code: def test_error_prone_param_axis(self):
      # NOTE: This test defends current, potentially error prone behaviour
      # (passing axis!=-1 and not passing param_axis). It will be removed in a
      # future version of Haiku.
      ln = layer_norm.LayerNorm(1, True, True)
      x = jnp.ones([3, 4, 5, 6])
      ln(x)
      self.assertEqual(ln.params_dict()["layer_norm/scale"].shape, (6,))
      self.assertEqual(
          ln.params_dict()["layer_norm/offset"].shape, (6,)
      )
  
imports: import functools
  import itertools
  from absl.testing import absltest
  from absl.testing import parameterized
  from haiku._src import initializers
  from haiku._src import layer_norm
  from haiku._src import test_utils
  from haiku._src import transform
  import jax
  import jax.numpy
  import numpy
label_desc: Use image node_id 14 for calling the LayerNormTest obj's underlying member method code with example usage: obj.test_error_prone_param_axis() without return types