f1df735684946dbbcefe41e41c7b1c3f2f751a07,deepchem/models/tensorgraph/layers.py,Dense,create_tensor,#Dense#Any#Any#,203

Before Change

    else:
      biases_initializer = self.biases_initializer()
    if not self.time_series:
      out_tensor = tf.contrib.layers.fully_connected(
          parent,
          num_outputs=self.out_channels,
          activation_fn=self.activation_fn,
          biases_initializer=biases_initializer,
          weights_initializer=self.weights_initializer(),
          scope=self._get_scope_name(),
          reuse=self._reuse,
          trainable=True)
    else:
      dense_fn = lambda x: tf.contrib.layers.fully_connected(x,
                                                             num_outputs=self.out_channels,
                                                             activation_fn=self.activation_fn,
                                                             biases_initializer=biases_initializer,
                                                             weights_initializer=self.weights_initializer(),
                                                             scope=self._get_scope_name(),
                                                             reuse=self._reuse,
                                                             trainable=True)
      out_tensor = tf.map_fn(dense_fn, parent)
    if set_tensors:
      self.variables = tf.get_collection(
          tf.GraphKeys.GLOBAL_VARIABLES, scope=self._get_scope_name())
      self.out_tensor = out_tensor
    return out_tensor

After Change

      biases_initializer = None
    else:
      biases_initializer = self.biases_initializer()
    for reuse in (self._reuse, False):
      dense_fn = lambda x: tf.contrib.layers.fully_connected(x,
                                                             num_outputs=self.out_channels,
                                                             activation_fn=self.activation_fn,

Instances