code: def execute(self, output):
      onnx_model = OnnxExporter(
          self._nnp, self._batch_size, self._ir_version, opset="11"
      ).export_model_proto()
      tf_rep = prepare(onnx_model)
      if self._model_format == "TF_PB":
          output_path = os.path.dirname(output)
          tf_model = tf_rep.tf_module.__call__.get_concrete_function(
              **tf_rep.signatures
          )
          frozen_func = convert_variables_to_constants_v2(
              tf_model, lower_control_flow=False
          )
          tf.io.write_graph(
              graph_or_graph_def=frozen_func.graph,
              logdir=output_path,
              name=os.path.basename(output),
              as_text=False,
          )
      else:
          tf_rep.export_graph(output)
  
file_path: nnabla/python/src/nnabla/utils/converter/tensorflow/exporter.py
imports: import os
  import tensorflow
  from onnx_tf.backend import prepare
  from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2
  from ..onnx import OnnxExporter
label_desc: Use image node_id 3 for calling the TensorflowExporter obj's underlying member method code with example usage: obj.execute(output) without return types