



import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM





def   __snake_case			(    _UpperCAmelCase       ):
    if "model" in orig_key:
        __a		 =       orig_key.replace('''model.'''     ,				''''''       )
    if "norm1" in orig_key:
        __a		 =       orig_key.replace('''norm1'''     ,				'''attention.output.LayerNorm'''       )
    if "norm2" in orig_key:
        __a		 =       orig_key.replace('''norm2'''     ,				'''output.LayerNorm'''       )
    if "norm" in orig_key:
        __a		 =       orig_key.replace('''norm'''     ,				'''LayerNorm'''       )
    if "transformer" in orig_key:
        __a		 =       orig_key.split('''.'''       )[0].split('''_'''       )[-1]
        __a		 =       orig_key.replace(f'transformer_{layer_num}'     ,				f'encoder.layer.{layer_num}'       )
    if "mha.attn" in orig_key:
        __a		 =       orig_key.replace('''mha.attn'''     ,				'''attention.self'''       )
    if "mha" in orig_key:
        __a		 =       orig_key.replace('''mha'''     ,				'''attention'''       )
    if "W_q" in orig_key:
        __a		 =       orig_key.replace('''W_q'''     ,				'''self.query'''       )
    if "W_k" in orig_key:
        __a		 =       orig_key.replace('''W_k'''     ,				'''self.key'''       )
    if "W_v" in orig_key:
        __a		 =       orig_key.replace('''W_v'''     ,				'''self.value'''       )
    if "ff1" in orig_key:
        __a		 =       orig_key.replace('''ff1'''     ,				'''intermediate.dense'''       )
    if "ff2" in orig_key:
        __a		 =       orig_key.replace('''ff2'''     ,				'''output.dense'''       )
    if "ff" in orig_key:
        __a		 =       orig_key.replace('''ff'''     ,				'''output.dense'''       )
    if "mlm_class" in orig_key:
        __a		 =       orig_key.replace('''mlm.mlm_class'''     ,				'''cls.predictions.decoder'''       )
    if "mlm" in orig_key:
        __a		 =       orig_key.replace('''mlm'''     ,				'''cls.predictions.transform'''       )
    if "cls" not in orig_key:
        __a		 =       '''yoso.''' + orig_key

    return orig_key





def   __snake_case			(    _UpperCAmelCase     ,				_UpperCAmelCase       ):
    for key in orig_state_dict.copy().keys():
        __a		 =       orig_state_dict.pop(_UpperCAmelCase       )

        if ("pooler" in key) or ("sen_class" in key):
            continue
        else:
            __a		 =       val

    __a		 =       orig_state_dict['''cls.predictions.decoder.bias''']
    __a		 =       torch.arange(_UpperCAmelCase       ).expand((1, -1)       ) + 2

    return orig_state_dict





def   __snake_case			(    _UpperCAmelCase     ,				_UpperCAmelCase     ,				_UpperCAmelCase       ):
    __a		 =       torch.load(_UpperCAmelCase     ,				map_location='''cpu'''       )['''model_state_dict''']
    __a		 =       YosoConfig.from_json_file(_UpperCAmelCase       )
    __a		 =       YosoForMaskedLM(_UpperCAmelCase       )

    __a		 =       convert_checkpoint_helper(config.max_position_embeddings     ,				_UpperCAmelCase       )

    print(model.load_state_dict(_UpperCAmelCase       )       )
    model.eval()
    model.save_pretrained(_UpperCAmelCase       )

    print(f'Checkpoint successfuly converted. Model saved at {pytorch_dump_path}'       )


if __name__ == "__main__":
 __snake_case		:Union[str, Any]   	=  argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '''--pytorch_model_path''', default=None, type=str, required=True, help='''Path to YOSO pytorch checkpoint.'''
 )
 parser.add_argument(
     '''--config_file''',
     default=None,
     type=str,
     required=True,
     help='''The json file for YOSO model config.''',
 )
 parser.add_argument(
     '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
 )
 __snake_case		:Optional[int]   	=  parser.parse_args()
 convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)










# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union


__snake_case		:List[str]   	=  re.compile(r'''^(?P<major>\d+)''' r'''\.(?P<minor>\d+)''' r'''\.(?P<patch>\d+)$''')

@total_ordering
@dataclass
class 					_A :
       UpperCamelCase__						:					str
       UpperCamelCase__						:					Optional[str]		      =		None
       UpperCamelCase__						:					Optional[Union[str, int]]		      =		None
       UpperCamelCase__						:					Optional[Union[str, int]]		      =		None
       UpperCamelCase__						:					Optional[Union[str, int]]		      =		None



       def 	_lowerCamelCase    (	self							:  Union[str, Any]):


           '''simple docstring'''

           __a ,     __a ,     __a		 =       _str_to_version_tuple(self.version_str)



       def __repr__(	self							:  Tuple):


           '''simple docstring'''

           return F'{self.tuple[0]}.{self.tuple[1]}.{self.tuple[2]}'



       @property
       def 	_lowerCamelCase    (	self							:  Optional[int]):


           '''simple docstring'''

           return self.major, self.minor, self.patch



       def 	_lowerCamelCase    (	self							:  Any  ,	__SCREAMING_SNAKE_CASE							:  Optional[int]):


           '''simple docstring'''

           if isinstance(__SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE):
               return Version(__SCREAMING_SNAKE_CASE)
           elif isinstance(__SCREAMING_SNAKE_CASE  ,	__SCREAMING_SNAKE_CASE):
               return other
           raise TypeError(F'{other} (type {type(__SCREAMING_SNAKE_CASE)}) cannot be compared to version.')



       def __eq__(	self							:  int  ,	__SCREAMING_SNAKE_CASE							:  Any):


           '''simple docstring'''

           try:
               __a		 =       self._validate_operand(__SCREAMING_SNAKE_CASE)
           except (TypeError, ValueError):
               return False
           else:
               return self.tuple == other.tuple



       def __lt__(	self							:  str  ,	__SCREAMING_SNAKE_CASE							:  Tuple):


           '''simple docstring'''

           __a		 =       self._validate_operand(__SCREAMING_SNAKE_CASE)
           return self.tuple < other.tuple



       def __hash__(	self							:  Optional[Any]):


           '''simple docstring'''

           return hash(_version_tuple_to_str(self.tuple))



       @classmethod
       def 	_lowerCamelCase    (	cls							:  List[str]  ,	__SCREAMING_SNAKE_CASE							:  Optional[Any]):


           '''simple docstring'''

           __a		 =       {f.name for f in dataclasses.fields(cls)}
           return cls(**{k: v for k, v in dic.items() if k in field_names})





       def 	_lowerCamelCase    (	self							:  int):


           '''simple docstring'''

           return self.version_str





def   __snake_case			(    _UpperCAmelCase       ):
    __a		 =       _VERSION_REG.match(_UpperCAmelCase       )
    if not res:
        raise ValueError(f'Invalid version \'{version_str}\'. Format should be x.y.z with {{x,y,z}} being digits.'       )
    return tuple(int(_UpperCAmelCase       ) for v in [res.group('''major'''       ), res.group('''minor'''       ), res.group('''patch'''       )]       )





def   __snake_case			(    _UpperCAmelCase       ):
    return ".".join(str(_UpperCAmelCase       ) for v in version_tuple       )





