std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,
            std::unique_ptr<TensorSliceReader::VarToDataTypeMap> >

};

struct TF_Graph {
  TF_Graph();

  mutable tensorflow::mutex mu;
  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each

                                                    void* device_info,
                                                    TF_Status* status);

// Returns whether `device_name` maps to a registered custom device.
TF_CAPI_EXPORT extern bool TFE_IsCustomDevice(TFE_Context* ctx,
                                              const char* device_name);

      const std::function<void(BackwardFunction*)>& backward_function_deleter,
      const std::vector<Gradient*>& in_grads, absl::Span<Gradient*> out_grads);

  // Maps from tensor IDs to corresponding JVPs.
  std::unordered_map<int64_t, Gradient*> accumulated_gradients_;
  // Not owned; provides operations on Tensors which are currently only
  // available in language bindings (e.g. Python).

// in this address space.
TF_CAPI_EXPORT extern TF_Buffer* TF_GetAllOpList(void);

// TF_ApiDefMap encapsulates a collection of API definitions for an operation.
//
// This object maps the name of a TensorFlow operation to a description of the
// API to generate for it, as defined by the ApiDef protocol buffer (
// https://www.tensorflow.org/code/tensorflow/core/framework/api_def.proto)
//