code: def test_instance_normalization_forward_backward(
      ctx,
      func_name,
      seed,
      x_shape,
      batch_axis,
      channel_axis,
      eps,
      output_stat,
      no_scale,
      no_bias,
      broadcast_affine_params,
  ):
      from nbla_test_utils import function_tester
  
      rng = np.random.RandomState(seed)
      x, beta, gamma = create_inputs(
          rng,
          x_shape,
          batch_axis,
          channel_axis,
          no_scale,
          no_bias,
          broadcast_affine_params,
      )
  
      function_tester(
          rng,
          F.instance_normalization,
          ref_instance_normalization,
          [x, beta, gamma],
          [channel_axis, batch_axis, eps, output_stat],
          ctx=ctx,
          func_name=func_name,
          dstep=1e-2,
          atol_b=1e-2,
          backward=[True, not no_bias, not no_scale],
          disable_half_test=True,
      )
  
file_path: nnabla/python/test/function/test_instance_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 4 for calling a global function with example usage: test_instance_normalization_forward_backward(ctx, func_name, seed, x_shape, batch_axis, channel_axis, eps, output_stat, no_scale, no_bias, broadcast_affine_params) without return types