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 functools
  from typing import Any, Dict, Mapping, Optional, Tuple
  from absl import logging
  import flax.linen
  from flax.training import common_utils
  import jax
  import jax.numpy
  import ml_collections
  from scenic.model_lib.base_models import base_model
  from scenic.model_lib.base_models import model_utils
  from scenic.projects.baselines import vit
  from scenic.projects.t5 import layers
  from scenic.projects.t5 import model
  from t5x import decoding
  from t5x.models import DecodeFnCallable
label_desc: Use image node_id 1 for calling a global function with example usage: l2_normalize(x, axis, eps) and returns: unknown