message: Remove some overcautious comments from the port to 1.7+
diff: @@ -685,11 +685,9 @@ bool NGraphFusionVisitor::FuseAvgPoolBprop(HloInstruction* root) {
  // Given the TF convolution dimensions, attempts to reconstruct the data
  // format (NCHW or NHWC). Returns false if the dimensions are not consistent
  // with NCHW; otherwise, updates "data_format" by reference.
  -static bool ReconstructConvolutionDataFormat(
  +static bool ReconstructConvolutionDataFormatForBpropData(
  const ConvolutionDimensionNumbers& dnums,
  tensorflow::TensorFormat& data_format) {
  - // TODO(amprocte): we're checking input_* now, whereas previously there was
  - // only one set of parameters corresponding to both input and output.
  if (dnums.input_batch_dimension() == 0 &&
  dnums.input_feature_dimension() == 1) {
  data_format = tensorflow::FORMAT_NCHW;
  @@ -866,8 +864,6 @@ bool NGraphFusionVisitor::FuseConvolutionBpropData(HloInstruction* root) {
  // of TF's usual HWio.
  const ConvolutionDimensionNumbers& dims =
  root->convolution_dimension_numbers();
  - // TODO(amprocte): we're checking input_* now, whereas previously there was
  - // only one set of parameters corresponding to both input and output.
  size_t num_spatial_dims = dims.input_spatial_dimensions().size();
  if (dims.kernel_output_feature_dimension() != int64(num_spatial_dims) ||
  @@ -879,7 +875,7 @@ bool NGraphFusionVisitor::FuseConvolutionBpropData(HloInstruction* root) {
  // we can't.
  tensorflow::TensorFormat data_format; // returned by reference
  - if (!ReconstructConvolutionDataFormat(dims, data_format)) {
  + if (!ReconstructConvolutionDataFormatForBpropData(dims, data_format)) {
  return false;
  }
  @@ -997,8 +993,6 @@ static bool TransposeDimensionsMatchConvFilterBpropOutput(
  static bool ReconstructConvolutionDataFormatForBpropFilters(
  const ConvolutionDimensionNumbers& dnums,
  tensorflow::TensorFormat& data_format) {
  - // TODO(amprocte): we're checking input_* now, whereas previously there was
  - // only one set of parameters corresponding to both input and output.
  if (dnums.input_feature_dimension() == 0 &&
  dnums.input_batch_dimension() == 1) {
  data_format = tensorflow::FORMAT_NCHW;
  @@ -1109,8 +1103,6 @@ bool NGraphFusionVisitor::FuseConvolutionBpropFilters(HloInstruction* root) {
  size_t input_first_spatial_axis =
  (data_format == tensorflow::FORMAT_NCHW ? 2 : 1);
  - // TODO(amprocte): we're checking input_* now, whereas previously there was
  - // only one set of parameters corresponding to both input and output.
  size_t num_spatial_dims = dims.input_spatial_dimensions().size();
  for (size_t i = 0; i < num_spatial_dims; i++) {
  