TEST_F(XlaKernelCreatorTest, OneFloatOneResourceArgument) {
  FunctionDef fdef = XTimesY();
  (*fdef.mutable_attr())["_XlaMustCompile"] = BoolAttr(true);
  Init({fdef});
  XlaKernelCreator xla_kernel_creator;
  auto callsite =
      ToNodeProperties(R"pb(
        name: 'XTimesY' op: 'XTimesY' input: 'a' input: 'b'
      )pb");
  (*(callsite->node_def.mutable_attr()))["_XlaMustCompile"] = BoolAttr(true);

  def.set_device(DEVICE_CPU);

  AttrValue typeAttr;
  SetAttrValue(input_tensor->dtype(), &typeAttr);

  AttrValue outTypeAttr;
  SetAttrValue(out_type, &outTypeAttr);

  (*def.mutable_attr())["T"] = typeAttr;
  (*def.mutable_attr())["type"] = outTypeAttr;

  def.add_input(
      strings::StrCat("input1: ", DataTypeString(input_tensor->dtype())));

  std::unique_ptr<OpKernel> kernel =

            (*node_def.mutable_attr())["shared_name"].set_s(node_def.name());
          } else {
            // Use the concat of function name and node name for such ops in a
            // function as the shared_name. "@" is used as the separator because
            // it is not allowed in the function name or the node name.
            (*node_def.mutable_attr())["shared_name"].set_s(

                           std::vector<Output>* grad_outputs) {
  NameAttrList f;
  TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "f", &f));
  for (const auto& attr : op.node()->attrs()) {
    (*f.mutable_attr())[attr.first] = attr.second;
  }

  std::vector<Output> func_inputs;
  std::vector<DataType> input_dtypes;
  const int num_inputs = op.num_inputs();
  func_inputs.reserve(num_inputs + grad_inputs.size());

      }

      (*node_def->mutable_attr())["_handle_dtypes"] = handle_dtypes_attr;
      (*node_def->mutable_attr())["_handle_shapes"] = handle_shapes_attr;
    }
  }

  TF_RETURN_IF_ERROR(
      SetShapeAttribute("_output_shapes", arg_type, node_def->mutable_attr()));

  DataType dtype;
  TF_RETURN_IF_ERROR(ConvertToDataType(arg_type.getElementType(), &dtype));

      }

      (*node_def->mutable_attr())["_handle_dtypes"] = handle_dtypes_attr;
      (*node_def->mutable_attr())["_handle_shapes"] = handle_shapes_attr;
    }
  }

  TF_RETURN_IF_ERROR(
      SetShapeAttribute("_output_shapes", arg_type, node_def->mutable_attr()));

  DataType dtype;
  TF_RETURN_IF_ERROR(ConvertToDataType(arg_type.getElementType(), &dtype));

                               NodeDef* const_node) {
  const_node->set_name(variable_node.name());
  const_node->set_op("Const");
  (*const_node->mutable_attr())["dtype"] = variable_node.attr().at("dtype");
  variable_value.AsProtoTensorContent(
      (*const_node->mutable_attr())["value"].mutable_tensor());
}

// Converts a ReadVariableOp NodeDef to an Identity NodeDef.
void ConvertReadVariableOpToIdentity(const NodeDef& node,

  //   C = XTimesTwo[_xla_compile_id="cluster"](A)
  TF_ASSERT_OK(scope_.graph()->AddFunctionLibrary(f_lib_proto));

  Output x = Placeholder(scope_, DT_FLOAT);
  NameAttrList f;
  f.set_name("XTimesTwo");
  (*f.mutable_attr())["T"].set_type(DT_FLOAT);
  auto results =
      PartitionedCall(scope_, std::initializer_list<Input>{x}, {DT_FLOAT}, f);
  RunTest(x, {}, results[0], {});

  auto stateful_results = StatefulPartitionedCall(

  std::map<string, int> host_compute_core = {{"0", 1}, {"1", 0}};
  std::vector<string> shape_inference_graphs;
  bool has_outside_compilation;
  NameAttrList name_attrs;
  name_attrs.set_name("cluster");
  *name_attrs.mutable_attr() = attrs;
  TF_CHECK_OK(ExtractOutsideCompilationTest(
      "_xla", "_oc", "cluster", name_attrs, "cluster_rewritten", "host_graph",
      host_compute_core, &fld, &shape_inference_graphs,

                                  }}},
                                {{"c", "t0:y:0"}});

  AttrValue true_attribute;
  true_attribute.set_b(true);
  (*called_func.mutable_attr())[kXlaMustCompileAttr] = true_attribute;
  *library.add_function() = called_func;
  TF_ASSERT_OK(root.graph()->AddFunctionLibrary(library));
  FunctionLibraryDefinition flib_def(OpRegistry::Global(), library);