};

struct TFE_MonitoringBoolGauge0 : TFE_MonitoringGauge<bool, 0> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringBoolGauge1 : TFE_MonitoringGauge<bool, 1> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringBoolGauge2 : TFE_MonitoringGauge<bool, 2> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};

struct TFE_MonitoringBuckets {

  // `keep_alive_secs` of inactivity.
  virtual Status SetOrUpdateServerDef(const ServerDef& server_def,
                                      bool reset_context, int keep_alive_secs,
                                      int64_t init_timeout_in_ms, int retries,
                                      bool clear_existing_contexts = false) = 0;

  // Initializes context for the local worker and no contexts will be created

  // Hint: use c.release()() to run early.
  F release() {
    released_ = true;
    return std::move(f_);
  }

  bool is_released() const { return released_; }

 private:
  static_assert(!std::is_reference<F>::value, "F must not be a reference");

  bool released_ = false;
  F f_;
};

template <int&... ExplicitParameterBarrier, typename F,
          typename DecayF = typename std::decay<F>::type>

TempFile::~TempFile() {
  std::fstream::close();
  std::remove(name_.c_str());
}

const std::string TempFile::getName() const { return name_; }

bool TempFile::truncate() {
  std::fstream::close();
  std::fstream::open(name_, std::ios::binary | std::ios::out);
  return std::fstream::is_open();

namespace tensorflow {
namespace gradients {
namespace internal {

void CompareNumericalAndAutodiffGradients(
    Model model, Model grad_model, AbstractContext* ctx,
    absl::Span<AbstractTensorHandle* const> inputs, bool use_function,
    double abs_error = 1e-2);

void CheckTensorValue(AbstractTensorHandle* t, absl::Span<const float> manuals,
                      absl::Span<const int64_t> dims, double abs_error = 1e-2);

  absl::StatusOr<core::RefCountPtr<FunctionRecord>> GetFunctionRecord()
      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing

                    unsigned char value) {
  desc->node_builder.Attr(attr_name, static_cast<bool>(value));
}

void TF_SetAttrBoolList(TF_OperationDescription* desc, const char* attr_name,
                        const unsigned char* values, int num_values) {
  std::unique_ptr<bool[]> b(new bool[num_values]);
  for (int i = 0; i < num_values; ++i) {
    b[i] = values[i];
  }

  virtual Status SetAttrInt(const char* attr_name, int64_t value) = 0;
  virtual Status SetAttrFloat(const char* attr_name, float value) = 0;
  virtual Status SetAttrBool(const char* attr_name, bool value) = 0;
  virtual Status SetAttrType(const char* attr_name, DataType value) = 0;
  virtual Status SetAttrShape(const char* attr_name, const int64_t* dims,
                              const int num_dims) = 0;

  tensorflow::string underlying_device;
  // Set to true whenever a TensorHandle is copied onto the device
  bool* arrived_flag;
  // Set to true whenever an operation is executed
  bool* executed_flag;
  // If true, only explicit op placements are accepted. If false, uses
  // type-based dispatch.
  bool strict_scope_placement;
};

struct LoggedTensor {
  TFE_TensorHandle* tensor;
  LoggedTensor() = delete;

  GCSFile(google::cloud::storage::Client&& gcs_client, bool compose,
          uint64_t block_size, size_t max_bytes, uint64_t max_staleness,
          uint64_t stat_cache_max_age, size_t stat_cache_max_entries);
} GCSFile;

// This function is used to initialize a filesystem without the need of setting
// manually environement variables.
void InitTest(TF_Filesystem* filesystem, bool compose, uint64_t block_size,