message: Conv2DTranspose uses constant height and width when possible.
diff: @@ -1182,7 +1182,18 @@ class Conv2DTranspose(Conv2D):
  else:
  h_axis, w_axis = 1, 2
  - height, width = inputs_shape[h_axis], inputs_shape[w_axis]
  + # Use the constant height and weight when possible.
  + # TODO(scottzhu): Extract this into a utility function that can be applied
  + # to all convolutional layers, which currently lost the static shape
  + # information due to tf.shape().
  + height, width = None, None
  + if inputs.shape.rank is not None:
  + dims = inputs.shape.as_list()
  + height = dims[h_axis]
  + width = dims[w_axis]
  + height = height if height is not None else inputs_shape[h_axis]
  + width = width if width is not None else inputs_shape[w_axis]
  +
  kernel_h, kernel_w = self.kernel_size
  stride_h, stride_w = self.strides
  