hunk.code_window:     model = ResNet(**kwargs)
       model.default_cfg = copy.deepcopy(default_cfg)
       if kwargs.pop('pruned', False):
           model = adapt_model_from_file(model, variant)
       if pretrained:
           load_pretrained(
               model,
  
hunk.labels: keep keep replace keep keep keep keep
hunk.after_edit:     if pruned:
  
hunk.file_path: timm/models/resnet.py
hunk.type: replace
file: #!/usr/bin/env bash
  source /workspace/venv/bin/activate
  
  pip install -r requirements-sotabench.txt
  
  