code: def _l2_normalize(x, axis=None, eps=1e-12):
      """Normalizes along dimension `axis` using an L2 norm.
  
      This specialized function exists for numerical stability reasons.
  
      Args:
        x: An input ndarray.
        axis: Dimension along which to normalize, e.g. `1` to separately normalize
          vectors in a batch. Passing `None` views `t` as a flattened vector when
          calculating the norm (equivalent to Frobenius norm).
        eps: Epsilon to avoid dividing by zero.
  
      Returns:
        An array of the same shape as 'x' L2-normalized along 'axis'.
      """
      return x * jax.lax.rsqrt(
          (x * x).sum(axis=axis, keepdims=True) + eps
      )
  
imports: import dataclasses
  import functools
  from typing import Any, Callable, Iterable, Optional, Sequence, Tuple, Union
  import jax
  import jax.numpy
  from jax import lax
  from jax.nn import initializers
  from flax.linen import dtypes, module, transforms
label_desc: Use image node_id 5 for calling a global function with example usage: _l2_normalize(x, axis, eps) and returns: unknown