code: def create_dann_like_video(
      method: Method,
      dataset,
      image_modality,
      feature_extractor,
      task_classifier,
      critic,
      **train_params,
  ):
      """DANN-based deep learning methods for domain adaptation on video data: DANN, CDAN, CDAN+E"""
  
      # Uncomment for later work.
      # Set up a new create_fewshot_trainer for video data based on original one in `domain_adapter.py`
  
      # if dataset.is_semi_supervised():
      #     return create_fewshot_trainer_video(
      #         method, dataset, feature_extractor, task_classifier, critic, **train_params
      #     )
  
      if method.is_dann_method():
          alpha = 0.0 if method is Method.Source else 1.0
          return DANNTrainerVideo(
              alpha=alpha,
              image_modality=image_modality,
              dataset=dataset,
              feature_extractor=feature_extractor,
              task_classifier=task_classifier,
              critic=critic,
              method=method,
              **train_params,
          )
      elif method.is_cdan_method():
          return CDANTrainerVideo(
              dataset=dataset,
              image_modality=image_modality,
              feature_extractor=feature_extractor,
              task_classifier=task_classifier,
              critic=critic,
              method=method,
              use_entropy=method is Method.CDAN_E,
              **train_params,
          )
      elif method is Method.WDGRL:
          return WDGRLTrainerVideo(
              dataset=dataset,
              image_modality=image_modality,
              feature_extractor=feature_extractor,
              task_classifier=task_classifier,
              critic=critic,
              method=method,
              **train_params,
          )
      else:
          raise ValueError(f"Unsupported method: {method}")
  
imports: import torch
  import kale.predict.losses
  from kale.loaddata.video_access import get_image_modality
  from kale.pipeline.domain_adapter import BaseMMDLike, CDANTrainer, DANNTrainer, GradReverse, Method, set_requires_grad, WDGRLTrainer
label_desc: Use image node_id 2 for calling a global function with example usage: create_dann_like_video(method, dataset, image_modality, feature_extractor, task_classifier, critic) and returns: DANNTrainerVideo, CDANTrainerVideo, WDGRLTrainerVideo