code: def test_get_softmax_arg_model(
      model: torch.nn.Module,
      data: np.ndarray,
      params: dict,
  ):
      model.eval()
  
      sm_model = PyTorchModel(model, softmax=True)
      no_sm_model = PyTorchModel(model, softmax=False)
  
      sm_out = sm_model.predict(x=data["x"])
      no_sm_out = no_sm_model.predict(x=data["x"])
  
      assert np.allclose(sm_out, softmax(no_sm_out)), "Test failed."
  
file_path: Quantus/tests/functions/test_pytorch_model.py
imports: from collections import OrderedDict
  from typing import Union
  import numpy
  import pytest
  import torch
  from pytest_lazyfixture import lazy_fixture
  from scipy.special import softmax
  from quantus.helpers.model.pytorch_model import PyTorchModel
label_desc: Use image node_id 2 for calling a global function with example usage: test_get_softmax_arg_model(model, data, params) without return types