int padding_after = padding_before + offset;
      padding_values[2 * i] = padding_before;
      padding_values[2 * i + 1] = padding_after;
    }
  }

  if (input_zp_value == 0 ||
      absl::c_all_of(padding_values, [](int v) { return v == 0; })) {
    padding = CreateConstValue<int32_t>(
        builder, loc, {num_dims - 2, 2},
        SmallVector<int32_t>(padding_values.begin() + 2,

      CompileTimeConstantOperand<TF::ListDiffOp, 0, 1>,  // $x, $y
      // $k, $padding_value
      CompileTimeConstantOperand<TF::MatrixDiagPartV3Op, 1, 2>,
      // $k, $num_rows, $num_cols, $padding_value
      CompileTimeConstantOperand<TF::MatrixDiagV2Op, 1, 2, 3, 4>,
      // $k, $num_rows, $num_cols, $padding_value
      CompileTimeConstantOperand<TF::MatrixDiagV3Op, 1, 2, 3, 4>,

  // Verify padding_value is a tensor with all 0s.
  mlir::Value padding_value = tf_matrix_diag_v2_or_v3_op.getPaddingValue();
  mlir::Type element_type =
      mlir::cast<ShapedType>(padding_value.getType()).getElementType();
  if (mlir::isa<FloatType>(element_type)) {
    DenseFPElementsAttr padding_attr;
    if (!matchPattern(padding_value, m_Constant(&padding_attr)) ||

  auto padding_type =
      RankedTensorType::get({4, 2}, builder->getIntegerType(32));
  auto paddings = DenseIntElementsAttr::get(padding_type, values);
  auto paddings_value = builder->create<TF::ConstOp>(filter.getLoc(), paddings);
  std::vector<int64_t> pad_shape = {filter_shape[0] + pad_h,
                                    filter_shape[1] + pad_w, filter_shape[2],