// Registers a function with this context, after this the function is
  // available to be called/referenced by its name in this context.
  virtual Status RegisterFunction(AbstractFunction*) = 0;
  // Remove a function. 'func' argument is the name of a previously added
  // FunctionDef. The name is in fdef.signature.name.
  virtual Status RemoveFunction(const string& func) = 0;

 private:
  const AbstractContextKind kind_;
};

// Dynamic cluster API.

// Update an existing context with a new set of servers defined in a ServerDef
// proto. Servers can be added to and removed from the list of remote workers
// in the context. A New set of servers identified by the ServerDef must be up
// when the context is updated.
//
// This API is for experimental usage and may be subject to change.

void TF_InitGraph(TP_OptimizerRegistrationParams* params, TF_Status* status);

// Get a set of node names that must be preserved. They can not be transformed
// or removed during the graph transformation. This includes feed and fetch
// nodes, keep_ops, init_ops. Fills in `num_values` and `storage_size`, they
// will be used in `TF_GetNodesToPreserveList`.

    TF_Status* status);

// Frees the memory used by the `func` struct.
// TF_DeleteFunction is a noop if `func` is null.
// Deleting a function does not remove it from any graphs it was copied to.
TF_CAPI_EXPORT extern void TF_DeleteFunction(TF_Function* func);

// Attempts to evaluate `output`. This will only be possible if `output` doesn't

      : device_(device),
        tensors_(std::move(tensors)),
        shape_(std::vector<int64_t>(shape.begin(), shape.end())),
        dtype_(dtype) {}
  ParallelTensor(const ParallelDevice& device,
                 std::vector<TensorHandlePtr> tensors, const TF_DataType dtype)
      : device_(device),
        tensors_(std::move(tensors)),
        shape_(absl::nullopt),
        dtype_(dtype) {}

  virtual bool IsCustomDevice(const string& device_name) = 0;

  // Register a custom device. It will return error is the device name is
  // already registered.
  // TODO(tfrt-devs): Remove this method. Let caller register it directly into
  // CustomDeviceOpHandler.
  virtual Status RegisterCustomDevice(const string& name,
                                      std::unique_ptr<CustomDevice> device) = 0;

    TF_DataType data_type, void* data, size_t len, TF_Status* status);

// Specify the server_def that enables collective ops.
// This is different to the above function in that it doesn't create remote
// contexts, and remotely executing ops is not possible. It just enables
// communication for collective ops.
TF_CAPI_EXPORT extern void TFE_EnableCollectiveOps(TFE_Context* ctx,

    tensor_tape_[o.GetID()] = op_id;
    tensor_usage_[o.GetID()] = 1;
    tensors.push_back(o);
  }
  op_tape_[op_id] = OpTapeEntry<BackwardFunction, TapeTensor>{
      op_type, std::move(tensors), std::move(ids), backward_function_getter(),
      backward_function_deleter};
}

template <typename Gradient, typename BackwardFunction, typename TapeTensor>

      : filesystem_(std::move(filesystem)),
        ops_(std::move(filesystem_ops)),
        random_access_file_ops_(std::move(random_access_file_ops)),
        writable_file_ops_(std::move(writable_file_ops)),
        read_only_memory_region_ops_(std::move(read_only_memory_region_ops)),
        plugin_memory_allocate_(std::move(plugin_memory_allocate)),
        plugin_memory_free_(std::move(plugin_memory_free)) {}

TF_CAPI_EXPORT extern TFE_ContextDevicePlacementPolicy
TFE_ContextGetDevicePlacementPolicy(TFE_Context* ctx);

// A tensorflow.ServerDef specifies remote workers (in addition to the current
// workers name). Operations created in this context can then be executed on
// any of these remote workers by setting an appropriate device.
//
// If the following is set, all servers identified by the
// ServerDef must be up when the context is created.