code: def _test_shape(model_fn, backbone, input_shape, *args, **kwargs):
      # create test sample
      x = np.ones((1, *input_shape))
  
      # define model and process sample
      model = model_fn(
          backbone, input_shape=input_shape, *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 5 for calling a global function with example usage: _test_shape(model_fn, backbone, input_shape) without return types