code: def _check_output_and_model_output_shapes(true_shape, model_shape):
      assert len(true_shape) == len(model_shape)
      for i in range(len(true_shape)):
          if true_shape[i] == N:
              assert model_shape[i] in {N, None}
          elif true_shape[i] == batch_size:
              assert model_shape[i] in {batch_size, None}
          else:
              assert model_shape[i] == true_shape[i]
  
file_path: spektral/tests/test_layers/pooling/test_global_pooling.py
imports: import numpy
  import tensorflow
  from tensorflow.keras import Input, Model
  from spektral.layers import GlobalAttentionPool, GlobalAttnSumPool, GlobalAvgPool, GlobalMaxPool, GlobalSumPool, SortPool
  from tests.test_layers.convolutional.core import _test_get_config
label_desc: Use image node_id 1 for calling a global function with example usage: _check_output_and_model_output_shapes(true_shape, model_shape) without return types