23747136a68f87c72d496477cc6a2d85cef993c4,deepchem/models/layers.py,DAGLayer,build,#DAGLayer#Any#,2946

Before Change

      else:
        self.dropouts.append(None)
      prev_layer_size = layer_size
    self.W_list.append(init([prev_layer_size, self.n_outputs]))
    self.b_list.append(backend.zeros(shape=[
        self.n_outputs,
    ]))

After Change

        self.dropouts.append(None)
      prev_layer_size = layer_size
    self.W_list.append(
        self.add_weight(
            name="kernel",
            shape=(prev_layer_size, self.n_outputs),
            initializer=self.init,
            trainable=True))
    self.b_list.append(
        self.add_weight(
            name="bias",
            shape=(self.n_outputs,),
            initializer="zeros",
            trainable=True))
    if self.dropout is not None and self.dropout > 0.0:
      self.dropouts.append(Dropout(rate=self.dropout))
    else:

Instances