code: def test_input_with_unknown_leading_dimension(self):
      def get_random_shape_input():
          # Returns a Tensor of shape (?, 6)
          return tf.map_fn(
              lambda x: x * tf.random.normal([6]),
              test_utils.get_tensor_with_random_shape(),
          )
  
      # Validate the premise of the test.
      assert get_random_shape_input().shape.as_list() == [None, 6]
      test_data = self.run_one_to_many_encode_decode(
          self.default_encoding_stage(), get_random_shape_input
      )
      self.common_asserts_for_test_data(test_data)
      encoded_shape = test_data.encoded_x[
          kashin.KashinHadamardEncodingStage.ENCODED_VALUES_KEY
      ].shape
      self.assertEqual(test_data.x.shape[0], encoded_shape[0])
      self.assertEqual(8, encoded_shape[1])
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.stages.research import kashin
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.testing import test_utils
label_desc: Use image node_id 9 for calling the KashinHadamardEncodingStageTest obj's underlying member method code with example usage: obj.test_input_with_unknown_leading_dimension() and returns: tf