




import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


UpperCamelCase								=     logging.get_logger(__name__)

UpperCamelCase								=     {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase								=     {
    'vocab_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
    },
    'tokenizer_file': {
        'allenai/longformer-base-4096': (
            'https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json'
        ),
    },
}

UpperCamelCase								=     {
    'allenai/longformer-base-4096': 4096,
    'allenai/longformer-large-4096': 4096,
    'allenai/longformer-large-4096-finetuned-triviaqa': 4096,
    'allenai/longformer-base-4096-extra.pos.embd.only': 4096,
    'allenai/longformer-large-4096-extra.pos.embd.only': 4096,
}





class  __lowerCamelCase       (    UpperCamelCase__    ):




    """simple docstring"""

    snake_case__					=      VOCAB_FILES_NAMES
    snake_case__					=      PRETRAINED_VOCAB_FILES_MAP
    snake_case__					=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    snake_case__					=      ["input_ids", "attention_mask"]
    snake_case__					=      LongformerTokenizer


    def __init__(       self     :     Dict   ,	SCREAMING_SNAKE_CASE__     :     int=None   ,	SCREAMING_SNAKE_CASE__     :     List[Any]=None   ,	SCREAMING_SNAKE_CASE__     :     Tuple=None   ,	SCREAMING_SNAKE_CASE__     :     Union[str, Any]="replace"   ,	SCREAMING_SNAKE_CASE__     :     str="<s>"   ,	SCREAMING_SNAKE_CASE__     :     int="</s>"   ,	SCREAMING_SNAKE_CASE__     :     Dict="</s>"   ,	SCREAMING_SNAKE_CASE__     :     Optional[Any]="<s>"   ,	SCREAMING_SNAKE_CASE__     :     Union[str, Any]="<unk>"   ,	SCREAMING_SNAKE_CASE__     :     Tuple="<pad>"   ,	SCREAMING_SNAKE_CASE__     :     List[Any]="<mask>"   ,	SCREAMING_SNAKE_CASE__     :     str=False   ,	SCREAMING_SNAKE_CASE__     :     Any=True   ,	**SCREAMING_SNAKE_CASE__     :     Union[str, Any]   ,	)      ->       Any:
         super().__init__(
             SCREAMING_SNAKE_CASE__   ,	SCREAMING_SNAKE_CASE__   ,	tokenizer_file=SCREAMING_SNAKE_CASE__   ,	errors=SCREAMING_SNAKE_CASE__   ,	bos_token=SCREAMING_SNAKE_CASE__   ,	eos_token=SCREAMING_SNAKE_CASE__   ,	sep_token=SCREAMING_SNAKE_CASE__   ,	cls_token=SCREAMING_SNAKE_CASE__   ,	unk_token=SCREAMING_SNAKE_CASE__   ,	pad_token=SCREAMING_SNAKE_CASE__   ,	mask_token=SCREAMING_SNAKE_CASE__   ,	add_prefix_space=SCREAMING_SNAKE_CASE__   ,	trim_offsets=SCREAMING_SNAKE_CASE__   ,	**SCREAMING_SNAKE_CASE__   ,	)

         lowerCAmelCase__		= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
         if pre_tok_state.get("add_prefix_space"   ,	SCREAMING_SNAKE_CASE__   ) != add_prefix_space:
              lowerCAmelCase__		= getattr(SCREAMING_SNAKE_CASE__   ,	pre_tok_state.pop("type"   )   )
              lowerCAmelCase__		= add_prefix_space
              lowerCAmelCase__		= pre_tok_class(**SCREAMING_SNAKE_CASE__   )

         lowerCAmelCase__		= add_prefix_space

         lowerCAmelCase__		= "post_processor"
         lowerCAmelCase__		= getattr(self.backend_tokenizer   ,	SCREAMING_SNAKE_CASE__   ,	SCREAMING_SNAKE_CASE__   )
         if tokenizer_component_instance:
              lowerCAmelCase__		= json.loads(tokenizer_component_instance.__getstate__()   )

              # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
              if "sep" in state:
                   lowerCAmelCase__		= tuple(state["sep"]   )
              if "cls" in state:
                   lowerCAmelCase__		= tuple(state["cls"]   )

              lowerCAmelCase__		= False

              if state.get("add_prefix_space"   ,	SCREAMING_SNAKE_CASE__   ) != add_prefix_space:
                   lowerCAmelCase__		= add_prefix_space
                   lowerCAmelCase__		= True

              if state.get("trim_offsets"   ,	SCREAMING_SNAKE_CASE__   ) != trim_offsets:
                   lowerCAmelCase__		= trim_offsets
                   lowerCAmelCase__		= True

              if changes_to_apply:
                   lowerCAmelCase__		= getattr(SCREAMING_SNAKE_CASE__   ,	state.pop("type"   )   )
                   lowerCAmelCase__		= component_class(**SCREAMING_SNAKE_CASE__   )
                   setattr(self.backend_tokenizer   ,	SCREAMING_SNAKE_CASE__   ,	SCREAMING_SNAKE_CASE__   )


