CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);
  auto* cell = TFE_MonitoringGetCellCounter0(counter);
  TFE_MonitoringCounterCellIncrementBy(cell, 1);
  EXPECT_EQ(TFE_MonitoringCounterCellValue(cell), 1);
  auto* collection_registry = monitoring::CollectionRegistry::Default();
  monitoring::CollectionRegistry::CollectMetricsOptions options;

  *result = filename_;
  return OkStatus();
}

Status ModularWritableFile::Tell(int64_t* position) {
  if (ops_->tell == nullptr)
    return errors::Unimplemented(
        tensorflow::strings::StrCat("Tell() not implemented for ", filename_));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  *position = ops_->tell(file_.get(), plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

// Atomically increments the value of the cell. The value must be non-negative.
TF_CAPI_EXPORT extern void TFE_MonitoringCounterCellIncrementBy(
    TFE_MonitoringCounterCell* cell, int64_t value);

// Retrieves the current value of the cell.
TF_CAPI_EXPORT extern int64_t TFE_MonitoringCounterCellValue(
    TFE_MonitoringCounterCell* cell);

// APIs for Counter without label.

_current_module.__path__ = [_module_dir] + _current_module.__path__

_current_module.nn.rnn_cell = _KerasLazyLoader(
    globals(),
    submodule="__internal__.legacy.rnn_cell",
    name="rnn_cell",
    mode="v1")
if _tf_uses_legacy_keras:
  _module_dir = _module_util.get_parent_dir_for_name(
      "tf_keras.api._v1.keras.__internal__.legacy.rnn_cell")
else:
  _module_dir = _module_util.get_parent_dir_for_name(

//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test.py
//tensorflow/lite/python:interpreter

TF_Graph::TF_Graph()
    : graph(tensorflow::OpRegistry::Global()),
      refiner(graph.versions().producer(), graph.op_registry()),
      delete_requested(false),
      parent(nullptr),
      parent_inputs(nullptr) {
  // Tell the shape refiner to also run shape inference on functions.
  refiner.set_function_library_for_shape_inference(&graph.flib_def());
}

TF_Graph* TF_NewGraph() { return new TF_Graph; }

  return context->GetContextId();
}

void TFE_MonitoringCounterCellIncrementBy(TFE_MonitoringCounterCell* cell,
                                          int64_t value) {
  cell->cell.IncrementBy(value);
}

int64_t TFE_MonitoringCounterCellValue(TFE_MonitoringCounterCell* cell) {
  return cell->cell.value();
}

TFE_MonitoringCounter0* TFE_MonitoringNewCounter0(const char* name,

    *   tf.optimizers => tf.keras.optimizers
    *   Add tf.keras.layers.AbstractRNNCell as the preferred implementation of
        RNN cell for TF v2. User can use it to implement RNN cell with custom
        behavior.
    *   Adding `clear_losses` API to be able to clear losses at the end of
        forward pass in a custom training loop in eager.

  # that they are not substituted for their corresponding commands in shell
  # scripts. By setting "expand_aliases", we enable alias expansion in
  # non-interactive shells as well.
  shopt -s expand_aliases
else
  echo '==TFCI==: Error: Cannot find path to grealpath or gstat'
  echo 'TF CI scripts require GNU core utilties to be installed. Please make'

  Status Append(StringPiece data) override;
  Status Close() override;
  Status Flush() override;
  Status Sync() override;
  Status Name(StringPiece* result) const override;
  Status Tell(int64_t* position) override;

 private:
  std::string filename_;
  std::unique_ptr<TF_WritableFile> file_;
  const TF_WritableFileOps* ops_;  // not owned
  ModularWritableFile(const ModularWritableFile&) = delete;