code: def initialize_one_view_from_vit_parameters(
      config: ml_collections.ConfigDict,
      params: Dict[str, Any],
      restored_model_cfg: ml_collections.ConfigDict,
      restored_params: Dict[str, Any],
      view_idx: int,
      transformer_key: str = "MultiviewEncoder",
  ):
      """Initialize one view of MTV from a ViT model.
  
      Args:
        config: Configuration for the model being updated.
        params: The parameters of the model.
        restored_model_cfg: Configuration of the model from which the
          restored_train_state come from. Usually used for some asserts.
        restored_params: Restored parameters from the given pretrained checkpoint.
        view_idx: The index of the view for which we restore the model.
        transformer_key: The key of transformer whose weights are being updated.
      """
  
      for m_key, m_params in restored_params.items():
          if m_key == "output_projection":
              pass
          elif m_key == "pre_logits":
              # We don't do a linear projection in this model. pre_logits is generated
              # as an identity transformation.
              pass
          elif m_key == "cls":
              if config.model.classifier == "token":
                  # The CLS token from a ViT model has a shape of (1, 1, channels) while
                  # the CLS token from the MTV model has a shape of (1, temporal_dims, 1,
                  # channels).
                  cls_key = f"cls_view{view_idx}"
                  temporal_dims = params[cls_key].shape[1]
                  params[cls_key] = jnp.tile(
                      m_params[jnp.newaxis, ...],
                      [1, temporal_dims, 1, 1],
                  )
          elif m_key == "Transformer":
              for tm_key, tm_params in m_params.items():
                  if (
                      "posembed_input" == tm_key
                  ):  # Might need resolution change
                      vivit_utils.init_posemb(
                          params[transformer_key],
                          m_params,
                          config,
                          restored_model_cfg,
                          is_temporal=False,
                          posemb_name=f"posembed_input_view{view_idx}",
                      )
                  elif "encoderblock" in tm_key:
                      msa_encoderblock_name = f"{tm_key}_view{view_idx}"
                      cross_view_encoderblock_name = (
                          f"cross_view_{tm_key}"
                      )
                      if (
                          msa_encoderblock_name
                          in params[transformer_key]
                      ):
                          params[transformer_key][
                              msa_encoderblock_name
                          ] = tm_params
                      elif (
                          cross_view_encoderblock_name
                          in params[transformer_key]
                      ):
                          cross_view_encoderblock_params = params[
                              transformer_key
                          ][cross_view_encoderblock_name]
                          # In vit.Encoder1DBlock(), default names are used. For example,
                          # `LayerNorm_0` stores the params for the layer norm before MSA and
                          # `LayerNorm_1` stores the params for the layer norm before MLP.
                          cross_view_encoderblock_params[
                              f"msa_ln_view{view_idx}"
                          ] = tm_params["LayerNorm_0"]
                          cross_view_encoderblock_params[
                              f"msa_view{view_idx}"
                          ] = tm_params[
                              "MultiHeadDotProductAttention_0"
                          ]
                          cross_view_encoderblock_params[
                              f"mlp_ln_view{view_idx}"
                          ] = tm_params["LayerNorm_1"]
                          cross_view_encoderblock_params[
                              f"mlp_view{view_idx}"
                          ] = tm_params["MlpBlock_0"]
                  else:
                      logging.info(
                          "Skipping restoring `%s`, in restored model but not in the"
                          " target.",
                          tm_key,
                      )
          elif m_key == "embedding":
              central_frame_init_embedding(
                  params, m_params, view_idx, config
              )
          else:
              logging.info(
                  "Skipping `%s`, in restored model but not in target",
                  m_key,
              )
  
imports: from typing import Any, Dict, List, Optional, Sequence
  from absl import logging
  import flax
  import jax.numpy
  import ml_collections
  import numpy
  from scenic.projects.vivit import model_utils
  from scenic.train_lib import train_utils
  import scipy.ndimage
label_desc: Use image node_id 10 for calling a global function with example usage: initialize_one_view_from_vit_parameters(config, params, restored_model_cfg, restored_params, view_idx, transformer_key) without return types