code: def check_normalization_params(
      f_name, p_shape, gamma_ref, beta_ref, no_scale, no_bias
  ):
      n_params = int(not no_scale) + int(not no_bias)
      assert len(nn.get_parameters()) == n_params
      assert len(nn.get_parameters(grad_only=False)) == n_params
  
      if not no_scale:
          gamma = nn.get_parameters()["{}/gamma".format(f_name)]
          assert gamma.shape == p_shape
          assert gamma.need_grad
          assert_allclose(gamma.d, gamma_ref)
  
      if not no_bias:
          beta = nn.get_parameters()["{}/beta".format(f_name)]
          assert beta.shape == p_shape
          assert beta.need_grad
          assert_allclose(beta.d, beta_ref)
  
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  import nnabla.initializer
  from nnabla.testing import assert_allclose
  from nbla_test_utils import list_context
label_desc: Use image node_id 16 for calling a global function with example usage: check_normalization_params(f_name, p_shape, gamma_ref, beta_ref, no_scale, no_bias) without return types