code: def l2_normalize(x, axis=-1, eps=1e-10):
      """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'.
      """
      denorm = (x * x).sum(axis=axis, keepdims=True) + eps
      return (x * jax.lax.rsqrt(denorm)).astype(x.dtype)
  
imports: import functools
  from typing import Optional, Sequence
  from flax import linen
  import jax
  import jax.numpy
  from scenic.projects.knowledge_visual_language.models import constants
  from t5x.examples.t5 import layers
  from t5x.examples.t5 import network
label_desc: Use image node_id 4 for calling a global function with example usage: l2_normalize(x, axis, eps) and returns: unknown