code: def test_reverse_with_additional_inputs(self):
      # The layer stack below runs iteratively the update equation:
      # x_n = n * alpha * (x_{n-1} + 1)
      # with x_0 = 1, for n={1, ..., N}, where N = stack_height
      # The reverse layer stack as a result runs the update equation:
      # y_{n-1} = (N - n + 1) * alpha * (y_n + 1)
      # with y_N = 1, for n={N-1, ..., 0}, where N = stack_height
      width = 2
      batch_size = 3
      stack_height = 4
      total_multiplier = 24
      alpha = jnp.power(total_multiplier, -1.0 / stack_height)
      forward, backward = self._compute_weights(stack_height, alpha)
  
      def inner_fn(x, extra):
          # Compared to previous test we pass in the `extra` argument as an
          # additional input, in order to directly initialize the parameters to the
          # index `n` of the iteration.
          out = basic.Linear(
              x.shape[1],
              w_init=initializers.Constant(extra * jnp.eye(x.shape[1])),
              b_init=initializers.Constant(extra),
          )(x)
          return out, out
  
      @multi_transform.without_apply_rng
      @transform.transform
      def hk_fn(x, extra, reverse=False):
          return layer_stack.layer_stack(
              stack_height, with_per_layer_inputs=True
          )(inner_fn)(x, extra, reverse=reverse)
  
      extra = jnp.arange(stack_height) + 1
      extra = extra * alpha
      key_seq = base.PRNGSequence(19)
      init_value = 1 + jax.random.uniform(
          next(key_seq), [batch_size, width]
      )
      params = hk_fn.init(next(key_seq), init_value, extra)
  
      x_n, x_all = hk_fn.apply(params, init_value, extra)
      self.assertEqual(x_all.shape[0], stack_height)
      for x_t, (a, b) in zip(x_all, forward):
          np.testing.assert_allclose(x_t, a * init_value + b, rtol=1e-6)
      np.testing.assert_allclose(x_n, x_all[-1], rtol=1e-6)
  
      y_0, y_all = hk_fn.apply(params, init_value, extra, reverse=True)
      self.assertEqual(y_all.shape[0], stack_height)
      for y_t, (a, b) in zip(y_all, reversed(backward)):
          np.testing.assert_allclose(y_t, a * init_value + b, rtol=1e-6)
      np.testing.assert_allclose(y_0, y_all[0], rtol=1e-6)
  
imports: import functools
  import re
  from typing import Optional
  from absl.testing import absltest
  from absl.testing import parameterized
  from haiku._src import base
  from haiku._src import basic
  from haiku._src import config
  from haiku._src import initializers
  from haiku._src import layer_stack
  from haiku._src import module
  from haiku._src import multi_transform
  from haiku._src import transform
  from haiku._src import utils
  import jax
  import jax.numpy
  import numpy
  from scipy import stats
label_desc: Use image node_id 15 for calling the LayerStackTest obj's underlying member method code with example usage: obj.test_reverse_with_additional_inputs() and returns: out,  out, layer_stack