





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


_lowercase		:     Dict 					=logging.get_logger(__name__)

_lowercase		:     Union[str, Any] 					={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

_lowercase		:     Union[str, Any] 					={
    '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'
        ),
    },
}

_lowercase		:     int 					={
    '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 	UpperCamelCase_     (     snake_case__       ):
     _a			:	Optional[Any]							=				VOCAB_FILES_NAMES
     _a			:	Dict							=				PRETRAINED_VOCAB_FILES_MAP
     _a			:	List[str]							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _a			:	Union[str, Any]							=				['input_ids', 'attention_mask']
     _a			:	List[Any]							=				LongformerTokenizer



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

       lowerCamelCase_  :    Optional[Any]   	=			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
       if pre_tok_state.get('add_prefix_space'					,			lowerCamelCase	) != add_prefix_space:
         lowerCamelCase_  :    Any   	=			getattr(lowerCamelCase					,			pre_tok_state.pop('type'	)	)
         lowerCamelCase_  :    Dict   	=			add_prefix_space
         lowerCamelCase_  :    str   	=			pre_tok_class(**lowerCamelCase	)

       lowerCamelCase_  :    Optional[Any]   	=			add_prefix_space

       lowerCamelCase_  :    Dict   	=			'''post_processor'''
       lowerCamelCase_  :    Dict   	=			getattr(self.backend_tokenizer					,			lowerCamelCase					,			lowerCamelCase	)
       if tokenizer_component_instance:
         lowerCamelCase_  :    Union[str, Any]   	=			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_  :    int   	=			tuple(state['sep']	)
         if "cls" in state:
           lowerCamelCase_  :    str   	=			tuple(state['cls']	)

         lowerCamelCase_  :    List[Any]   	=			False

         if state.get('add_prefix_space'					,			lowerCamelCase	) != add_prefix_space:
           lowerCamelCase_  :    Optional[int]   	=			add_prefix_space
           lowerCamelCase_  :    Tuple   	=			True

         if state.get('trim_offsets'					,			lowerCamelCase	) != trim_offsets:
           lowerCamelCase_  :    str   	=			trim_offsets
           lowerCamelCase_  :    Optional[Any]   	=			True

         if changes_to_apply:
           lowerCamelCase_  :    List[str]   	=			getattr(lowerCamelCase					,			state.pop('type'	)	)
           lowerCamelCase_  :    str   	=			component_class(**lowerCamelCase	)
           setattr(self.backend_tokenizer					,			lowerCamelCase					,			lowerCamelCase	)



     @property
     def      __a    (		self    :    Tuple	):
       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]					,			lowerCamelCase    :    List[Any]	):
       lowerCamelCase_  :    Union[str, Any]   	=			AddedToken(lowerCamelCase					,			lstrip=lowerCamelCase					,			rstrip=lowerCamelCase	) if isinstance(lowerCamelCase					,			lowerCamelCase	) else value
       lowerCamelCase_  :    List[Any]   	=			value



     def      __a    (		self    :    Dict					,			*lowerCamelCase    :    Any					,			**lowerCamelCase    :    Dict	):
       lowerCamelCase_  :    Any   	=			kwargs.get('is_split_into_words'					,			lowerCamelCase	)
       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(*lowerCamelCase					,			**lowerCamelCase	)



     def      __a    (		self    :    Optional[int]					,			*lowerCamelCase    :    Optional[int]					,			**lowerCamelCase    :    Optional[Any]	):
       lowerCamelCase_  :    Optional[Any]   	=			kwargs.get('is_split_into_words'					,			lowerCamelCase	)

       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(*lowerCamelCase					,			**lowerCamelCase	)



     def      __a    (		self    :    Any					,			lowerCamelCase    :    Optional[int]					,			lowerCamelCase    :    str = None	):
       lowerCamelCase_  :    Optional[Any]   	=			self._tokenizer.model.save(lowerCamelCase					,			name=lowerCamelCase	)
       return tuple(lowerCamelCase	)



     def      __a    (		self    :    Dict					,			lowerCamelCase    :    Any					,			lowerCamelCase    :    List[Any]=None	):
       lowerCamelCase_  :    int   	=			[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    :    str					,			lowerCamelCase    :    Optional[int]					,			lowerCamelCase    :    int = None	):
       lowerCamelCase_  :    Optional[int]   	=			[self.sep_token_id]
       lowerCamelCase_  :    Dict   	=			[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 os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

_lowercase		:     Optional[Any] 					=[(1,)]


def 		_SCREAMING_SNAKE_CASE    (   ):
		lowerCamelCase_  :    Union[str, Any]   	=			bool(os.getenv('RUN_SLOW'       ,0	)	)
		if run_slow:
				assert True
		else:
				assert False, "should have been skipped"


def 		_SCREAMING_SNAKE_CASE    (   ):
		lowerCamelCase_  :    List[str]   	=			bool(os.getenv('RUN_SLOW'       ,0	)	)
		if run_slow and torch_device == "cuda":
				assert True
		else:
				assert False, "should have been skipped"






@require_torch
class 	UpperCamelCase_     (     unittest.TestCase       ):



					@slow
					@require_torch_gpu
					def      __a    (		self    :    Tuple	):
							check_slow_torch_cuda()



					@require_torch_gpu
					@slow
					def      __a    (		self    :    Optional[int]	):
							check_slow_torch_cuda()





					@parameterized.expand(lowerCamelCase	)
					@slow
					def      __a    (		self    :    List[str]					,			lowerCamelCase    :    Optional[Any]=None	):
							check_slow()


@slow
@require_torch_gpu
def 		_SCREAMING_SNAKE_CASE    (   ):
		check_slow_torch_cuda()


@require_torch_gpu
@slow
def 		_SCREAMING_SNAKE_CASE    (   ):
		check_slow_torch_cuda()


@slow
@pytest.mark.parametrize('param'       ,[1]	)
def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
		check_slow()





@pytest.mark.parametrize('param'       ,[1]	)
@slow
def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
		check_slow()
