code: def test_reduce_batch_count_mean_and_var(
      self,
      x,
      input_signature,
      expected_count,
      expected_mean,
      expected_var,
      reduce_instance_dims,
      function_handler,
  ):
      @function_handler(input_signature=input_signature)
      def _reduce_batch_count_mean_and_var(x):
          result = tf_utils.reduce_batch_count_mean_and_var(
              x, reduce_instance_dims=reduce_instance_dims
          )
          # Verify that the output shapes are maintained.
          # TODO(b/178189903): This will fail if _dense_shape_default isn't set in
          # reduce_batch_count.
          if (
              not isinstance(x, tf.RaggedTensor)
              and not reduce_instance_dims
              and x.get_shape().ndims
          ):
              for tensor in result:
                  self.assertEqual(
                      x.get_shape()[1:].as_list(),
                      tensor.get_shape().as_list(),
                  )
          return result
  
      count, mean, var = _reduce_batch_count_mean_and_var(x)
      self.assertAllEqual(expected_count, count)
      self.assertAllEqual(expected_mean, mean)
      self.assertAllEqual(expected_var, var)
  
imports: import os
  import numpy
  from packaging import version
  import tensorflow
  from tensorflow_transform import analyzers
  from tensorflow_transform import annotators
  from tensorflow_transform import tf_utils
  from tensorflow_transform import test_case
  from tensorflow.python.framework import composite_tensor
label_desc: Use image node_id 16 for calling the TFUtilsTest obj's underlying member method code with example usage: obj.test_reduce_batch_count_mean_and_var(x, input_signature, expected_count, expected_mean, expected_var, reduce_instance_dims, function_handler) and returns: result