code: def test_save_module_grad_only_false():
      x = nn.Variable.from_numpy_array(np.random.random([1, 2, 10, 10]))
      ref_y = PF.convolution(x, 4, kernel=(3, 3), stride=(1, 1))
      for v in nn.get_parameters().values():
          v.need_grad = False
      ref_g = nn.graph_def.create_graph_from_variable(
          "te_module", ref_y
      )
      y = ref_g(x)
      forward_variable_and_check_equal(ref_y, y)
  
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  from nnabla.testing import assert_allclose
  from helper import get_saved_test_model, forward_variable_and_check_equal, forward_variable, assert_topology, dump_network_topology
  import legacy_nnp_graph
  from nnabla.utils import nnp_graph
label_desc: Use image node_id 24 for calling a global function with example usage: test_save_module_grad_only_false() without return types