code: def _check_trainable_parameters(y):
      def _check_trainable_inputs(f):
          for i in f.inputs:
              if i.need_grad:
                  return True
          return False
  
      return y.visit_check(_check_trainable_inputs)
  
file_path: nnabla/python/test/models/test_deeplabv3plus.py
imports: from __future__ import absolute_import
  import pytest
  from nnabla.utils.nnp_graph import NnpNetwork
  import nnabla
  import numpy
  from nnabla.models.utils import get_model_url_base_from_env
label_desc: Use image node_id 1 for calling a global function with example usage: _check_trainable_parameters(y) and returns: y, False, True