code: def compute_feature_targets(
      batch: Batch, config: ml_collections.ConfigDict
  ):
      """Compute the feature targets for feature regression.
  
      Args:
        batch: A single batch of data. This is updated with the feature target.
        config: The training configuration, used to generate the targets.
      """
      # TODO(lgeorgescu): some parameters should be modified only for one modality
      # such as patch size.
  
      batch[
          "targets"
      ] = {}  # pytype: disable=container-type-mismatch  # jax-ndarray
      feature_targets = config.masked_feature_loss.target
      for feature_target in feature_targets:
          if feature_target == avmae_base_model.FeatureTargets.RGB:
              batch["targets"][
                  feature_target
              ] = avmae_base_model.get_rgb_targets(
                  batch["inputs"][feature_target],
                  tuple(config.model.patches.size),
                  config.masked_feature_loss.get(
                      "select_central_frame"
                  ),
                  config.masked_feature_loss.get(
                      "reconstruct_grayscale", False
                  ),
                  config.masked_feature_loss.get(
                      "standardise_per_patch", False
                  ),
                  config.masked_feature_loss.get(
                      "standardise_per_patch_channels", False
                  ),
              )
          elif (
              feature_target
              == avmae_base_model.FeatureTargets.SPECTROGRAM
          ):
              batch["targets"][
                  feature_target
              ] = avmae_base_model.get_spectogram_targets(  # pylint: disable=line-too-long
                  batch["inputs"][feature_target],
                  tuple(config.model.patches.size[:2]),
                  config.masked_feature_loss.get(
                      "standardise_per_patch", False
                  ),
              )
          else:
              raise ValueError(
                  f"Unsupported feature target: {feature_target}."
              )
  
imports: import functools
  from typing import Any, Callable, Dict, Iterator, Mapping, Optional, Tuple, Type, Union
  from absl import logging
  from clu import metric_writers
  from clu import periodic_actions
  import flax
  from flax import jax_utils
  import flax.linen
  import jax
  from jax.example_libraries.optimizers import clip_grads
  import jax.numpy
  import jax.profiler
  import ml_collections
  import numpy
  from scenic.common_lib import debug_utils
  from scenic.dataset_lib import dataset_utils
  from scenic.model_lib.base_models import base_model
  from scenic.projects.av_mae import base_model
  from scenic.projects.av_mae import train_utils
  from scenic.train_lib_deprecated import lr_schedules
  from scenic.train_lib_deprecated import optimizers
  from scenic.train_lib_deprecated import pretrain_utils
  from scenic.train_lib_deprecated import train_utils
label_desc: Use image node_id 3 for calling a global function with example usage: compute_feature_targets(batch, config) without return types