code: import argparse
  import csv
  
  import torch
  import transformers
  
  
  def parse_arguments():
      parser = argparse.ArgumentParser(description="MiniConf Portal Command Line")
  
      parser.add_argument("papers", default=False, help="papers file to parse")
      return parser.parse_args()
  
  
  if __name__ == "__main__":
      args = parse_arguments()
      tokenizer = transformers.AutoTokenizer.from_pretrained("deepset/sentence_bert")
  
      model = transformers.AutoModel.from_pretrained("deepset/sentence_bert")
      model.eval()
  
      with open(args.papers, "r",encoding='utf-8') as f:
          abstracts = list(csv.DictReader(f))
          all_abstracts = torch.zeros(len(abstracts), 768)
          with torch.no_grad():
              for i, row in enumerate(abstracts):
  
                  input_ids = torch.tensor([tokenizer.encode(row["abstract"])][:512])
                  all_hidden_states, _ = model(input_ids)[-2:]
                  all_abstracts[i] = all_hidden_states.mean(0).mean(0)
                  print(i)
                  print(row['author'])
      torch.save(all_abstracts, "embeddings.torch")
  
apis: torch.save torch.no_grad