}

void TestScalarSummaryOp(Tensor* tags, Tensor* values, string expected_output,
                         error::Code expected_code) {
  // Initialize node used to fetch OpKernel
  Status status;
  NodeDef def;
  def.set_op("ScalarSummary");

  def.set_device(DEVICE_CPU);

  AttrValue valuesTypeAttr;
  SetAttrValue(values->dtype(), &valuesTypeAttr);
  (*def.mutable_attr())["T"] = valuesTypeAttr;

  } while (name_set.contains(candidate));
  return candidate;
}

absl::StatusOr<Node*> CloneConstantsForBetterClusteringPassImpl::CloneNode(
    const absl::flat_hash_set<string>& name_set, Node* n) {
  NodeDef new_in_def = n->def();
  new_in_def.clear_input();
  new_in_def.set_name(GenerateUniqueName(name_set, new_in_def.name()));
  TF_ASSIGN_OR_RETURN(Node * new_in, graph_->AddNode(new_in_def));

         std::find(node.output_types().begin(), node.output_types().end(),
                   DT_RESOURCE) != node.output_types().end();
}

void RemoveFromXlaCluster(NodeDef* node_def) {
  node_def->mutable_attr()->erase(kXlaClusterAttr);
}

void RemoveFromXlaCluster(Node* node) { node->ClearAttr(kXlaClusterAttr); }

namespace {
typedef xla_config_registry::XlaGlobalJitLevel XlaGlobalJitLevel;

                  .Input(inputs)
                  .Attr("ids", ids)
                  .Attr("calibration_methods", calibration_methods)
                  .Finalize(node_def()));
  ASSERT_THAT(InitOp(),
              StatusIs(tsl::error::INVALID_ARGUMENT,
                       HasSubstr("NodeDef missing attr 'output_file_path'")));
}

TEST_F(CalibrationStatisticsSaverTest, WrongNumInputs) {
  std::vector<std::string> ids{"1"};

    const FunctionLibraryDefinition& flib_def) {
  for (const std::string& func_name : flib_def.ListFunctionNames()) {
    const FunctionDef* func_def = flib_def.Find(func_name);
    for (const NodeDef& node_def : func_def->node_def()) {
      if (node_def.op() == kPartitionedCall) return true;
    }
  }
  return false;
}

}  // namespace

bool IsSupportedByNonReplicatedBridge(

    // In both cases, none should be variables.
    size_t expected_nodes = use_resource ? (use_identity ? 5 : 4) : 3;

    EXPECT_EQ(frozen_graph_def.node_size(), expected_nodes);
    for (const NodeDef& node : frozen_graph_def.node()) {
      EXPECT_NE(node.op(), "Variable") << node.name();
      EXPECT_NE(node.op(), "VariableV2") << node.name();
      EXPECT_NE(node.op(), "VarHandleOp") << node.name();

  return result;
}

Status AssertGraphDefIsUnclustered(const GraphDef& graphdef) {
  const char* kXlaClusterAttr = "_XlaCluster";
  const char* kXlaAlreadyClusteredAttr = "_XlaAlreadyClustered";

  for (const NodeDef& node : graphdef.node()) {
    if (node.attr().count(kXlaClusterAttr) ||
        node.attr().count(kXlaAlreadyClusteredAttr)) {
      return errors::InvalidArgument(

  TF_ASSERT_OK(DeviceFactory::AddDevices(
      SessionOptions(), "/job:localhost/replica:0/task:0", &devices));

  // Scope::ToGraph loses the assigned device name since it goes through
  // GraphDef/NodeDef which does not have a field for the assigned device name.
  Node* n = FindNodeByName(*graph, "shape");
  ASSERT_NE(n, nullptr);
  n->set_assigned_device_name(
      "/job:localhost/replica:0/task:0/device:XLA_GPU:0");

}

Status MakeXlaCompiledKernel(Graph* graph, const string& callee_name,
                             const string& node_name, int num_constant_args,
                             int num_resource_args, Node** result) {
  NodeDef call_node;
  call_node.set_name(node_name);
  call_node.set_op(callee_name);
  AddNodeAttr(kXlaCompiledKernelAttr, true, &call_node);
  AddNodeAttr(kXlaNumConstantArgsAttr, num_constant_args, &call_node);

  std::initializer_list<int64_t> dims = {2, 3, 4, 5};
  Tensor tensor(data_type, TensorShape(dims));
  for (int i = 0; i < 2 * 3 * 4 * 5; ++i) {
    tensor.flat<int32>()(i) = i;
  }

  NodeDef node;
  auto builder = NodeDefBuilder("some_node", "Const")
                     .Attr("dtype", data_type)
                     .Attr("value", tensor);
  // Create a bad output shape attr.
  AttrValue shape_attr;