static void InitializeTestRNG() {
    std::random_device rd;
    std::mt19937 gen(rd());
    std::uniform_int_distribution<> distribution;
    rng_val_ = distribution(gen);
  }

  static void SetCloudPath(const std::string& cloud_path) {
    cloud_path_ = cloud_path;
    if (cloud_path_.back() == '/') cloud_path_.pop_back();
  }

  static void SetTmpDir(const std::string& tmp_dir) {

  // outputs are as expected.
  // 'T' stands for 'tensor' since the outputs are tensors, not scalars.
  void RunT(const std::vector<std::pair<TF_Operation*, TF_Tensor*>>& inputs,
            std::initializer_list<TF_Output> outputs,
            const std::vector<std::vector<int32_t>>& expected_results) {
    // Create a session for this graph
    CSession csession(host_graph_, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

                          std::optional<DeviceId> resource_op_device,
                          std::optional<int> resource_var_operation_node_id,
                          std::optional<DeadnessPredicate> deadness_predicate,
                          bool is_xla_compile_attr_true,
                          std::optional<string> xla_scope) {
    cluster_storage_.push_back(std::make_unique<Cluster>(

  float float_min = std::min(0.f, float_quant_params.min()->Get(0));
  float float_max = std::max(0.f, float_quant_params.max()->Get(0));
  if (symmetric) {
    // When the symmetric case, ConvertStatsToQDQs in PrepareQuantizePass
    // updates the min and max values into bigger absolute values.
    float_max = std::max(std::abs(float_min), std::abs(float_max));
    float_min = -float_max;
  }

  EXPECT_TF_META("v", list_size, TF_ATTR_INT, -1);
  TF_OperationGetAttrIntList(oper, "v", values, list_size, s_);
  EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  EXPECT_TRUE(std::equal(std::begin(list), std::end(list), std::begin(values)));
}

TEST_F(CApiAttributesTest, Float) {
  auto desc = init("float");
  TF_SetAttrFloat(desc, "v", 2.718);

  auto oper = TF_FinishOperation(desc, s_);

    Value external_output = std::get<0>(result);
    external_output.replaceUsesWithIf(std::get<1>(result),
                                      replace_output_usage);
  }
}

std::pair<std::string, std::string> MakeCommunicationKeys(
    ArrayRef<Operation*> clustered_ops, ArrayRef<Value> external_operands,
    int communication_key_index, Operation& op) {
  std::string args_communication_key =

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),

#  include <tuple>
// C++11 puts its tuple into the ::std namespace rather than
// ::std::tr1.  gtest expects tuple to live in ::std::tr1, so put it there.
// This causes undefined behavior, but supported compilers react in
// the way we intend.
namespace std {
namespace tr1 {
using ::std::get;
using ::std::make_tuple;
using ::std::tuple;
using ::std::tuple_element;
using ::std::tuple_size;
}
}

      if (resized_tensor_list_index.count(i)) {
        updated_types->push_back(
            VariantToUnrankedTensorType(std::get<0>(it), std::get<1>(it)));
      } else {
        updated_types->push_back(std::get<2>(it).getType());
      }
    } else {
      updated_types->push_back(std::get<0>(it));
    }
    ++i;
  }
}

// Updates the tensorlist types to unranked tensor types based on the input

var subAST = map[byte]AST{
	't': &Name{Name: "std"},
	'a': &Qualified{Scope: &Name{Name: "std"}, Name: &Name{Name: "allocator"}},
	'b': &Qualified{Scope: &Name{Name: "std"}, Name: &Name{Name: "basic_string"}},
	's': &Qualified{Scope: &Name{Name: "std"}, Name: &Name{Name: "string"}},
	'i': &Qualified{Scope: &Name{Name: "std"}, Name: &Name{Name: "istream"}},
	'o': &Qualified{Scope: &Name{Name: "std"}, Name: &Name{Name: "ostream"}},