input = rewriter.create<ReverseOp>(
          loc, input_ty, op.getInput(),
          GetI64ElementsAttr(dims_to_reverse, &rewriter));
    auto sliced = rewriter.create<SliceOp>(
        loc, input, GetI64ElementsAttr(hlo_begin_indices, &rewriter),
        GetI64ElementsAttr(hlo_end_indices, &rewriter),
        GetI64ElementsAttr(hlo_strides, &rewriter));

    // Reshape slice result so that the shape is updated depending on

}

DenseIntElementsAttr GetI64ElementsAttr(ArrayAttr attr) {
  RankedTensorType ty =
      RankedTensorType::get(static_cast<int64_t>(attr.size()),
                            IntegerType::get(attr.getContext(), 64));
  return DenseIntElementsAttr::get(ty, attr.getValue());
}

DenseIntElementsAttr GetI64ElementsAttr(ArrayRef<int64_t> values,

ConstantOp GetScalarNegZeroOfType(Type ty, Location loc, OpBuilder* builder);

// Converts an ArrayAttr to a 1D 64-bit dense elements attribute.
DenseIntElementsAttr GetI64ElementsAttr(ArrayAttr attr);
DenseIntElementsAttr GetI64ElementsAttr(llvm::ArrayRef<int64_t> values,
                                        Builder* builder);

}  // namespace mhlo
}  // namespace mlir

#include "tensorflow/core/util/tensor_format.h"

namespace mlir {
namespace TF {
namespace {

// Returns 1D 64-bit dense elements attribute with the given values.
static DenseIntElementsAttr GetI64ElementsAttr(ArrayRef<int64_t> values,
                                               Builder *builder) {
  RankedTensorType ty = tensorflow::GetTypeFromTFTensorShape(

def GetScalarNanOfType : NativeCodeCall<
  "GetScalarOfType(getElementTypeOrSelf($0), "
  "std::numeric_limits<double>::quiet_NaN())">;

class GetI64ScalarElementsAttr<int value> :
  NativeCodeCall<"GetI64ElementsAttr({" # value # "}, &$_builder)">;

class GetF32Scalar<int value> :
  NativeCodeCall<"GetF32Scalar(&$_builder, " # value # ")">;

def TrueBoolAttr : AttrConstraint<CPred<"$_self.cast<::mlir::BoolAttr>().getValue()">>;

        limit_indices[channel_idx] = depth_idx + 1;
      }
      return rewriter.create<mhlo::SliceOp>(
          conv_op.getLoc(), tensor,
          GetI64ElementsAttr(start_indices, &rewriter),
          GetI64ElementsAttr(limit_indices, &rewriter),
          GetI64ElementsAttr(strides, &rewriter));
    };

    // Storage for smaller convolution results
    std::vector<mlir::Value> conv_results;

  RankedTensorType ty = mlir::RankedTensorType::get(
      {static_cast<int32_t>(values.size())}, builder->getIntegerType(32));
  return DenseIntElementsAttr::get(ty, values);
}

DenseIntElementsAttr GetI64ElementsAttr(ArrayRef<int64_t> values,
                                        Builder *builder) {
  RankedTensorType ty = RankedTensorType::get(
      {static_cast<int64_t>(values.size())}, builder->getIntegerType(64));