
"""simple docstring"""

import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase			:       List[str]									=				logging.get_logger(__name__)

UpperCamelCase			:       List[Any]									=				{"vocab_file": "spiece.model"}

UpperCamelCase			:       Dict									=				{
    "vocab_file": {
        "bert_for_seq_generation": (
            "https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"
        ),
    }
}

UpperCamelCase			:       Tuple									=				{"bert_for_seq_generation": 5_1_2}

class __lowerCAmelCase	(   __SCREAMING_SNAKE_CASE    ):
    lowercase		     =		VOCAB_FILES_NAMES
    lowercase		     =		PRETRAINED_VOCAB_FILES_MAP
    lowercase		     =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase		     =		[]
    lowercase		     =		["input_ids", "attention_mask"]





    def __init__(			self			,  __UpperCAmelCase			,  __UpperCAmelCase="<s>"			,  __UpperCAmelCase="</s>"			,  __UpperCAmelCase="<unk>"			,  __UpperCAmelCase="<pad>"			,  __UpperCAmelCase="<::::>"			,  __UpperCAmelCase = None			,  **__UpperCAmelCase			,  ):

     '''simple docstring'''




     __UpperCamelCase       						= {} if sp_model_kwargs is None else sp_model_kwargs

     # Add extra_ids to the special token list
     super().__init__(
         bos_token=__UpperCAmelCase			,  eos_token=__UpperCAmelCase			,  unk_token=__UpperCAmelCase			,  pad_token=__UpperCAmelCase			,  sep_token=__UpperCAmelCase			,  sp_model_kwargs=self.sp_model_kwargs			,  **__UpperCAmelCase			,  )

     __UpperCamelCase       						= vocab_file

     __UpperCamelCase       						= spm.SentencePieceProcessor(**self.sp_model_kwargs   )
     self.sp_model.Load(__UpperCAmelCase   )





    @property
    def 		UpperCAmelCase      (			self   ):

     '''simple docstring'''




     return self.sp_model.get_piece_size()





    def 		UpperCAmelCase      (			self   ):

     '''simple docstring'''




     __UpperCamelCase       						= {self.convert_ids_to_tokens(__UpperCAmelCase   ): i for i in range(self.vocab_size   )}
     vocab.update(self.added_tokens_encoder   )
     return vocab





    def __getstate__(			self   ):

     '''simple docstring'''




     __UpperCamelCase       						= self.__dict__.copy()
     __UpperCamelCase       						= None
     return state





    def __setstate__(			self			,  __UpperCAmelCase   ):

     '''simple docstring'''




     __UpperCamelCase       						= d

     # for backward compatibility
     if not hasattr(self			,  'sp_model_kwargs'   ):
      __UpperCamelCase       						= {}

     __UpperCamelCase       						= spm.SentencePieceProcessor(**self.sp_model_kwargs   )
     self.sp_model.Load(self.vocab_file   )





    def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

     '''simple docstring'''




     return self.sp_model.encode(__UpperCAmelCase			,  out_type=__UpperCAmelCase   )





    def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

     '''simple docstring'''




     return self.sp_model.piece_to_id(__UpperCAmelCase   )





    def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

     '''simple docstring'''




     __UpperCamelCase       						= self.sp_model.IdToPiece(__UpperCAmelCase   )
     return token





    def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

     '''simple docstring'''




     __UpperCamelCase       						= []
     __UpperCamelCase       						= ''
     for token in tokens:
      # make sure that special tokens are not decoded using sentencepiece model
      if token in self.all_special_tokens:
       out_string += self.sp_model.decode(__UpperCAmelCase   ) + token
       __UpperCamelCase       						= []
      else:
       current_sub_tokens.append(__UpperCAmelCase   )
     out_string += self.sp_model.decode(__UpperCAmelCase   )
     return out_string.strip()







    def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase = None   ):

