/// The callback to read timestamps.
  std::function<uint64_t()> timer_seconds_;

  /// Guards access to the cache and the LRU list.
  absl::Mutex mu_;

  /// The cache (a map from string key to Entry).
  std::map<std::string, Entry> cache_ ABSL_GUARDED_BY(mu_);

  /// The LRU list of entries. The front of the list identifies the most
  /// recently accessed entry.

TF_CAPI_EXPORT extern void TF_GetOutputPropertiesList(
    TF_GraphProperties* graph_properties, const char* name,
    TF_Buffer** properties, int num_values, TF_Status* status);

// Helper to maintain a map between function names in a given
// FunctionDefLibrary and function definitions.
// Typical use case, is to look up an OpDef by type name.
typedef struct TF_FunctionLibraryDefinition TF_FunctionLibraryDefinition;

TF_CAPI_EXPORT extern void TFE_OpAddAttrs(TFE_Op* op, const TFE_OpAttrs* attrs);

// Serialize `attrs` as a tensorflow::NameAttrList protocol buffer (into `buf`),
// containing the op name and a map of its attributes.
TF_CAPI_EXPORT extern void TFE_OpAttrsSerialize(const TFE_OpAttrs* attrs,
                                                TF_Buffer* buf,
                                                TF_Status* status);

  // acquires each thread in order (and so only one Execute will schedule
  // blocking collective operations at a time), and avoids some dynamic
  // allocation/scheduling.
  //
  // TODO(allenl): Keep a map from outer thread to list of inner threads rather
  // than a single list of threads so aliased nested parallel devices don't
  // re-use a thread.
  std::vector<std::unique_ptr<DeviceThread>> device_threads_;

TF_CAPI_EXPORT extern void TF_DeleteApiDefMap(TF_ApiDefMap* apimap);

// Add ApiDefs to the map.
//
// `text` corresponds to a text representation of an ApiDefs protocol message.
// (https://www.tensorflow.org/code/tensorflow/core/framework/api_def.proto).
//
// The provided ApiDefs will be merged with existing ones in the map, with
// precedence given to the newly added version in case of conflicts with

  bool HasTensor(const string& name) const;
  const string DebugString() const;

  // Returns a map from variable names to their shapes.  Slices of a partitioned
  // tensor are combined into a single entry.
  const TensorSliceReader::VarToShapeMap& GetVariableToShapeMap() const;

  // Returns a map from variable names to their data types.  Slices of a
  // partitioned tensor are combined into a single entry.

  // 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
  // value records whether the graph has been mutated since the corresponding

// for testing.

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRAPPLER_GRAPPLER_INTERNAL_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRAPPLER_GRAPPLER_INTERNAL_H_

#include <functional>
#include <memory>
#include <unordered_map>
#include <unordered_set>
#include <vector>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/experimental/grappler/grappler.h"
#include "tensorflow/core/framework/graph.pb.h"

  std::function<void(BackwardFunction*)> backward_function_deleter;
};

// Map from tensor_id to internally-defined operation-id of the operation which
// produced this tensor. A value of -1 means that the tensor was directly
// watched and not the result of any operation in the tape.
using TensorTape = std::unordered_map<int64_t, int64_t>;

// Map from operation-id to tape entry.
template <typename BackwardFunction, typename TapeTensor>

    /// Wait on cond_var if state is FETCHING.
    absl::CondVar cond_var;
  };

  /// \brief The block map type for the file block cache.
  ///
  /// The block map is an ordered map from Key to Block.
  typedef std::map<Key, std::shared_ptr<Block>> BlockMap;

  /// Prune the cache by removing files with expired blocks.
  void Prune() ABSL_LOCKS_EXCLUDED(mu_);