text: import torch
  from torch import optim
  
  from ..models.epic.tsn import TSN
  
  def load_model(num_classes, input_frame_length):
      #class_counts = (num_classes,352)
      class_counts = num_classes
      segment_count = input_frame_length
      base_model = 'featurefc'
  #    repo = 'epic-kitchens/action-models'
  #    model = torch.hub.load(repo, 'TRN', class_counts, segment_count, 'RGB',
  #            base_model = base_model,
  #            pretrained='epic-kitchens')
  
      # Use TRN if you want to add an fc layer after the base model.
      # Use STRN if you don't.
      model = TSN(class_counts, segment_count, 'RGB',
              base_model = base_model,
              img_feature_dim=64)
  
  
      return model
  
  
  def load_pretrained(model):
      return None
  
  def get_optim_policies(model):
      return model.parameters()     # no policies
  
  ddp_find_unused_parameters = True
  