887f94bd4f292778622304ba627727a6dacad43f,deepchem/models/tensorgraph/layers.py,Conv2D,create_tensor,#Conv2D#Any#Any#,1913

Before Change

      parent_tensor = tf.expand_dims(parent_tensor, 3)
    for reuse in (self._reuse, False):
      try:
        out_tensor = tf.contrib.layers.conv2d(
            parent_tensor,
            num_outputs=self.num_outputs,
            kernel_size=self.kernel_size,
            stride=self.stride,
            padding=self.padding,
            activation_fn=self.activation_fn,
            normalizer_fn=self.normalizer_fn,
            biases_initializer=self.biases_initializer(),
            weights_initializer=self.weights_initializer(),
            scope=self._get_scope_name(),
            reuse=reuse)
        break
      except ValueError:
        if reuse:
          // This probably means the variable hasn"t been created yet, so try again
          // with reuse set to false.
          continue
        raise
    if set_tensors:
      self._record_variable_scope(self.scope_name)
      self.out_tensor = out_tensor
    return out_tensor

After Change

      parent_tensor = tf.expand_dims(parent_tensor, 3)
    for reuse in (self._reuse, False):
      try:
        if tfe.in_eager_mode():
          if not self._built:
            self._layer = self._build_layer(False)
          layer = self._layer
        else:
          layer = self._build_layer(reuse)
        out_tensor = layer(parent_tensor)
        if self.normalizer_fn is not None:
          out_tensor = self.normalizer_fn(out_tensor)
        break
      except ValueError:
        if reuse:
          // This probably means the variable hasn"t been created yet, so try again
          // with reuse set to false.
          continue
        raise
    if set_tensors:
      self._record_variable_scope(self.scope_name)
      self.out_tensor = out_tensor
    if tfe.in_eager_mode() and not self._built:
      self._built = True
      self.variables = self._layer.variables
    return out_tensor


class Conv3D(SharedVariableScope):

Instances