code: def testIsPruned2by4(
      self, weight, last_channel, expected, m_by_n=(2, 4)
  ):
      if last_channel == "C_OUT":
          weight = tf.transpose(tf.constant(weight))
      elif last_channel == "C_IN":
          weight = tf.constant(weight)
      answer = pruning_utils.is_pruned_m_by_n(
          weight, m_by_n, last_channel
      )
      self.assertEqual(answer, expected)
  
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 IsPrunedMbyNTest obj's underlying member method code with example usage: obj.testIsPruned2by4(weight, last_channel, expected, m_by_n) without return types