message: Exposes explicit padding argument in tf.nn.conv2d_transpose.
diff: @@ -2526,8 +2526,13 @@ def conv2d_transpose_v2(
  value is given it is replicated in the `H` and `W` dimension. By default
  the `N` and `C` dimensions are set to 0. The dimension order is determined
  by the value of `data_format`, see below for details.
  - padding: A string, either `'VALID'` or `'SAME'`. The padding algorithm. See
  - the "returns" section of `tf.nn.convolution` for details.
  + padding: Either the `string `"SAME"` or `"VALID"` indicating the type of
  + padding algorithm to use, or a list indicating the explicit paddings at
  + the start and end of each dimension. When explicit padding is used and
  + data_format is `"NHWC"`, this should be in the form `[[0, 0], [pad_top,
  + pad_bottom], [pad_left, pad_right], [0, 0]]`. When explicit padding used
  + and data_format is `"NCHW"`, this should be in the form `[[0, 0], [0, 0],
  + [pad_top, pad_bottom], [pad_left, pad_right]]`.
  data_format: A string. 'NHWC' and 'NCHW' are supported.
  dilations: An int or list of `ints` that has length `1`, `2` or `4`,
  defaults to 1. The dilation factor for each dimension of`input`. If a
  @@ -2561,6 +2566,7 @@ def conv2d_transpose_v2(
  strides = _get_sequence(strides, 2, channel_index, "strides")
  dilations = _get_sequence(dilations, 2, channel_index, "dilations")
  + padding, explicit_paddings = convert_padding(padding)
  return gen_nn_ops.conv2d_backprop_input(
  input_sizes=output_shape,
  @@ -2568,6 +2574,7 @@ def conv2d_transpose_v2(
  out_backprop=input,
  strides=strides,
  padding=padding,
  + explicit_paddings=explicit_paddings,
  data_format=data_format,
  dilations=dilations,
  name=name)
  