使用Mode.generate（）从变形金刚 - typeError：forward（）获得意外关键字参数＆＃x27; return_dict＆return_dict＆＃x27;

Question

我试图通过Transformers库中的FineTuned GPT2HeadWithValueModel进行推断。我正在使用generation_utils.py的model.generate（）方法，

我正在使用此函数来调用generate（）方法：

def top_p_sampling(text, model, tokenizer):
  encoding = tokenizer(text, return_tensors="pt")['input_ids']
  output_tensor = model.generate(
    encoding, 
    do_sample=True, 
    max_length=max_len, 
    top_k=50,
    top_p= .92,      
    temperature= .9,
    early_stopping=False)
  
  return tokenizer.decode(output_tensor[0], skip_special_tokens=True).strip()

但是当我尝试时：

text = "this is an example of input text"
comp = top_p_sampling(text, model_name, tokenizer_name)

我会收到以下错误：

TypeError: forward() got an unexpected keyword argument 'return_dict'

Full Trackback：

TypeError                                 Traceback (most recent call last)
<ipython-input-24-cc7c3f8aa367> in <module>()
      1 text = "this is an example of input text"
----> 2 comp = top_p_sampling(text, model_name, tokenizer_name)

4 frames
<ipython-input-23-a5241487f309> in top_p_sampling(text, model, tokenizer)
      9     temperature=temp,
     10     early_stopping=False,
---> 11     return_dict=False)
     12 
     13   return tokenizer.decode(output_tensor[0], skip_special_tokens=True).strip()

/usr/local/lib/python3.7/dist-packages/torch/autograd/grad_mode.py in decorate_context(*args, **kwargs)
     26         def decorate_context(*args, **kwargs):
     27             with self.__class__():
---> 28                 return func(*args, **kwargs)
     29         return cast(F, decorate_context)
     30 

/usr/local/lib/python3.7/dist-packages/transformers/generation_utils.py in generate(self, input_ids, max_length, min_length, do_sample, early_stopping, num_beams, temperature, top_k, top_p, repetition_penalty, bad_words_ids, bos_token_id, pad_token_id, eos_token_id, length_penalty, no_repeat_ngram_size, encoder_no_repeat_ngram_size, num_return_sequences, decoder_start_token_id, use_cache, num_beam_groups, diversity_penalty, prefix_allowed_tokens_fn, output_attentions, output_hidden_states, output_scores, return_dict_in_generate, **model_kwargs)
    938                 output_scores=output_scores,
    939                 return_dict_in_generate=return_dict_in_generate,
--> 940                 **model_kwargs,
    941             )
    942 

/usr/local/lib/python3.7/dist-packages/transformers/generation_utils.py in sample(self, input_ids, logits_processor, logits_warper, max_length, pad_token_id, eos_token_id, output_attentions, output_hidden_states, output_scores, return_dict_in_generate, **model_kwargs)
   1383                 return_dict=True,
   1384                 output_attentions=output_attentions,
-> 1385                 output_hidden_states=output_hidden_states,
   1386             )
   1387             next_token_logits = outputs.logits[:, -1, :]

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1101                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1102             return forward_call(*input, **kwargs)
   1103         # Do not call functions when jit is used
   1104         full_backward_hooks, non_full_backward_hooks = [], []

TypeError: forward() got an unexpected keyword argument 'return_dict'

我有点像新秀，所以我希望有人可以指出我在做什么错。多谢