     '''simple docstring'''




     if not os.path.isdir(__UpperCAmelCase   ):
      logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
      return
     __UpperCamelCase       						= os.path.join(
         __UpperCAmelCase			,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

     if os.path.abspath(self.vocab_file   ) != os.path.abspath(__UpperCAmelCase   ) and os.path.isfile(self.vocab_file   ):
      copyfile(self.vocab_file			,  __UpperCAmelCase   )
     elif not os.path.isfile(self.vocab_file   ):
      with open(__UpperCAmelCase			,  'wb'   ) as fi:
       __UpperCamelCase       						= self.sp_model.serialized_model_proto()
       fi.write(__UpperCAmelCase   )

     return (out_vocab_file,)





"""simple docstring"""

import argparse
from collections import defaultdict






def 							A		(       snake_case   :Tuple       ,      snake_case   :List[Any]       ,      snake_case   :List[Any]       ,      snake_case   :Union[str, Any]       ,      snake_case   :Optional[Any]	)   ->			Union[str, Any]:
 __UpperCamelCase       						= f'{file}_{class_name}_{test_name}'
 done_test[_id] += 1

 with open(snake_case       ,      'r'	) as f:
  __UpperCamelCase       						= f.readlines()

 __UpperCamelCase       						= f'class {class_name}('
 __UpperCamelCase       						= f'{4 * " "}def {test_name}('
 __UpperCamelCase       						= f'{8 * " "}{correct_line.split()[0]}'
 __UpperCamelCase       						= f'{1_6 * " "}{correct_line.split()[0]}'
 __UpperCamelCase       						= False
 __UpperCamelCase       						= False
 __UpperCamelCase       						= False
 __UpperCamelCase       						= False
 __UpperCamelCase       						= 0
 __UpperCamelCase       						= 0

 __UpperCamelCase       						= []
 for line in lines:
  if line.startswith(snake_case	):
   __UpperCamelCase       						= True
  elif in_class and line.startswith(snake_case	):
   __UpperCamelCase       						= True
  elif in_class and in_func and (line.startswith(snake_case	) or line.startswith(snake_case	)):
   __UpperCamelCase       						= len(line.split(correct_line.split()[0]	)[0]	)
   count += 1

   if count == done_test[_id]:
    __UpperCamelCase       						= True

  if in_class and in_func and in_line:
   if ")" not in line:
    continue
   else:
    __UpperCamelCase       						= True

  if in_class and in_func and in_line and insert_line:
   new_lines.append(f'{spaces * " "}{correct_line}'	)
   __UpperCamelCase       						= __UpperCamelCase       						= __UpperCamelCase       						= __UpperCamelCase       						= False
  else:
   new_lines.append(snake_case	)

 with open(snake_case       ,      'w'	) as f:
  for line in new_lines:
   f.write(snake_case	)






def 							A		(       snake_case   :List[str]       ,      snake_case   :str=None	)   ->			Tuple:
 if fail is not None:
  with open(snake_case       ,      'r'	) as f:
   __UpperCamelCase       						= {l.strip() for l in f.readlines()}
 else:
  __UpperCamelCase       						= None

 with open(snake_case       ,      'r'	) as f:
  __UpperCamelCase       						= f.readlines()

 __UpperCamelCase       						= defaultdict(snake_case	)
 for line in correct_lines:
  __UpperCamelCase						,			__UpperCamelCase						,			__UpperCamelCase						,			__UpperCamelCase       						= line.split(';'	)
  if test_failures is None or "::".join([file, class_name, test_name]	) in test_failures:
   overwrite_file(snake_case       ,      snake_case       ,      snake_case       ,      snake_case       ,      snake_case	)


if __name__ == "__main__":
      UpperCamelCase			:       str									=				argparse.ArgumentParser()
      parser.add_argument("--correct_filename", help="filename of tests with expected result")
      parser.add_argument("--fail_filename", help="filename of test failures", type=str, default=None)
      UpperCamelCase			:       List[Any]									=				parser.parse_args()

      main(args.correct_filename, args.fail_filename)



