3a5cea5d75447d9beea3a2b71e67aaaad9698f0c,kfac/examples/autoencoder_mnist.py,,get_keras_autoencoder,#,263

Before Change

  // Create Encoder
  model.add(layers.Input(**input_kwargs))
  for size in _ENCODER_SIZES[:-1]:
    model.add(layers.Dense(
        size, activation=_NONLINEARITY, **dense_kwargs))
  model.add(layers.Dense(_ENCODER_SIZES[-1], **dense_kwargs))

  // Create Decoder
  for size in _DECODER_SIZES:

After Change

  else:
    // Make sure you always wrap the input in keras
    inputs = layers.Input(**input_kwargs)

    x = inputs
    // Create Encoder
    for size in _ENCODER_SIZES[:-1]:
      x = layers.Dense(size, activation=_NONLINEARITY, **dense_kwargs)(x)
    x = layers.Dense(_ENCODER_SIZES[-1], **dense_kwargs)(x)

    // Create Decoder
    for size in _DECODER_SIZES:
      x = layers.Dense(size, activation=_NONLINEARITY, **dense_kwargs)(x)
    x = layers.Dense(784, **dense_kwargs)(x)

    model = tf.keras.Model(inputs=inputs, outputs=x)

  return model

Instances