if (!padding_attr) {
      return {0, 0, 0, 0};
    }

    auto padding_values = padding_attr.getValues<int64_t>();
    // Padding has [[h_low, h_high], [w_low, w_high]] format.
    // https://github.com/openxla/stablehlo/blob/main/docs/spec.md#convolution.
    return {padding_values[0], padding_values[1], padding_values[2],
            padding_values[3]};
  }

  // Returns the input and output dimensions, respectively.

              /*align_corners=*/true, lhs_dilation_values[0], padding_values[0],
              window_strides_values[0], input_sizes[0], output_sizes[0])) {
        align_corners = true;
        return success();
      }
      if (can_convert_to_bilinear(
              /*align_corners=*/false, lhs_dilation_values[0],
              padding_values[0], window_strides_values[0], input_sizes[0],
              output_sizes[0])) {

  if (!paddings_op) return failure();

  auto paddings_value = paddings_op.getValue().dyn_cast<DenseElementsAttr>();
  if (!paddings_value ||
      paddings_value.getNumElements() != permutation.size() * 2)
    return failure();

  SmallVector<int32_t, 8> shuffled_paddings(paddings_value.getNumElements());
  for (const auto &index_pair :
       llvm::enumerate(paddings_value.getValues<APInt>())) {

  let arguments = (ins
     TFL_TensorOf<[I8, I16, I32, I64, UI8, UI16, UI32, UI64, F32, F64]>:$input,
     TFL_TensorOf<[I32]>:$dilations,
     TFL_0DTensorOf<[I8, I16, I32, I64, UI8, UI16, UI32, UI64, F32, F64]>:$padding_value
  );

  let results = (outs TFL_TensorOf<[I8, I16, I32, I64, UI8, UI16, UI32, UI64, F32, F64]>:$output);
}

def TFL_AddOp : TFL_Op<"add", [