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

abstract: TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture...

      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).

                                                    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);

    *   In `map_vectorization` optimization, reduce the degree of parallelism in
        the vectorized map node.
    *   Add variant wrapper for `absl::string_view`.
    *   Add OpKernels for some stateless maps.
    *   DType is no longer convertible to an int. Use `dtype.as_datatype_enum`
        instead of `int(dtype)` to get the same result.
    *   Support both binary and -1/1 label input in v2 hinge and squared hinge

// 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)
//