code: def test_double_pool(self):
      test_utils.skip_test(self)
  
      key1, key2 = random.split(random.PRNGKey(1), 2)
      x1 = jnp.cos(random.normal(key1, (2, 4, 6, 3)))
      x2 = jnp.sin(random.normal(key2, (3, 4, 6, 3)))
  
      width = 256
      single_pool = stax.serial(
          stax.ConvLocal(width, (2, 3), W_std=2.0, b_std=0.01),
          stax.AvgPool((3, 2)),
      )
      init_fn, apply_fn, kernel_fn = stax.serial(
          single_pool, stax.Flatten()
      )
      k_single = kernel_fn(x1, x2)
      self._test_against_mc(
          apply_fn, init_fn, k_single.nngp, x1, x2, 0.05
      )
  
      init_fn, apply_fn, kernel_fn = stax.serial(
          single_pool, stax.AvgPool((1, 2)), stax.Flatten()
      )
      k_double = kernel_fn(x1, x2)
      self._test_against_mc(
          apply_fn, init_fn, k_double.nngp, x1, x2, 0.05
      )
  
imports: import itertools
  import random
  import string
  import time
  from absl.testing import absltest
  from jax import default_backend
  from jax import jit
  from jax import lax
  from jax import random
  from jax import vjp
  from jax import config
  import jax.numpy
  import more_itertools
  import neural_tangents
  from neural_tangents import stax
  from neural_tangents._src.empirical import _DEFAULT_TESTING_NTK_IMPLEMENTATION
  from neural_tangents._src.utils import utils
  from tests import test_utils
  import numpy
label_desc: Use image node_id 5 for calling the ConvLocalTest obj's underlying member method code with example usage: obj.test_double_pool() without return types