Method d_forward

unsupervised_class3/dcgan_tf.py:301–310

(self, X, reuse=None, is_training=True)

  def d_forward(self, X, reuse=None, is_training=True):
    # encapsulate this because we use it twice
    output = X
    for layer in self.d_convlayers:
      output = layer.forward(output, reuse, is_training)
    output = tf.contrib.layers.flatten(output)
    for layer in self.d_denselayers:
      output = layer.forward(output, reuse, is_training)
    logits = self.d_finallayer.forward(output, reuse, is_training)
    return logits


  def build_generator(self, Z, g_sizes):