Function separable_conv2d_shape

tensorflow/python/framework/common_shapes.py:293–353

Shape function for a SeparableConv2D op. This op has three inputs: * input, a 4D tensor with shape = [batch_size, rows, cols, depth_in] * depthwise_filter, a 4D tensor with shape = [filter_rows, filter_cols, depth_in, depth_multiplier] * pointwise_filter, a 4D tensor with shape = [1,

(op)

def separable_conv2d_shape(op):
  """Shape function for a SeparableConv2D op.

  This op has three inputs:

  * input, a 4D tensor with shape = [batch_size, rows, cols, depth_in]

  * depthwise_filter, a 4D tensor with shape = [filter_rows,
    filter_cols, depth_in, depth_multiplier]

  * pointwise_filter, a 4D tensor with shape = [1, 1, depth_in *
    depth_multiplier, depth_out]

  The output is a 4D tensor with shape = [batch_size, out_rows,
  out_cols, depth_out], where out_rows and out_cols depend on the
  value of the op's "padding" and "strides" attrs.

  Args:
    op: A SeparableConv2D Operation.

  Returns:
    A list containing the Shape of the SeparableConv2D output.

  Raises:
    ValueError: If the shapes of the input or filter are incompatible.
  """
  input_shape = op.inputs[0].get_shape().with_rank(4)
  depthwise_filter_shape = op.inputs[1].get_shape().merge_with(
      tensor_shape.TensorShape([None, None, input_shape[3], None]))
  pointwise_depth_in = depthwise_filter_shape[2] * depthwise_filter_shape[3]

  pointwise_filter_shape = op.inputs[2].get_shape().merge_with(
      tensor_shape.TensorShape([1, 1, pointwise_depth_in, None]))

  batch_size = input_shape[0]
  in_rows = input_shape[1]
  in_cols = input_shape[2]

  filter_rows = depthwise_filter_shape[0]
  filter_cols = depthwise_filter_shape[1]
  depth_out = pointwise_filter_shape[3]

  stride_b, stride_r, stride_c, stride_d = op.get_attr("strides")
  if stride_b != 1 or stride_d != 1:
    raise ValueError("Current implementation does not yet support "
                     "strides in the batch and depth dimensions.")
  if stride_r != stride_c:
    # TODO(shlens): Add support for this.
    raise ValueError("Current implementation only supports equal length "
                     "strides in the row and column dimensions.")

  # TODO(mrry,shlens): Raise an error if the stride would cause
  # information in the input to be ignored. This will require a change
  # in the kernel implementation.
  stride = stride_r
  padding = op.get_attr("padding")
  out_rows, out_cols = get2d_conv_output_size(in_rows, in_cols, filter_rows,
                                              filter_cols, stride, stride,