for (BlockArgument& func_arg : func_args) {
    auto resource_type = mlir::dyn_cast<TF::ResourceType>(
        getElementTypeOrSelf(func_arg.getType()));
    if (!resource_type) continue;
    if (failed(ValidateResourceArgument(function, func_arg, resource_type)))
      return failure();

    add_resource_argument(func_arg, resource_type);
  }

    const auto resource_type = RankedTensorType::get(
        /*shape=*/{}, /*elementType=*/TF::ResourceType::get(
            /*subtypes=*/llvm::ArrayRef<TensorType>{const_op.getType()},
            builder.getContext()));
    auto var_handle_op =
        builder.create<TF::VarHandleOp>(const_op.getLoc(),
                                        /*resource=*/resource_type,

      auto resource_type =
          mlir::TF::ResourceType::get({resource_subtype}, builder.getContext());

      auto tensor_type = mlir::cast<mlir::TensorType>(mlir_arg.getType());
      if (tensor_type.hasRank()) {
        mlir_arg.setType(
            GetTypeFromTFTensorShape(tensor_type.getShape(), resource_type));
      } else {

  node_def->set_op(FunctionLibraryDefinition::kArgOp);

  mlir::TensorType arg_type = mlir::cast<mlir::TensorType>(arg.getType());
  if (auto resource_type =
          mlir::dyn_cast<mlir::TF::ResourceType>(arg_type.getElementType())) {
    llvm::ArrayRef<mlir::TensorType> subtypes = resource_type.getSubtypes();
    if (!subtypes.empty()) {
      AttrValue handle_dtypes_attr;
      AttrValue handle_shapes_attr;

  node_def->set_op(FunctionLibraryDefinition::kArgOp);

  mlir::TensorType arg_type = mlir::cast<mlir::TensorType>(arg.getType());
  if (auto resource_type =
          mlir::dyn_cast<mlir::TF::ResourceType>(arg_type.getElementType())) {
    llvm::ArrayRef<mlir::TensorType> subtypes = resource_type.getSubtypes();
    if (!subtypes.empty()) {
      AttrValue handle_dtypes_attr;
      AttrValue handle_shapes_attr;

							}
						}
						dumps[resourceType] = append(dumps[resourceType], &discoveryv3.Resource{
							Name:     w.Config.Name,
							Resource: protoconv.MessageToAny(w),
						})
					default:
						dumps[resourceType] = append(dumps[resourceType], rr)
					}
				default:
					dumps[resourceType] = append(dumps[resourceType], rr)
				}
			}
		} else {

			"Components.{{.ComponentName}}.K8S.PriorityClassName":   {OutPath: "[{{.ResourceType}}:{{.ResourceName}}].spec.template.spec.priorityClassName."},
			"Components.{{.ComponentName}}.K8S.ReadinessProbe":      {OutPath: "[{{.ResourceType}}:{{.ResourceName}}].spec.template.spec.containers.[name:{{.ContainerName}}].readinessProbe"},

	for resourceType := range totalMemoryType {
		commonMemoryTypeSet[resourceType] = true
	}

	for resourceType := range nodeAllocatableReservation {
		if !(corev1helper.IsHugePageResourceName(resourceType) || resourceType == v1.ResourceMemory) {
			continue
		}
		commonMemoryTypeSet[resourceType] = true
	}

	for resourceType := range commonMemoryTypeSet {

			continue
		}

		if currSingular.Resource != singular.Resource {
			return resourceType, fmt.Errorf("multiple possible singular resources (%v) found for %v", resources, resourceType)
		}
	}

	if singular.Empty() {
		return resourceType, fmt.Errorf("no singular of resource %v has been defined", resourceType)
	}

	return singular.Resource, nil
}

};

// Returns the type of the local variable for the stack size.
Type GetSizeVarType(OpBuilder builder) {
  auto size_type = cutil::GetSizeType(builder);
  return RankedTensorType::get(
      {}, TF::ResourceType::get(ArrayRef<TensorType>{size_type},
                                builder.getContext()));
}

// Returns the aliasing argument number of a fucntion return value if it simply