untrainable variables.' %
  ('Fashion MNIST' if FLAGS.use_fashion_mnist else 'MNIST',
  len(model.trainable_variables), len(model.non_trainable_variables)))
  model.fit(x_train, y_train,
  batch_size=128,
  epochs=FLAGS.epochs,
  - steps_per_epoch=3,
  verbose=1,
  validation_data=(x_test, y_test))
  