code: def _skip_test(
      self,
      filter_shape,
      is_conv,
      is_res,
      padding,
      proj_into_2d,
      strides,
      use_pooling,
  ):
      if is_conv:
          test_utils.skip_test(self)
  
          if (
              is_res
              and is_conv
              and (
                  (strides is not None and strides != (1, 1))
                  or (padding == "VALID" and filter_shape != (1, 1))
              )
          ):
              raise absltest.SkipTest(
                  "Different paths in a residual models need to "
                  "return outputs of the same shape."
              )
      elif (
          filter_shape != FILTER_SHAPES[0]
          or padding != PADDINGS[0]
          or strides != STRIDES[0]
          or proj_into_2d != PROJECTIONS[0]
          or use_pooling
      ):
          raise absltest.SkipTest(
              "FC models do not have these parameters."
          )
  
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 1 for calling the StaxTest obj's underlying member method code with example usage: obj._skip_test(filter_shape, is_conv, is_res, padding, proj_into_2d, strides, use_pooling) without return types