code: def test_op_mean_variance_normalization(
      input_operand,
      use_stats_across_channels,
      do_variance_scaling,
      epsilon,
      output_ref,
      device_id,
      precision,
  ):
      dt_precision = PRECISION_TO_TYPE[precision]
      input_ref = AA(input_operand, dtype=dt_precision)
      a = C.input_variable(
          shape=input_ref.shape,
          dtype=sanitize_dtype_cntk(precision),
          needs_gradient=False,
          name="a",
      )
      norm_op = C.mean_variance_normalization(
          a,
          epsilon=epsilon,
          use_stats_across_channels=use_stats_across_channels,
          do_variance_scaling=do_variance_scaling,
      )
      output_test = norm_op.eval(
          {a: input_ref}, device=cntk_device(device_id)
      )
  
      assert np.allclose(output_test, output_ref, atol=1e-4)
  
imports: from __future__ import division
  import numpy
  import pytest
  import cntk
  from .ops_test_utils import unittest_helper, _test_unary_op, _test_binary_op, AA, precision, PRECISION_TO_TYPE, cntk_device
  from cntk.internal import sanitize_dtype_cntk
  from cntk.internal.utils import _ones_like, eval
label_desc: Use image node_id 21 for calling a global function with example usage: test_op_mean_variance_normalization(input_operand, use_stats_across_channels, do_variance_scaling, epsilon, output_ref, device_id, precision) without return types