TF_AbstractOp* TF_NewAbstractOp(TF_ExecutionContext* ctx);
void TF_DeleteAbstractOp(TF_AbstractOp*);

// TODO(srbs): Add APIs for specifying attrs etc.
// `op_type` must outlive `op`.
void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s);
// `op_name` must outlive `op`.
void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,

using tensorflow::NodeDef;

static void BoolDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<bool*>(data);
}

static void Int32Deallocator(void* data, size_t, void* arg) {
  delete[] static_cast<int32_t*>(data);
}

static void DoubleDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<double*>(data);
}

static void FloatDeallocator(void* data, size_t, void* arg) {

  // Set stack trace to be used for potential async error reporting.
  virtual void SetStackTrace(ManagedStackTrace stack_trace) = 0;

  virtual const tensorflow::AbstractOpAttrs* GetOpAttrs() const = 0;
  virtual void AddAttrs(const AbstractOpAttrs* op_attrs) = 0;

  virtual void SetCancellationManager(
      CancellationManager* cancellation_manager) = 0;

                                                 dtype.code);
  }
}

// Wraps the deleter function of DLManagedTensor to match the function signature
// TFE_NewTensorHandleFromDeviceMemory.
void DeallocatorWrapperFunc(void* data, size_t len, void* dlmt_vptr) {
  TFE_CallDLManagedTensorDeleter(dlmt_vptr);
}

// Checks whether the stride array matches the layout of compact, row-majored
// data.

TFE_MonitoringCounter0* CreateCounter0(const char* counter_name);
TFE_MonitoringCounter1* CreateCounter1(const char* counter_name,
                                       const char* label);
void IncrementCounter0(TFE_MonitoringCounter0* counter, int64_t delta = 1);
void IncrementCounter1(TFE_MonitoringCounter1* counter, const char* label,
                       int64_t delta = 1);

TEST(CAPI, MonitoringCellReader0) {
  auto counter_name = "test/counter0";

    return LookupLocked(key, value);
  }

  typedef std::function<void(const std::string&, T*, TF_Status*)> ComputeFunc;

  /// Look up the entry with key `key` and copy it to `value` if found. If not
  /// found, call `compute_func`. If `compute_func` set `status` to `TF_OK`,
  /// store a copy of the output parameter in the cache, and another copy in
  /// `value`.
  void LookupOrCompute(const std::string& key, T* value,

  return TapeTensor(g);
}

void TapeVSpace::MarkAsResult(AbstractTensorHandle* gradient) const {}

void TapeVSpace::DeleteGradient(AbstractTensorHandle* gradient) const {
  gradient->Unref();
}

void Tape::Watch(const AbstractTensorHandle* t) {
  GradientTape::Watch(ToId(t));
}
void Tape::RecordOperation(absl::Span<AbstractTensorHandle* const> inputs,

  ASSERT_GE(TF_NowNanos(), 946684800 * 1e9);
}

namespace {

struct SomeThreadData {
  ::tensorflow::mutex mu;
  bool did_work = false;
};

void SomeThreadFunc(void* data) {
  auto* real_data = static_cast<SomeThreadData*>(data);
  ::tensorflow::mutex_lock l(real_data->mu);
  real_data->did_work = true;
}

}  // namespace

TEST(TestEnv, TestThreads) {

limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/c_api_remote_test_util.h"
#include "tensorflow/core/platform/test.h"

namespace {

void TestRemoteExecuteSilentCopiesFunc(bool async, bool remote,
                                       bool heavy_load_on_streaming_rpc,
                                       bool remote_func_outputs = false,

  outputs[0] = temp_outputs[1];
  temp_outputs[0]->Unref();
  return absl::OkStatus();
}

class CppGradients
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    status_ = StatusFromTF_Status(status.get());