code: def test_nonlinear(
      self,
      model,
      width,
      same_inputs,
      is_ntk,
      filter_shape,
      proj_into_2d,
      b_std,
      W_std,
      parameterization,
      s,
  ):
      is_conv = "conv" in model
  
      if parameterization == "standard":
          width //= s
  
      padding = PADDINGS[0]
      strides = STRIDES[0]
      phi = stax.Relu()
      use_pooling, is_res = False, False
      layer_norm = None
      pool_type = "AVG"
      use_dropout = False
  
      # Check for duplicate / incorrectly-shaped NN configs / wrong backend.
      if is_conv:
          test_utils.skip_test(self)
      elif (
          proj_into_2d != PROJECTIONS[0]
          or filter_shape != FILTER_SHAPES[0]
      ):
          raise absltest.SkipTest(
              "FC models do not have these parameters."
          )
  
      net = _get_net(
          W_std=W_std,
          b_std=b_std,
          filter_shape=filter_shape,
          is_conv=is_conv,
          use_pooling=use_pooling,
          is_res=is_res,
          padding=padding,
          phi=phi,
          strides=strides,
          width=width,
          is_ntk=is_ntk,
          proj_into_2d=proj_into_2d,
          pool_type=pool_type,
          layer_norm=layer_norm,
          parameterization=parameterization,
          s=s,
          use_dropout=use_dropout,
      )
  
      _check_agreement_with_empirical(
          self,
          net=net,
          same_inputs=same_inputs,
          use_dropout=use_dropout,
          is_ntk=is_ntk,
          rtol=0.015,
          atol=1000,
      )
  
imports: import functools
  import itertools
  import random
  from absl.testing import absltest
  from jax import config
  from jax import default_backend
  from jax import jit
  from jax import random
  from jax.example_libraries import stax
  import jax.numpy
  import neural_tangents
  from neural_tangents import stax
  from neural_tangents._src.empirical import _DEFAULT_TESTING_NTK_IMPLEMENTATION
  from tests import test_utils
  import numpy
label_desc: Use image node_id 2 for calling the ParameterizationTest obj's underlying member method code with example usage: obj.test_nonlinear(model, width, same_inputs, is_ntk, filter_shape, proj_into_2d, b_std, W_std, parameterization, s) without return types