




'''simple docstring'''



import os
from pathlib import Path
from typing import Dict, List

import fire
import torch

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.utils.logging import get_logger


UpperCAmelCase_    :					Optional[int]					      =						get_logger(__name__)







def      _UpperCamelCase	(_lowerCamelCase							:       str				,		_lowerCamelCase							:       str		)->				Union[str, Any]:




     '''simple docstring'''





     if text.startswith(_lowerCamelCase		):
          return text[len(_lowerCamelCase		) :]
     return text  # or whatever







def      _UpperCamelCase	(_lowerCamelCase							:       Any		)->				List[Any]:




     '''simple docstring'''





     return {remove_prefix(_lowerCamelCase				,		'''model.'''		): v for k, v in sd.items()}







def      _UpperCamelCase	(_lowerCamelCase							:       List[Dict[str, torch.Tensor]]		)->				Tuple:




     '''simple docstring'''





     __snake_case         =					{}
     for k in state_dicts[0].keys():
          __snake_case         =					[sd[k] for sd in state_dicts]
          __snake_case         =					sum(_lowerCamelCase		) / len(_lowerCamelCase		)
          assert isinstance(_lowerCamelCase				,		torch.Tensor		)
          __snake_case         =					new_t
     return new_sd







def      _UpperCamelCase	(_lowerCamelCase							:       str				,		_lowerCamelCase							:       str				,		_lowerCamelCase							:       str		)->				None:




     '''simple docstring'''





     __snake_case         =					AutoModelForSeqaSeqLM.from_pretrained(_lowerCamelCase		)
     if os.path.isfile(_lowerCamelCase		):
          __snake_case         =					[pl_ckpt_path]
     else:
          assert os.path.isdir(_lowerCamelCase		)
          __snake_case         =					list(Path(_lowerCamelCase		).glob('''*.ckpt'''		)		)
          assert ckpt_files, f'''could not find any ckpt files inside the {pl_ckpt_path} directory'''

     if len(_lowerCamelCase		) > 1:
          logger.info(f'''averaging the weights of {ckpt_files}'''		)

     __snake_case         =					[sanitize(torch.load(_lowerCamelCase				,		map_location='''cpu'''		)['''state_dict''']		) for x in ckpt_files]
     __snake_case         =					average_state_dicts(_lowerCamelCase		)

     __snake_case   ,      __snake_case         =					hf_model.load_state_dict(_lowerCamelCase				,		strict=_lowerCamelCase		)
     assert not missing, f'''missing keys: {missing}'''
     hf_model.save_pretrained(_lowerCamelCase		)
     try:
          __snake_case         =					AutoTokenizer.from_pretrained(_lowerCamelCase		)
          tok.save_pretrained(_lowerCamelCase		)
     except Exception:
          pass
          # dont copy tokenizer if cant


if __name__ == "__main__":
     fire.Fire(convert_pl_to_hf)












'''simple docstring'''



def      _UpperCamelCase	(_lowerCamelCase							:       list				,		_lowerCamelCase							:       int		)->				int:




     '''simple docstring'''





     for index, item in enumerate(_lowerCamelCase		):
          if item == target:
               return index
     return -1







def      _UpperCamelCase	(_lowerCamelCase							:       list				,		_lowerCamelCase							:       int				,		_lowerCamelCase							:       int				,		_lowerCamelCase							:       int		)->				int:




     '''simple docstring'''





     if not (0 <= high < len(_lowerCamelCase		) and 0 <= low < len(_lowerCamelCase		)):
          raise Exception('''Invalid upper or lower bound!'''		)
     if high < low:
          return -1
     if sequence[low] == target:
          return low
     if sequence[high] == target:
          return high
     return rec_linear_search(_lowerCamelCase				,		low + 1				,		high - 1				,		_lowerCamelCase		)


if __name__ == "__main__":
     UpperCAmelCase_    :					List[Any]					      =						input('''Enter numbers separated by comma:\n''').strip()
     UpperCAmelCase_    :					Optional[int]					      =						[int(item.strip()) for item in user_input.split(''',''')]

     UpperCAmelCase_    :					List[str]					      =						int(input('''Enter a single number to be found in the list:\n''').strip())
     UpperCAmelCase_    :					Optional[int]					      =						linear_search(sequence, target)
     if result != -1:
          print(F"""linear_search({sequence}, {target}) = {result}""")
     else:
          print(F"""{target} was not found in {sequence}""")






