code: def testFactorizedMaxPool(self, window_shape):
      shape = [1024, 2048]
      weights = tf.Variable(
          glorot_uniform_initializer()(shape),
          shape=shape,
          name="weights",
      )
      pooling_kwargs = {
          "window_shape": window_shape,
          "pooling_type": "MAX",
          "strides": window_shape,
          "padding": "SAME",
      }
      self._compare_pooling_methods(weights, pooling_kwargs)
  
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 4 for calling the PruningUtilsParameterizedTest obj's underlying member method code with example usage: obj.testFactorizedMaxPool(window_shape) without return types