message: minor change per Penporn's code review suggestion
diff: @@ -581,7 +581,7 @@ class MklConvOp : public OpKernel {
  : TFDataFormatToMklDnn3DDataFormat(data_format_);
  auto mkl_fmt_tag = MklTensorFormatToMklDnnDataFormat(tf_fmt);
  - // NOTE: 'mkl_fmt_tag` will be `format_tag::undef` for ReLU
  + // NOTE: `mkl_fmt_tag` will be `format_tag::undef` for ReLU
  OP_REQUIRES(context, mkl_fmt_tag != memory::format_tag::undef,
  errors::InvalidArgument("Invalid data format"));
  @@ -873,8 +873,7 @@ class MklConvOp : public OpKernel {
  if (!native_format && add_mkl_shape == *output_mkl_shape &&
  ForwardMklTensorInToOutWithMklShape(context, kInputIndex_Add,
  kOutputIndex_Dst, output_tensor,
  - add_mkl_shape, false) &&
  - !native_format) {
  + add_mkl_shape, false)) {
  return;
  } else {
  AllocateOutputSetMklShape(context, kOutputIndex_Dst, output_tensor,
  @@ -1127,7 +1126,7 @@ class MklConvOp : public OpKernel {
  const Tensor& cached_filter_md =
  *cached_filter_md_ptensor_.AccessTensor(context);
  - // Check if the memory descriptor of the cached weights is same as
  + // Check if the memory descriptor of the cached weights is the same as
  // filter_md. If so, we can use the cached weights; otherwise
  // return nullptr.
  if (filter_md == *static_cast<memory::desc*>(cached_filter_md.data())) {
  @@ -1701,17 +1700,18 @@ class MklQuantizedConv2DSumReluOp
  // if summand_type is also DT_QUINT8 as the scale_output,
  // the scaling factor of 255.0f cancels each other and thus is avoided.
  // If it is not then it is DT_INT8 and is scaled appropriately.
  - if (summand_type == DT_QUINT8)
  + if (summand_type == DT_QUINT8) {
  params.post_op_params.push_back({"sum",
  mkldnn::algorithm::undef,
  {scale_summand / scale_output},
  ""});
  - else
  + } else {
  params.post_op_params.push_back(
  {"sum",
  mkldnn::algorithm::undef,
  {255.0f * scale_summand / (scale_output * 127.0f)},
  ""});
  + }
  } else {
  params.post_op_params.push_back(
  {"sum", mkldnn::algorithm::undef, {1.0}, ""});
  