if (dot.getDotDimensionNumbers() != first_dot.getDotDimensionNumbers())
      return rewriter.notifyMatchFailure(
          dot, "dot_general ops have different dimension numbers");
    if (dot.getPrecisionConfig() != first_dot.getPrecisionConfig())
      return rewriter.notifyMatchFailure(
          dot, "dot_general ops have different precision configs");
    if (!dot.getLhs().getType().hasStaticShape())

//===----------------------------------------------------------------------===//
// MatMul op patterns.
//===----------------------------------------------------------------------===//

def GetPrecisionConfig: NativeCodeCall<
  "GetPrecisionConfig(&$_builder)">;

def : Pat<(TF_MatMulOp $a, $b, $transpose_a, $transpose_b, $grad_a, $grad_b),
          (MHLO_DotOp
          (TF_TransposeOp $a, (TF_ConstOp (Get2DTransposePerm $transpose_a))),

        BufferOffset<flatbuffers::Vector<unsigned int>> precision_config = 0;
        if (vhlo_op.getPrecisionConfig()) {
          precision_config = BuildVhloPrecisionConfigV1(
              mlir::dyn_cast<mlir::vhlo::ArrayV1Attr>(
                  vhlo_op.getPrecisionConfig()));
        }

        auto convolution_option = tflite::CreateStablehloConvolutionOptions(

  if (axis < 0) {
    axis += rank;
  }
  return b->getI64IntegerAttr(axis);
}

// Returns a PrecisionConfig as an array attribute based on whether TF32
// execution is enabled
static ArrayAttr GetPrecisionConfig(Builder *builder) {
  mlir::mhlo::Precision precision = tsl::tensor_float_32_execution_enabled()
                                        ? mhlo::Precision::DEFAULT

        op.getWindowStrides(), op.getPadding(), op.getLhsDilation(),
        op.getRhsDilation(), op.getFeatureGroupCount(),
        op.getDimensionNumbers(), op.getPrecisionConfig(), 1);
    return ::mlir::success();
  };
};

void XlaConvOp::getCanonicalizationPatterns(RewritePatternSet &results,
                                            MLIRContext *context) {