code: def _test_none_shape(model_fn, backbone, *args, **kwargs):
      # define number of channels
      input_shape = kwargs.get("input_shape", None)
      n_channels = 3 if input_shape is None else input_shape[-1]
  
      # create test sample
      x = np.ones((1, 32, 32, n_channels))
  
      # define model and process sample
      model = model_fn(backbone, *args, **kwargs)
      y = model.predict(x)
  
      # check output dimensions
      assert x.shape[:-1] == y.shape[:-1]
  
file_path: segmentation_models/tests/test_models.py
imports: import os
  import pytest
  import random
  import six
  import numpy
  import segmentation_models
  from segmentation_models import Unet
  from segmentation_models import Linknet
  from segmentation_models import PSPNet
  from segmentation_models import FPN
  from segmentation_models import get_available_backbone_names
label_desc: Use image node_id 4 for calling a global function with example usage: _test_none_shape(model_fn, backbone) without return types