01a2b5fcd6151bb7264607ef71945eee95b73ea4,deepchem/models/layers.py,DAGGather,build,#DAGGather#Any#,3082

Before Change

            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:

After Change

    init = initializers.get(self.init)
    prev_layer_size = self.n_graph_feat
    for layer_size in self.layer_sizes:
      self.W_list.append(init([prev_layer_size, layer_size]))
      self.b_list.append(backend.zeros(shape=[
          layer_size,
      ]))

Instances