    @property
    def    a      (       self     :     Any   )      ->       str:
         if self._mask_token is None:
              if self.verbose:
                   logger.error("Using mask_token, but it is not set yet."   )
              return None
         return str(self._mask_token   )


    @mask_token.setter
    def    a      (       self     :     Union[str, Any]   ,	SCREAMING_SNAKE_CASE__     :     Optional[int]   )      ->       Optional[int]:
         lowerCAmelCase__		= AddedToken(SCREAMING_SNAKE_CASE__   ,	lstrip=SCREAMING_SNAKE_CASE__   ,	rstrip=SCREAMING_SNAKE_CASE__   ) if isinstance(SCREAMING_SNAKE_CASE__   ,	SCREAMING_SNAKE_CASE__   ) else value
         lowerCAmelCase__		= value


    def    a      (       self     :     List[str]   ,	*SCREAMING_SNAKE_CASE__     :     List[Any]   ,	**SCREAMING_SNAKE_CASE__     :     Tuple   )      ->       BatchEncoding:
         lowerCAmelCase__		= kwargs.get("is_split_into_words"   ,	SCREAMING_SNAKE_CASE__   )
         assert self.add_prefix_space or not is_split_into_words, (
             f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
             "to use it with pretokenized inputs."
         )

         return super()._batch_encode_plus(*SCREAMING_SNAKE_CASE__   ,	**SCREAMING_SNAKE_CASE__   )


    def    a      (       self     :     int   ,	*SCREAMING_SNAKE_CASE__     :     Optional[int]   ,	**SCREAMING_SNAKE_CASE__     :     Optional[int]   )      ->       BatchEncoding:
         lowerCAmelCase__		= kwargs.get("is_split_into_words"   ,	SCREAMING_SNAKE_CASE__   )

         assert self.add_prefix_space or not is_split_into_words, (
             f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
             "to use it with pretokenized inputs."
         )

         return super()._encode_plus(*SCREAMING_SNAKE_CASE__   ,	**SCREAMING_SNAKE_CASE__   )


    def    a      (       self     :     List[str]   ,	SCREAMING_SNAKE_CASE__     :     str   ,	SCREAMING_SNAKE_CASE__     :     Optional[str] = None   )      ->       Tuple[str]:
         lowerCAmelCase__		= self._tokenizer.model.save(SCREAMING_SNAKE_CASE__   ,	name=SCREAMING_SNAKE_CASE__   )
         return tuple(SCREAMING_SNAKE_CASE__   )


    def    a      (       self     :     List[str]   ,	SCREAMING_SNAKE_CASE__     :     int   ,	SCREAMING_SNAKE_CASE__     :     int=None   )      ->       Any:
         lowerCAmelCase__		= [self.bos_token_id] + token_ids_a + [self.eos_token_id]
         if token_ids_a is None:
              return output

         return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]


    def    a      (       self     :     List[str]   ,	SCREAMING_SNAKE_CASE__     :     List[int]   ,	SCREAMING_SNAKE_CASE__     :     Optional[List[int]] = None   )      ->       List[int]:
         lowerCAmelCase__		= [self.sep_token_id]
         lowerCAmelCase__		= [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 + sep + token_ids_a + sep   ) * [0]






import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()



def 							_A   (						lowerCAmelCase_     :					Optional[Any]   ,				lowerCAmelCase_     :					Tuple			):
     """simple docstring"""

     lowerCAmelCase__		= CanineConfig()
     lowerCAmelCase__		= CanineModel(lowerCAmelCase_			)
     model.eval()

     print(F'Building PyTorch model from configuration: {config}'			)

     # Load weights from tf checkpoint
     load_tf_weights_in_canine(lowerCAmelCase_   ,				lowerCAmelCase_   ,				lowerCAmelCase_			)

     # Save pytorch-model (weights and configuration)
     print(F'Save PyTorch model to {pytorch_dump_path}'			)
     model.save_pretrained(lowerCAmelCase_			)

     # Save tokenizer files
     lowerCAmelCase__		= CanineTokenizer()
     print(F'Save tokenizer files to {pytorch_dump_path}'			)
     tokenizer.save_pretrained(lowerCAmelCase_			)


if __name__ == "__main__":
     UpperCamelCase								=     argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         '--tf_checkpoint_path',
         default=None,
         type=str,
         required=True,
         help='Path to the TensorFlow checkpoint. Should end with model.ckpt',
     )
     parser.add_argument(
         '--pytorch_dump_path',
         default=None,
         type=str,
         required=True,
         help='Path to a folder where the PyTorch model will be placed.',
     )
     UpperCamelCase								=     parser.parse_args()
     convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)
