code: def get_similars_idxs(cls, learn, layer_ls, **kwargs):
          "Gets the indices for the most similar images in `ds_type` dataset"
          hook = hook_output(learn.model[layer_ls[0]][layer_ls[1]][layer_ls[2]])
          dl = learn.data.fix_dl
  
          ds_actns = cls.get_actns(learn, hook=hook, dl=dl, **kwargs)
          similarities = cls.comb_similarity(ds_actns, ds_actns, **kwargs)
          idxs = cls.sort_idxs(similarities)
          return cls.padded_ds(dl, **kwargs), idxf get_similars_idxs(cls, learn, layer_ls, **kwargs):
          "Gets the indices for the most similar images in `ds_type` dataset"
          hook = hook_output(learn.model[layer_ls[0]][layer_ls[1]][layer_ls[2]])
          dl = learn.data.fix_dl
  
          ds_actns = cls.get_actns(learn, hook=hook, dl=dl, **kwargs)
          similarities = cls.comb_similarity(ds_actns, ds_actns, **kwargs)
          idxs = cls.sort_idxs(similarities)
          return cls.padded_ds(dl, **kwargs), idxs
docs: Gets the indices for the most similar images in `ds_type` dataset