// the object. Using duplicate metric name will crash the program with fatal
// error.
TF_CAPI_EXPORT extern TFE_MonitoringCounter0* TFE_MonitoringNewCounter0(
    const char* name, TF_Status* status, const char* description);
// Deletes the Counter object.
TF_CAPI_EXPORT extern void TFE_MonitoringDeleteCounter0(
    TFE_MonitoringCounter0* counter);
// Retrieves the cell from the Counter object. The Counter object will manage

  // The devices operations run on.
  const std::vector<std::string>& underlying_devices() const {
    return underlying_devices_;
  }

  // Takes a description of a single operation being executed on the
  // ParallelDevice, and in turn runs one operation per component device with
  // its corresponding inputs from the input ParallelTensors. Wraps the

      gtl::ArraySlice<Gradient*> output_gradients, absl::Span<Gradient*> result,
      bool build_default_zeros_grads = true);

  // Whether the tape is persistent. See ctor for detailed description.
  bool IsPersistent() const { return persistent_; }

 private:
  TensorTape tensor_tape_;
  OpTape<BackwardFunction, TapeTensor> op_tape_;
  int64_t next_op_id_{0};

// The return value was current at the time of TFE_TensorDebugInfo creation.
TF_CAPI_EXPORT extern int64_t TFE_TensorDebugInfoOnDeviceDim(
    TFE_TensorDebugInfo* debug_info, int dim_index);

// Description of the TensorFlow op to execute.
//
// Assumes that the provided 'ctx' outlives the returned TFE_Op, i.e.,
// TFE_DeleteOp() is called before TFE_DeleteContext().
//

      DataType dtype, absl::Span<const int64_t> dim_sizes) = 0;

  typedef void (*MemoryReleaser)(void* data, size_t len, void* arg);

  // Create a tensor instance from the given data buffer and description.
  // `memory_releaser` will be called on destruction, and it's responsible for
  // cleaning up the underlying buffer.
  virtual AbstractTensorInterface* CreateTensor(