code: def test_mask_fc(
      self, same_inputs, get, concat, p, mask_axis, mask_constant
  ):
      width = 512
      n_samples = 128
      tol = 0.04
      key = random.PRNGKey(1)
  
      x1 = random.normal(key, (4, 6, 5, 7))
      x1 = test_utils.mask(x1, mask_constant, mask_axis, key, p)
  
      if same_inputs:
          x2 = None
      else:
          x2 = random.normal(key, (2, 6, 5, 7))
          x2 = test_utils.mask(x2, mask_constant, mask_axis, key, p)
  
      nn = stax.serial(
          stax.Flatten(),
          stax.FanOut(3),
          stax.parallel(
              stax.serial(
                  stax.Dense(width, 1.0, 0.1),
                  stax.Abs(),
                  stax.DotGeneral(lhs=-0.2),
                  stax.Dense(width, 1.5, 0.01),
              ),
              stax.serial(
                  stax.Dense(width, 1.1, 0.1),
                  stax.DotGeneral(rhs=0.7),
                  stax.Erf(),
                  stax.Dense(width if concat != 1 else 512, 1.5, 0.1),
              ),
              stax.serial(
                  stax.DotGeneral(rhs=0.5),
                  stax.Dense(width, 1.2),
                  stax.ABRelu(-0.2, 0.4),
                  stax.Dense(width if concat != 1 else 1024, 1.3, 0.2),
              ),
          ),
          (
              stax.FanInSum()
              if concat is None
              else stax.FanInConcat(concat)
          ),
          stax.Dense(width, 2.0, 0.01),
          stax.Relu(),
      )
  
      if get == "nngp":
          init_fn, apply_fn, kernel_fn = stax.serial(
              nn, stax.Dense(width, 1.0, 0.1)
          )
      elif get == "ntk":
          init_fn, apply_fn, kernel_fn = stax.serial(
              nn, stax.Dense(1, 1.0, 0.1)
          )
      else:
          raise ValueError(get)
  
      kernel_fn_mc = nt.monte_carlo_kernel_fn(
          init_fn=init_fn,
          apply_fn=stax.unmask_fn(apply_fn),
          key=key,
          n_samples=n_samples,
          device_count=0 if concat in (0, -2) else -1,
          implementation=_DEFAULT_TESTING_NTK_IMPLEMENTATION,
          vmap_axes=None if concat in (0, -2) else 0,
      )
  
      kernel_fn = jit(kernel_fn, static_argnames="get")
      exact = kernel_fn(x1, x2, get, mask_constant=mask_constant)
      empirical = kernel_fn_mc(
          x1, x2, get=get, mask_constant=mask_constant
      )
      test_utils.assert_close_matrices(self, empirical, exact, tol)
  
imports: 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
  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
label_desc: Use image node_id 1 for calling the MaskingTest obj's underlying member method code with example usage: obj.test_mask_fc(same_inputs, get, concat, p, mask_axis, mask_constant) without return types