设置padding_side='left'后仍触发AutoModelForCausalLM解码器架构警告

使用AutoModelForCausalLM和AutoTokenizer结合DialoGPT生成文本输出时，即便采用HuggingFace官方示例代码，仍会收到如下警告：

'A decoder-only architecture is being used, but right-padding was detected! For correct generation results, please set padding_side='left' when initializing the tokenizer.'

官方示例代码如下：

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch


tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")

# Let's chat for 5 lines
for step in range(5):
    # encode the new user input, add the eos_token and return a tensor in Pytorch
    new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')

    # append the new user input tokens to the chat history
    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids

    # generated a response while limiting the total chat history to 1000 tokens, 
    chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)

    # pretty print last ouput tokens from bot
    print("DialoGPT: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))

尝试在初始化tokenizer时设置padding_side='left'但无效果，查阅资料得知DialoGPT可能需要右填充，目前仅能通过以下代码抑制日志消除警告，但这并非最优方案，寻求解决办法：

from transformers.utils import logging

logging.set_verbosity_info()

内容的提问来源于stack exchange，提问作者TurboToaster33