


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


a	: Dict      =				get_logger(__name__)






def        lowerCamelCase__   (					__lowerCamelCase    :  Union[str, Any]						,	__lowerCamelCase    :  Union[str, Any]	):
  if text.startswith(__snake_case	):
    return text[len(__snake_case	) :]
  return text  # or whatever






def        lowerCamelCase__   (					__lowerCamelCase    :  Dict	):
  return {remove_prefix(__snake_case						,	"""model."""	): v for k, v in sd.items()}






def        lowerCamelCase__   (					__lowerCamelCase    :  str	):
  __UpperCAmelCase							:			List[Any]     =						{}
  for k in state_dicts[0].keys():
    __UpperCAmelCase							:			Any     =						[sd[k] for sd in state_dicts]
    __UpperCAmelCase							:			Tuple     =						sum(__snake_case	) / len(__snake_case	)
    assert isinstance(__snake_case						,	torch.Tensor	)
    __UpperCAmelCase							:			Optional[Any]     =						new_t
  return new_sd






def        lowerCamelCase__   (					__lowerCamelCase    :  Optional[Any]						,	__lowerCamelCase    :  Union[str, Any]						,	__lowerCamelCase    :  Dict	):
  __UpperCAmelCase							:			Optional[Any]     =						AutoModelForSeqaSeqLM.from_pretrained(__snake_case	)
  if os.path.isfile(__snake_case	):
    __UpperCAmelCase							:			Optional[int]     =						[pl_ckpt_path]
  else:
    assert os.path.isdir(__snake_case	)
    __UpperCAmelCase							:			int     =						list(Path(__snake_case	).glob("""*.ckpt"""	)	)
    assert ckpt_files, f"""could not find any ckpt files inside the {pl_ckpt_path} directory"""

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

  __UpperCAmelCase							:			int     =						[sanitize(torch.load(__snake_case						,	map_location="""cpu"""	)["""state_dict"""]	) for x in ckpt_files]
  __UpperCAmelCase							:			List[str]     =						average_state_dicts(__snake_case	)

  __UpperCAmelCase   ,				__UpperCAmelCase							:			List[Any]     =						hf_model.load_state_dict(__snake_case						,	strict=__snake_case	)
  assert not missing, f"""missing keys: {missing}"""
  hf_model.save_pretrained(__snake_case	)
  try:
    __UpperCAmelCase							:			Union[str, Any]     =						AutoTokenizer.from_pretrained(__snake_case	)
    tok.save_pretrained(__snake_case	)
  except Exception:
    pass
    # dont copy tokenizer if cant


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










import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional

from .logging import get_logger


a	: Any      =				set()
a	: List[Any]      =				get_logger(__name__)






def        lowerCamelCase__   (					__lowerCamelCase    :  Optional[str] = None	):

  def decorator(__lowerCamelCase    :  Callable	):
    global _emitted_deprecation_warnings

    if inspect.isclass(__lowerCamelCase	):
      __UpperCAmelCase							:			Optional[Any]     =						deprecated_class_or_function.__init__
      __UpperCAmelCase							:			int     =						deprecated_class_or_function.__name__
    else:
      __UpperCAmelCase							:			Any     =						deprecated_class_or_function
      __UpperCAmelCase							:			Any     =						deprecated_function.__name__
      # Support deprecating __init__ class method: class name instead
      __UpperCAmelCase							:			List[str]     =						name if name != """__init__""" else deprecated_function.__qualname__.split("""."""	)[-2]

    __UpperCAmelCase							:			Union[str, Any]     =						(
        f"""{name} is deprecated and will be removed in the next major version of datasets.""" + f""" {help_message}"""
        if help_message
        else """"""
    )

    @wraps(__lowerCamelCase	)
    def wrapper(*__lowerCamelCase    :  List[str]						,	**__lowerCamelCase    :  Tuple	):
      __UpperCAmelCase							:			Optional[Any]     =						hash(__lowerCamelCase	)
      if func_hash not in _emitted_deprecation_warnings:
        warnings.warn(__lowerCamelCase						,	category=__lowerCamelCase						,	stacklevel=2	)
        _emitted_deprecation_warnings.add(__lowerCamelCase	)
      return deprecated_function(*__lowerCamelCase						,	**__lowerCamelCase	)

    __UpperCAmelCase							:			List[str]     =						"""deprecated"""

    if inspect.isclass(__lowerCamelCase	):
      __UpperCAmelCase							:			int     =						wrapper
      return deprecated_class_or_function
    else:
      return wrapper

  return decorator
class 					a					(				enum.EnumMeta     ):



      """simple docstring"""


      def __getattribute__(   cls      :    Optional[int]	,   __lowercase      :    List[Any]      )							->   str:
        __UpperCAmelCase							:			List[Any]     =						super().__getattribute__(__lowercase      )
        if isinstance(__lowercase	,   enum.Enum      ) and obj._on_access:
          obj._on_access()
        return obj
      def __getitem__(   cls      :    Union[str, Any]	,   __lowercase      :    Optional[int]      )							->   Optional[int]:
        __UpperCAmelCase							:			Union[str, Any]     =						super().__getitem__(__lowercase      )
        if member._on_access:
          member._on_access()
        return member




      def __call__(   cls      :    List[str]	,   __lowercase      :    Dict	,   __lowercase      :    List[Any]=None	,   *, __lowercase      :    Dict=None	,   __lowercase      :    Any=None	,   __lowercase      :    Optional[Any]=None	,   __lowercase      :    Dict=1      )							->   List[Any]:
        __UpperCAmelCase							:			Union[str, Any]     =						super().__call__(__lowercase	,   __lowercase	,   module=__lowercase	,   qualname=__lowercase	,   type=__lowercase	,   start=__lowercase      )
        if isinstance(__lowercase	,   enum.Enum      ) and obj._on_access:
          obj._on_access()
        return obj


class 					a					(				enum.Enum							, metaclass=lowercase__     ):



      """simple docstring"""


      def __new__(   cls      :    Dict	,   __lowercase      :    Tuple      )							->   Optional[Any]:
        __UpperCAmelCase							:			List[Any]     =						object.__new__(cls      )
        __UpperCAmelCase							:			Any     =						value
        __UpperCAmelCase							:			int     =						member.deprecate
        return member
      @property
      def 			UpperCAmelCase   (   self      :    Optional[Any]      )							->   Dict:
        return ""




      def 			UpperCAmelCase   (   self      :    str      )							->   Dict:
        __UpperCAmelCase							:			Optional[int]     =						f""" {self.help_message}""" if self.help_message else """"""
        warnings.warn(
            f"""'{self.__objclass__.__name__}' is deprecated and will be removed in the next major version of datasets."""
            + help_message	,   __lowercase	,   stacklevel=3	,   )


