/// 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.
  std::list<std::string> lru_list_ ABSL_GUARDED_BY(mu_);
};

}  // namespace tf_gcs_filesystem

void TF_OutputListSetNumOutputs(TF_OutputList* o, int num_outputs, TF_Status*);
// Return the number of outputs in the list.
int TF_OutputListNumOutputs(TF_OutputList* o);
// Return the `i`th output in the list.
TF_AbstractTensor* TF_OutputListGet(TF_OutputList* o, int i);
// Append a tensor at the end of the output list, growing its size by one.

// by TF_StringStreamNext are invalid after this call.
TF_CAPI_EXPORT extern void TF_StringStreamDone(TF_StringStream* list);

// Retrieves the list of children of the given directory. You can iterate
// through the list with TF_StringStreamNext. The caller is responsible for
// freeing the list (see TF_StringStreamDone).

typedef struct TFE_Context TFE_Context;
typedef struct TFE_Op TFE_Op;

namespace tensorflow {
DEFINE_CONVERSION_FUNCTIONS(tensorflow::AbstractOpAttrs, TFE_OpAttrs);

// Set an AttrValue on the op. Doesn't handle the list types.
void SetOpAttrValueScalar(TFE_Context* ctx, TFE_Op* op,
                          const tensorflow::AttrValue& default_value,
                          const char* attr_name, TF_Status* status);
}  // namespace tensorflow

  // Releases the cleanup function instead of running it.
  // Hint: use c.release()() to run early.
  F release() {
    released_ = true;
    return std::move(f_);
  }

  bool is_released() const { return released_; }

 private:
  static_assert(!std::is_reference<F>::value, "F must not be a reference");

  bool released_ = false;
  F f_;
};

template <int&... ExplicitParameterBarrier, typename F,

  // onto its internal state after a call to `ComputeGradient`.
  using GradientTape<AbstractTensorHandle, GradientFunction,
                     TapeTensor>::IsPersistent;

  // Adds this tensor to the list of watched tensors.
  //
  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.

  void SetOutputs(std::initializer_list<TF_Operation*> outputs);
  void SetOutputs(const std::vector<TF_Output>& outputs);
  void SetTargets(std::initializer_list<TF_Operation*> targets);

  void Run(TF_Status* s);

  void CloseAndDelete(TF_Status* s);

  TF_Tensor* output_tensor(int i) { return output_values_[i]; }

  TF_Session* mutable_session() { return session_; }

};

struct TF_Function {
  tensorflow::FunctionRecord* record;
};

struct TF_ApiDefMap {
  explicit TF_ApiDefMap(const tensorflow::OpList& op_list)
      :
#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
        api_def_map(op_list),
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
        update_docs_called(false) {
  }

  virtual bool GetType(absl::string_view attr_name, DataType* result) const = 0;
  virtual Status GetTypeList(
      absl::string_view attr_name,
      absl::InlinedVector<DataType, 4>* type_list) const = 0;

 private:
  const AbstractOpAttrsKind kind_;
};

}  // namespace tensorflow

  // Returns the device ID which created the handle.
  virtual int DeviceId(Status* status) const = 0;
  // Returns a tensor for the handle. If tensor is remote, it will be copied.
  virtual AbstractTensorInterface* Resolve(Status* status) = 0;

  std::string DebugString() const override;

  // Returns a Boolean hint indicating whether callers should prefer