code: def _inflate_with_mean_channel(x):
      """Inflate tensor with an extra mean channel."""
      mean_channel = jnp.mean(x, axis=-1, keepdims=True)
      y = jnp.concatenate([x, mean_channel], axis=-1)
      return y
  
imports: import functools
  import re
  from typing import Any, Callable, Dict, Optional, Sequence, Tuple
  from absl import logging
  import flax
  import flax.linen
  import jax
  import jax.numpy
  import ml_collections
  import numpy
  from scenic.common_lib import debug_utils
  from scenic.model_lib.base_models import base_model
  from scenic.model_lib.base_models import classification_model
  from scenic.model_lib.base_models import model_utils
  from scenic.model_lib.base_models.classification_model import ClassificationModel
  from scenic.model_lib.layers import nn_layers
  from scenic.projects.av_mae import model_utils
  from scenic.projects.baselines import vit
  from scenic.projects.mbt import model
  from scenic.projects.vivit import model_utils
  import scipy
label_desc: Use image node_id 2 for calling a global function with example usage: _inflate_with_mean_channel(x) and returns: y