





import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

a__:      Union[str, Any]									=		logging.get_logger(__name__)


a__:      Any									=		{name: getattr(transformers, name + 'Fast') for name in SLOW_TO_FAST_CONVERTERS}


def 	UpperCamelCase__(       UpperCamelCase__			:       Union[str, Any] ,     UpperCamelCase__			:       Any ,     UpperCamelCase__			:       Optional[int] ,     UpperCamelCase__			:       Optional[int]  )->List[Any]:
       if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
              raise ValueError(f"Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys()  )}."  )

       if tokenizer_name is None:
              A__											=						TOKENIZER_CLASSES
       else:
              A__											=						{tokenizer_name: getattr(UpperCamelCase__ ,     tokenizer_name + '''Fast'''  )}

       logger.info(f"Loading tokenizer classes: {tokenizer_names}"  )

       for tokenizer_name in tokenizer_names:
              A__											=						TOKENIZER_CLASSES[tokenizer_name]

              A__											=						True
              if checkpoint_name is None:
                     A__											=						list(tokenizer_class.max_model_input_sizes.keys()  )
              else:
                     A__											=						[checkpoint_name]

              logger.info(f"For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}"  )

              for checkpoint in checkpoint_names:
                     logger.info(f"Loading {tokenizer_class.__class__.__name__} {checkpoint}"  )

                     # Load tokenizer
                     A__											=						tokenizer_class.from_pretrained(UpperCamelCase__ ,     force_download=UpperCamelCase__  )

                     # Save fast tokenizer
                     logger.info(f"Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}"  )

                     # For organization names we create sub-directories
                     if "/" in checkpoint:
                            A__					,	A__											=						checkpoint.split('''/'''  )
                            A__											=						os.path.join(UpperCamelCase__ ,     UpperCamelCase__  )
                     elif add_prefix:
                            A__											=						checkpoint
                            A__											=						dump_path
                     else:
                            A__											=						None
                            A__											=						dump_path

                     logger.info(f"=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}"  )

                     if checkpoint in list(tokenizer.pretrained_vocab_files_map.values()  )[0]:
                            A__											=						list(tokenizer.pretrained_vocab_files_map.values()  )[0][checkpoint]
                            A__											=						file_path.split(UpperCamelCase__  )[-1][0]
                            if next_char == "/":
                                   A__											=						os.path.join(UpperCamelCase__ ,     UpperCamelCase__  )
                                   A__											=						None

                            logger.info(f"=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}"  )

                     A__											=						tokenizer.save_pretrained(
                         UpperCamelCase__ ,     legacy_format=UpperCamelCase__ ,     filename_prefix=UpperCamelCase__  )
                     logger.info(f"=> File names {file_names}"  )

                     for file_name in file_names:
                            if not file_name.endswith('''tokenizer.json'''  ):
                                   os.remove(UpperCamelCase__  )
                                   logger.info(f"=> removing {file_name}"  )


if __name__ == "__main__":
       a__:      Optional[Any]									=		argparse.ArgumentParser()
       # Required parameters
       parser.add_argument(
           '--dump_path', default=None, type=str, required=True, help='Path to output generated fast tokenizer files.'
       )
       parser.add_argument(
           '--tokenizer_name',
           default=None,
           type=str,
           help=(
               F"Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will "
               'download and convert all the checkpoints from AWS.'
           ),
       )
       parser.add_argument(
           '--checkpoint_name',
           default=None,
           type=str,
           help='Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.',
       )
       parser.add_argument(
           '--force_download',
           action='store_true',
           help='Re-download checkpoints.',
       )
       a__:      Union[str, Any]									=		parser.parse_args()

       convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)












import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer


a__:      Optional[int]									=		logging.get_logger(__name__)

a__:      int									=		{'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

a__:      Optional[Any]									=		{
    'vocab_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/vocab.txt',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/vocab.txt',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt'
        ),
        'bert-base-multilingual-cased': 'https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt',
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt'
        ),
        'bert-base-german-dbmdz-cased': 'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt',
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json'
        ),
        'bert-base-multilingual-cased': (
            'https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-cased': (
            'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json'
        ),
    },
}

