#include "mlir/IR/PatternMatch.h"  // from @llvm-project
#include "tsl/platform/statusor.h"

namespace mlir {
namespace TFL {

// Returns a Constant op with a single value.
absl::StatusOr<arith::ConstantOp> CreateConstOpWithSingleValue(
    PatternRewriter* rewriter, Location loc, ShapedType shaped_type, int value);

// Returns a Constant op with a splat vector value.
absl::StatusOr<arith::ConstantOp> CreateConstOpWithVectorValue(

  return rewriter->create<arith::ConstantOp>(loc, dense_type,
                                             cast<TypedAttr>(*attr));
}

absl::StatusOr<arith::ConstantOp> CreateConstOpWithSingleValue(
    PatternRewriter* rewriter, Location loc, ShapedType shaped_type,
    int value) {
  ShapedType scalar_type =
      RankedTensorType::get({}, shaped_type.getElementType());

    float val = 0.0;
    bias_attr = mlir::DenseFPElementsAttr::get(bias_type, val);
  } else {
    // TODO(renjieliu): Refactor this and share the logic with
    // CreateConstOpWithSingleValue. Also, make sure it works with QConst.
    return failure();
  }

  auto zero_bias = rewriter.create<TFL::ConstOp>(op->getLoc(), bias_attr);
  op->setOperand(bias_idx, zero_bias);

    // Expanded inputs.
    // Insert at -2 location.
    auto one_ele_type =
        tensorflow::GetTypeFromTFTensorShape({1}, rewriter.getIntegerType(32));
    auto minus_two = CreateConstOpWithSingleValue(&rewriter, rfft_op.getLoc(),
                                                  one_ele_type, -2);

    SmallVector<int64_t, 4> expanded_input_shape;
    SmallVector<int64_t, 4> expanded_output_shape;

    }

    Value mul_rhs_value;
    if (!output_type.hasRank() || (output_type.getNumDynamicDims() > 0)) {
      auto status_or_const_op =
          CreateConstOpWithSingleValue(&rewriter, loc, input_type, 1);
      if (!status_or_const_op.ok()) {
        return failure();
      }

      mul_rhs_value = rewriter.create<TFL::FillOp>(