code: def test_conv_transpose_circular(self, size, filter_shape, strides):
      if size > 2:
          test_utils.skip_test(self)
  
      x = random.normal(random.PRNGKey(1), (2, size, 3))
      dn = ("NHC", "HIO", "NHC")
      padding = "CIRCULAR"
      filter_shape = (filter_shape,)
      strides = (strides,)
  
      init_fn, _, _ = stax.ConvTranspose(
          4, filter_shape, strides, padding
      )
      _, params = init_fn(random.PRNGKey(2), x.shape)
      f_conv = self._conv_transpose_circular(
          x, params, strides, padding, dn
      )
      f_adj = self._conv_transpose_circular_via_grad(
          x, params, strides, padding, dn
      )
      self.assertAllClose(f_adj, f_conv)
  
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 4 for calling the ConvTransposeTest obj's underlying member method code with example usage: obj.test_conv_transpose_circular(size, filter_shape, strides) without return types