a__:      List[str]									=		{
    'bert-base-uncased': 512,
    'bert-large-uncased': 512,
    'bert-base-cased': 512,
    'bert-large-cased': 512,
    'bert-base-multilingual-uncased': 512,
    'bert-base-multilingual-cased': 512,
    'bert-base-chinese': 512,
    'bert-base-german-cased': 512,
    'bert-large-uncased-whole-word-masking': 512,
    'bert-large-cased-whole-word-masking': 512,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 512,
    'bert-large-cased-whole-word-masking-finetuned-squad': 512,
    'bert-base-cased-finetuned-mrpc': 512,
    'bert-base-german-dbmdz-cased': 512,
    'bert-base-german-dbmdz-uncased': 512,
    'TurkuNLP/bert-base-finnish-cased-v1': 512,
    'TurkuNLP/bert-base-finnish-uncased-v1': 512,
    'wietsedv/bert-base-dutch-cased': 512,
}

a__:      Optional[Any]									=		{
    'bert-base-uncased': {'do_lower_case': True},
    'bert-large-uncased': {'do_lower_case': True},
    'bert-base-cased': {'do_lower_case': False},
    'bert-large-cased': {'do_lower_case': False},
    'bert-base-multilingual-uncased': {'do_lower_case': True},
    'bert-base-multilingual-cased': {'do_lower_case': False},
    'bert-base-chinese': {'do_lower_case': False},
    'bert-base-german-cased': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking-finetuned-squad': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking-finetuned-squad': {'do_lower_case': False},
    'bert-base-cased-finetuned-mrpc': {'do_lower_case': False},
    'bert-base-german-dbmdz-cased': {'do_lower_case': False},
    'bert-base-german-dbmdz-uncased': {'do_lower_case': True},
    'TurkuNLP/bert-base-finnish-cased-v1': {'do_lower_case': False},
    'TurkuNLP/bert-base-finnish-uncased-v1': {'do_lower_case': True},
    'wietsedv/bert-base-dutch-cased': {'do_lower_case': False},
}




class     SCREAMING_SNAKE_CASE__ (						UpperCamelCase__      ):
 __SCREAMING_SNAKE_CASE							       =	VOCAB_FILES_NAMES
 __SCREAMING_SNAKE_CASE							       =	PRETRAINED_VOCAB_FILES_MAP
 __SCREAMING_SNAKE_CASE							       =	PRETRAINED_INIT_CONFIGURATION
 __SCREAMING_SNAKE_CASE							       =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __SCREAMING_SNAKE_CASE							       =	BertTokenizer



 def __init__(							self,__lowerCamelCase=None,__lowerCamelCase=None,__lowerCamelCase=True,__lowerCamelCase="[UNK]",__lowerCamelCase="[SEP]",__lowerCamelCase="[PAD]",__lowerCamelCase="[CLS]",__lowerCamelCase="[MASK]",__lowerCamelCase=True,__lowerCamelCase=None,**__lowerCamelCase,):
        super().__init__(
            __lowerCamelCase,tokenizer_file=__lowerCamelCase,do_lower_case=__lowerCamelCase,unk_token=__lowerCamelCase,sep_token=__lowerCamelCase,pad_token=__lowerCamelCase,cls_token=__lowerCamelCase,mask_token=__lowerCamelCase,tokenize_chinese_chars=__lowerCamelCase,strip_accents=__lowerCamelCase,**__lowerCamelCase,)

        A__											=						json.loads(self.backend_tokenizer.normalizer.__getstate__() )
        if (
            normalizer_state.get('''lowercase''',__lowerCamelCase ) != do_lower_case
            or normalizer_state.get('''strip_accents''',__lowerCamelCase ) != strip_accents
            or normalizer_state.get('''handle_chinese_chars''',__lowerCamelCase ) != tokenize_chinese_chars
        ):
               A__											=						getattr(__lowerCamelCase,normalizer_state.pop('''type''' ) )
               A__											=						do_lower_case
               A__											=						strip_accents
               A__											=						tokenize_chinese_chars
               A__											=						normalizer_class(**__lowerCamelCase )

        A__											=						do_lower_case



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase=None ):
        A__											=						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
               output += token_ids_a + [self.sep_token_id]

        return output



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        A__											=						[self.sep_token_id]
        A__											=						[self.cls_token_id]
        if token_ids_a is None:
               return len(cls + token_ids_a + sep ) * [0]
        return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]




 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        A__											=						self._tokenizer.model.save(__lowerCamelCase,name=__lowerCamelCase )
        return tuple(__lowerCamelCase )





