code: def test_group_normalization_double_backward(
      ctx,
      func_name,
      seed,
      num_groups,
      x_shape,
      batch_axis,
      channel_axis,
      eps,
      output_stat,
      no_scale,
      no_bias,
  ):
      from nbla_test_utils import backward_function_tester
  
      rng = np.random.RandomState(seed)
      x, beta, gamma = create_inputs(
          rng, x_shape, channel_axis, no_scale, no_bias
      )
      backward = [True, not no_bias, not no_scale]
      backward_function_tester(
          rng,
          F.group_normalization,
          inputs=[x, beta, gamma],
          func_args=[
              num_groups,
              channel_axis,
              batch_axis,
              eps,
              output_stat,
          ],
          atol_f=2e-4,
          backward=backward,
          ctx=ctx,
      )
  
file_path: nnabla/python/test/function/test_group_normalization.py
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  from nbla_test_utils import list_context
  from nnabla.normalization_functions import _force_list, _get_axes_excluding
label_desc: Use image node_id 6 for calling a global function with example usage: test_group_normalization_double_backward(ctx, func_name, seed, num_groups, x_shape, batch_axis, channel_axis, eps, output_stat, no_scale, no_bias) without return types