code: def init_class_embedding(
      to_params: Dict[str, Any], class_embedding: jnp.ndarray
  ):
      """Initialize class embedding.
  
      The class embedding of the current model has a shape of (num_frames,
      channels).
  
      Args:
        to_params: Params of the current model.
        class_embedding: A 1D float tensor of shape (channels,) representing the
          class embedding from the pretrained model.
      """
      num_frames = to_params["class_embedding"].shape[0]
      to_params["class_embedding"] = jnp.tile(
          jnp.expand_dims(class_embedding, axis=0), [num_frames, 1]
      )
  
imports: from typing import Any, Dict, List, Mapping, Optional, Sequence, Union
  from absl import logging
  import flax
  import jax
  import jax.numpy
  import ml_collections
  import numpy
  from scenic.projects.vivit import model_utils
  from scenic.train_lib import train_utils
label_desc: Use image node_id 10 for calling a global function with example usage: init_class_embedding(to_params, class_embedding) without return types