// `output` if its a resource or variant tensor, or otherwise returns the empty
// string.
TF_CAPI_EXPORT extern TF_Buffer* TF_GetHandleShapeAndType(TF_Graph* graph,
                                                          TF_Output output);

// Sets `output` based on `proto`, which should be a serialized
// CppShapeInferenceResult::HandleData proto. `output` should be a resource
// or variant tensor.

  std::unordered_map<int64_t, TapeTensor> sources_that_are_targets;
  for (int grad_index = 0, end = grad.size(); grad_index < end; ++grad_index) {
    Gradient* grad_tensor = grad[grad_index];
    if (grad_tensor != nullptr) {
      int64_t tensor_id = vspace_.TensorId(grad_tensor);
      targets.push_back(tensor_id);
      if (sources_set.find(tensor_id) != sources_set.end()) {
        sources_that_are_targets.emplace(

    const char* plugin_resource_name, void* plugin_resource,
    void (*delete_func)(void*), TF_Status* status);

// If the ResourceMgr provided by the `ctx` has a resource
// `plugin_resource_name`, returns it in `*result_plugin_resource`. Otherwise,
// invokes create_func to create the resource. `delete_func` is needed for
// ResourceMgr to clean up the resource. `status` will be set. If `status` is

  virtual void ClearCachesAndThreadExecutors() = 0;

  // Initialize the step resource container for a training step. This is used
  // in current TF runtime. For tfrt, it is used by fallback op handler.
  virtual void StartStep() = 0;
  // Destroy the step resource container for a training step.
  virtual void EndStep() = 0;