TFE_TensorHandle* var_handle = nullptr;
  int num_retvals = 1;
  executed = false;
  TFE_Execute(op.get(), &var_handle, &num_retvals, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_TRUE(executed);
  auto handle_cleaner = tensorflow::gtl::MakeCleanup(
      [var_handle]() { TFE_DeleteTensorHandle(var_handle); });

};

// Gets tensor from eager tensor handle.
const Tensor* GetTensorFromHandle(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h));
  if (handle->Type() != TensorHandle::LOCAL) {

        ::tensorflow::io::JoinPath(dirpath, "somefile.txt");
    TF_WritableFileHandle* handle;
    TF_NewWritableFile(filepath.c_str(), &handle, s);
    ASSERT_TF_OK(s) << "NewWritableFile failed for " << filepath << ": "
                    << TF_Message(s);

    const char* data = "Hello, world!\n";
    TF_AppendWritableFile(handle, data, strlen(data), s);
    ASSERT_TF_OK(s) << "TF_AppendWritableFile failed to append data to file at "

}

TapeTensor::TapeTensor(AbstractTensorHandle* handle) : handle_(handle) {
  handle_->Ref();
}
TapeTensor::TapeTensor(const TapeTensor& other) {
  handle_ = other.handle_;
  handle_->Ref();
}
TapeTensor::~TapeTensor() { handle_->Unref(); }

int64_t TapeTensor::GetID() const { return ToId(handle_); }

tensorflow::DataType TapeTensor::GetDType() const {
  return handle_->DataType();
}

      creator, device_type, configs);
}

#undef CONFIG_TOGGLE

absl::Status InitGraphPlugin(void* dso_handle) {
  tsl::Env* env = tsl::Env::Default();

  // Step 1: Load symbol for `TF_InitPlugin`
  void* dso_symbol;
  TF_RETURN_IF_ERROR(
      env->GetSymbolFromLibrary(dso_handle, "TF_InitGraph", &dso_symbol));

  // Step 2: Call `TF_InitPlugin`

                      ", dtype=", DataType_Name(DataType()),
                      ", type=", FullType().DebugString(), ")");
}

Status AbstractTensorHandle::TensorHandleStatus() const {
  // Tensor handles in current runtime don't carry error info and this method
  // should always return OK status.
  return absl::OkStatus();
}

  if (TF_GetCode(status) != TF_OK) return;

  TFE_TensorHandle* result_handles[num_replicas];
  int num_retvals = num_replicas;
  TFE_Execute(op.get(), result_handles, &num_retvals, status);
  if (TF_GetCode(status) != TF_OK) return;
  for (int i = 0; i < num_replicas; ++i) {
    (*components)[i].reset(result_handles[i]);
  }
}

TensorHandlePtr Multiply(TFE_Context* context, TFE_TensorHandle* first,

  // Pack 3 variable handles into one TFE_TensorHandle.
  // When remote is false, function device is placed on task0. Handle types are
  // REMOTE, REMOTE, LOCAL on task0. When remote is true, function device is
  // placed on task1, Handle types are LOCAL, REMOTE, LOCAL on task1.
  int num_replicas = 3;
  std::vector<TFE_TensorHandle*> handles = {h0, h1, h2};
  TFE_TensorHandle* packed_handle =

  TFE_OpAddInput(op.get(), input, status);
  if (TF_GetCode(status) != TF_OK) return nullptr;

  TFE_TensorHandle* result_handle;
  int num_retvals = 1;
  TFE_Execute(op.get(), &result_handle, &num_retvals, status);
  if (TF_GetCode(status) != TF_OK) return nullptr;
  return TensorHandlePtr(result_handle);
}

void TestCollective(bool async) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(

  TFE_CustomDeviceTensorHandleMethods handle_methods;
  handle_methods.num_dims = &LoggedTensorNumDims;
  handle_methods.dim = &LoggedTensorDim;
  handle_methods.deallocator = &LoggedTensorDeallocator;
  return TFE_NewCustomDeviceTensorHandle(context, logging_device_name.c_str(),
                                         dtype, t.release(), handle_methods,
                                         status);
}