message: Use cudnn for grouped backward input convolution.
  Previously we didn't enable this code because it looked like
  we had some benchmark regressions. It turns out this was just
  noise.
diff: @@ -321,38 +321,11 @@ MatchBackwardInput(HloInstruction* conv) {
  const auto no_match_result =
  std::make_tuple(false, Window(), ConvolutionDimensionNumbers(), nullptr);
  - // TODO: Theoretically cuDNN supports grouped convolutions also
  - // for the backward input convolution, but based on the cudnn's current state
  - // there is not much performance improvement when using the
  - // cudnn backward input API for grouped conv.
  - // This needs to be re-evaluated for future cuDNN versions.
  - // Note that we already have the necessary code down below, the only thing to
  - // enable it is to remove the following early return.
  - if (conv->feature_group_count() > 1) {
  - return no_match_result;
  - }
  -
  // Match instruction pattern.
  CHECK_EQ(HloOpcode::kConvolution, conv->opcode());
  HloInstruction* reverse_filter = conv->mutable_operand(1);
  ConvolutionDimensionNumbers dnums = conv->convolution_dimension_numbers();
  - // Match BackwardInput for a depthwise convolution and thunk it to forward
  - // convolution Output feature dimension and input feature dimension has been
  - // swapped in the bridge. Hence to get the actual input features we need to
  - // query the output feature dimension
  - auto kernel_out_feature_dim = dnums.kernel_output_feature_dimension();
  - auto kernel_out_features =
  - reverse_filter->shape().dimensions(kernel_out_feature_dim);
  -
  - // For a depthwise convolution, the input features must be equal to the
  - // feature_group_count. We can leverage this property to match a depthwise
  - // convolution and thunk it to forward conv
  - if (conv->feature_group_count() > 1 &&
  - kernel_out_features == conv->feature_group_count()) {
  - return no_match_result;
  - }
  -
  // We pattern-match to a backwards input conv if:
  //
  // - all spatial dims of the filter are reversed
  