rebar.py 文件源码

def _create_baseline(self, n_output=1, n_hidden=100,
                       is_zero_init=False,
                       collection='BASELINE'):
    # center input
    h = self._x
    if self.mean_xs is not None:
      h -= self.mean_xs

    if is_zero_init:
      initializer = init_ops.zeros_initializer()
    else:
      initializer = slim.variance_scaling_initializer()

    with slim.arg_scope([slim.fully_connected],
                        variables_collections=[collection, Q_COLLECTION],
                        trainable=False,
                        weights_initializer=initializer):
      h = slim.fully_connected(h, n_hidden, activation_fn=tf.nn.tanh)
      baseline = slim.fully_connected(h, n_output, activation_fn=None)

      if n_output == 1:
        baseline = tf.reshape(baseline, [-1])  # very important to reshape
    return baseline