Fix example by deleting bad steps_per_epoch value and associated TODO.
PiperOrigin-RevId: 238426188
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@ -103,16 +103,13 @@ def main(argv):
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fake_tiny_data=FLAGS.fast_test_mode)
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model.compile(loss=tf.keras.losses.categorical_crossentropy,
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optimizer=tf.keras.optimizers.SGD(),
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metrics=['accuracy'],
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# TODO(arnoegw): Remove after investigating huge allocs.
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run_eagerly=True)
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metrics=['accuracy'])
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print('Training on %s with %d trainable and %d untrainable variables.' %
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('Fashion MNIST' if FLAGS.use_fashion_mnist else 'MNIST',
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len(model.trainable_variables), len(model.non_trainable_variables)))
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model.fit(x_train, y_train,
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batch_size=128,
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epochs=FLAGS.epochs,
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steps_per_epoch=3,
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verbose=1,
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validation_data=(x_test, y_test))
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