mlir::Type type, const std::string& name);

  // Builds TF::VariantType from the given element type. Returns std::nullopt if
  // failure. Returns empty vector if the element type is not TF::VariantType or
  // there is empty TensorType in the TF::VariantType.
  std::optional<std::vector<BufferOffset<tflite::VariantSubType>>>
  BuildTFVariantType(mlir::Type element_type);

      TF_RETURN_IF_ERROR(
          ConvertDataType(element_dtype->type(), builder, &etype));
    }
    return GetTypeFromTFTensorShape(
        {}, mlir::TF::VariantType::get({mlir::UnrankedTensorType::get(etype)},
                                       etype.getContext()));
  }

  if (node.IsWhileNode()) {
    auto* output_shapes = node.attrs().Find("output_shapes");

  DCOMMENT("InferShapeForListInitOps " << *op << " could be inferred "
                                       << element_type);
  if (!element_type || !element_type.hasStaticShape()) return false;
  auto variant_type = VariantType::get(element_type, op->getContext());
  auto tensor_type = tensorflow::GetTypeFromTFTensorShape({}, variant_type);
  bool changed = RefineResultType(op, handle, tensor_type);

OpFoldResult TensorListElementShapeOp::fold(FoldAdaptor) {
  int width =
      getType().cast<ShapedType>().getElementType().getIntOrFloatBitWidth();
  auto variant_type =
      getElementTypeOrSelf(getOperand().getType()).cast<TF::VariantType>();
  if (variant_type.getSubtypes().empty()) return {};
  return ConvertShapeToAttr(variant_type.getSubtypes()[0], width);
}

//===----------------------------------------------------------------------===//