const auto values = GetPadOpPaddingValues(pool);

  llvm::SmallVector<int32_t> padding_vec(8, 0);  // NHWC
  for (auto [ind, val] : llvm::enumerate(values)) {
    padding_vec[ind + 2] = val;
  }

  auto padding_shape = RankedTensorType::get({4, 2}, builder.getI32Type());
  return DenseIntElementsAttr::get(padding_shape, padding_vec);
}

ShapedType GetPadOpType(CompositeOp op) {

func.func @commute_transpose_pad(
      %arg0: tensor<1x112x112x64xf32>, %padding_val: tensor<f32>)
      -> tensor<1x64x114x114xf32> {
  %tspos = stablehlo.transpose %arg0, dims = [0, 3, 1, 2]
      : (tensor<1x112x112x64xf32>) -> tensor<1x64x112x112xf32>
  %ret = stablehlo.pad %tspos, %padding_val,
      low = [0, 0, 1, 1], high = [0, 0, 1, 1], interior = [0, 0, 0, 0]

                                     ArrayRef<int32_t> padding_val,
                                     int *mask) const {
    for (const auto &idx : dense_elem_attr.getValues<APInt>()) {
      val.push_back(idx.getSExtValue());
      padded_val.push_back(idx.getSExtValue());
    }
    int attr_dim_count = val.size();
    int full_dim_count = padding_val.size();
    for (int i = attr_dim_count; i < full_dim_count; ++i) {