docstr: Adapts the model to the current data.
  
  Calls the :class:`~avalanche.models.DynamicModule`s adaptation.
docstr_tok: ["Adapts","the","model","to","the","current","data",".","Calls","the",":","class",":","`","~avalanche.models.DynamicModule","`","s","adaptation","."]
code: def model_adaptation(self, model=None):
      """Adapts the model to the current data.
  
      Calls the :class:`~avalanche.models.DynamicModule`s adaptation.
      """
      if model is None:
          model = self.model
  
      assert self.experience is not None
  
      # For training:
      if (
          isinstance(self.experience, OnlineCLExperience)
          and self.is_training
      ):
          if self.experience.access_task_boundaries:
              avalanche_model_adaptation(
                  model, self.experience.origin_experience
              )
          else:
              avalanche_model_adaptation(model, self.experience)
      else:
          avalanche_model_adaptation(model, self.experience)
  
      return model.to(self.device)
  
file_path: avalanche/avalanche/training/templates/observation_type/batch_observation.py
imports: import warnings
  from collections import defaultdict
  from typing import List, TypeVar
  from torch import Tensor
  from avalanche.benchmarks import OnlineCLExperience
  from avalanche.models.utils import avalanche_model_adaptation
  from avalanche.training.templates.strategy_mixin_protocol import SGDStrategyProtocol
  from avalanche.models.dynamic_optimizers import reset_optimizer, update_optimizer
  from avalanche.training.utils import _at_task_boundary
label_desc: Use image node_id 2 for calling the BatchObservation obj's underlying member method code with example usage: obj.model_adaptation(model) and returns: model