code: def _compare_pooling_methods(self, weights, pooling_kwargs):
      with self.cached_session():
          compat.initialize_variables(self)
          pooled_weights_tf = tf.squeeze(
              tf.nn.pool(
                  tf.reshape(
                      weights,
                      [
                          1,
                          weights.get_shape()[0],
                          weights.get_shape()[1],
                          1,
                      ],
                  ),
                  **pooling_kwargs,
              )
          )
          pooled_weights_factorized_pool = (
              pruning_utils.factorized_pool(weights, **pooling_kwargs)
          )
          self.assertAllClose(
              self.evaluate(pooled_weights_tf),
              self.evaluate(pooled_weights_factorized_pool),
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import compat
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_utils
label_desc: Use image node_id 1 for calling the PruningUtilsParameterizedTest obj's underlying member method code with example usage: obj._compare_pooling_methods(weights, pooling_kwargs) without return types