code: def load_visual_params(
      params: constants.PyTree, config: ml_collections.ConfigDict
  ):
      """Load encoder parameters."""
      load_params = vit_model.load(
          init_params=params.get("img_encoder"),
          init_file=config.model.vit_model_path,
          model_cfg="",
          dont_load="MAPHead(.+)|head(.+)",
      )
  
      params = replace_dict(
          params,
          load_params,
          model_prefix_path=["img_encoder"],
          name_mapping={},
      )
      return params
  
imports: import dataclasses
  import operator
  import re
  from typing import Any, Dict, List, Mapping, Optional, Tuple, Union
  from absl import logging
  from big_vision import utils
  from big_vision.models import vit
  from clu import metric_writers
  import flax
  from flax import jax_utils
  from flax.core import frozen_dict
  import jax
  import jax.numpy
  import ml_collections
  import optax
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib import datasets
  from scenic.projects.knowledge_visual_language.models import constants
  from scenic.projects.t5 import model
  from scenic.train_lib import train_utils
  from scenic.train_lib.train_utils import TrainState
label_desc: Use image node_id 10 for calling a global function with example usage: load_visual_params(params, config) and returns: params