




'''simple docstring'''


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


_snake_case      :      Any   							=		logging.get_logger(__name__)

_snake_case      :      List[Any]   							=		{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

_snake_case      :      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'
        ),
    },
}

_snake_case      :      Union[str, Any]   							=		{
    '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 			A    (		_a    ):
							lowercase_							=				VOCAB_FILES_NAMES
							lowercase_							=				PRETRAINED_VOCAB_FILES_MAP
							lowercase_							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_							=				['input_ids', 'attention_mask']
							lowercase_							=				LongformerTokenizer







							def __init__(  self       :  str							,			lowerCAmelCase_       :  Any=None							,			lowerCAmelCase_       :  Tuple=None							,			lowerCAmelCase_       :  Dict=None							,			lowerCAmelCase_       :  Optional[int]="replace"							,			lowerCAmelCase_       :  Optional[int]="<s>"							,			lowerCAmelCase_       :  Tuple="</s>"							,			lowerCAmelCase_       :  str="</s>"							,			lowerCAmelCase_       :  List[str]="<s>"							,			lowerCAmelCase_       :  Dict="<unk>"							,			lowerCAmelCase_       :  Optional[int]="<pad>"							,			lowerCAmelCase_       :  str="<mask>"							,			lowerCAmelCase_       :  str=False							,			lowerCAmelCase_       :  List[str]=True							,			**lowerCAmelCase_       :  int							,			)			->							Any:


														"""simple docstring"""


														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_							,			)

														_a	     =				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()					)
														if pre_tok_state.get('''add_prefix_space'''							,			lowerCAmelCase_					) != add_prefix_space:
																					_a	     =				getattr(lowerCAmelCase_							,			pre_tok_state.pop('''type'''					)					)
																					_a	     =				add_prefix_space
																					_a	     =				pre_tok_class(**lowerCAmelCase_					)

														_a	     =				add_prefix_space

														_a	     =				'''post_processor'''
														_a	     =				getattr(self.backend_tokenizer							,			lowerCAmelCase_							,			lowerCAmelCase_					)
														if tokenizer_component_instance:
																					_a	     =				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:
																												_a	     =				tuple(state['''sep''']					)
																					if "cls" in state:
																												_a	     =				tuple(state['''cls''']					)

																					_a	     =				False

																					if state.get('''add_prefix_space'''							,			lowerCAmelCase_					) != add_prefix_space:
																												_a	     =				add_prefix_space
																												_a	     =				True

																					if state.get('''trim_offsets'''							,			lowerCAmelCase_					) != trim_offsets:
																												_a	     =				trim_offsets
																												_a	     =				True

																					if changes_to_apply:
																												_a	     =				getattr(lowerCAmelCase_							,			state.pop('''type'''					)					)
																												_a	     =				component_class(**lowerCAmelCase_					)
																												setattr(self.backend_tokenizer							,			lowerCAmelCase_							,			lowerCAmelCase_					)







							@property
							def    __lowerCAmelCase			(  self       :  List[Any]					)			->							str:


														"""simple docstring"""


														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    __lowerCAmelCase			(  self       :  Any							,			lowerCAmelCase_       :  Any					)			->							Any:


														"""simple docstring"""


														_a	     =				AddedToken(lowerCAmelCase_							,			lstrip=lowerCAmelCase_							,			rstrip=lowerCAmelCase_					) if isinstance(lowerCAmelCase_							,			lowerCAmelCase_					) else value
														_a	     =				value







							def    __lowerCAmelCase			(  self       :  List[str]							,			*lowerCAmelCase_       :  str							,			**lowerCAmelCase_       :  Union[str, Any]					)			->							BatchEncoding:


														"""simple docstring"""


														_a	     =				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    __lowerCAmelCase			(  self       :  Optional[Any]							,			*lowerCAmelCase_       :  List[Any]							,			**lowerCAmelCase_       :  Union[str, Any]					)			->							BatchEncoding:


														"""simple docstring"""


														_a	     =				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    __lowerCAmelCase			(  self       :  Optional[Any]							,			lowerCAmelCase_       :  str							,			lowerCAmelCase_       :  Optional[str] = None					)			->							Tuple[str]:


														"""simple docstring"""


														_a	     =				self._tokenizer.model.save(lowerCAmelCase_							,			name=lowerCAmelCase_					)
														return tuple(lowerCAmelCase_					)







							def    __lowerCAmelCase			(  self       :  str							,			lowerCAmelCase_       :  int							,			lowerCAmelCase_       :  str=None					)			->							List[str]:


														"""simple docstring"""


														_a	     =				[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    __lowerCAmelCase			(  self       :  Dict							,			lowerCAmelCase_       :  List[int]							,			lowerCAmelCase_       :  Optional[List[int]] = None					)			->							List[int]:


														"""simple docstring"""


														_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 + sep + token_ids_a + sep					) * [0]







'''simple docstring'''


import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_reformer import ReformerTokenizer
else:
				_snake_case      :      int   							=		None


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


_snake_case      :      Union[str, Any]   							=		'▁'

_snake_case      :      Any   							=		{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

_snake_case      :      List[str]   							=		{
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    },
    'tokenizer_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
        )
    },
}

_snake_case      :      Union[str, Any]   							=		{
    'google/reformer-crime-and-punishment': 524288,
}

class 			A    (		_a    ):
							lowercase_							=				VOCAB_FILES_NAMES
							lowercase_							=				PRETRAINED_VOCAB_FILES_MAP
							lowercase_							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_							=				['input_ids', 'attention_mask']
							lowercase_							=				ReformerTokenizer







							def __init__(  self       :  Any							,			lowerCAmelCase_       :  int=None							,			lowerCAmelCase_       :  Optional[Any]=None							,			lowerCAmelCase_       :  List[str]="</s>"							,			lowerCAmelCase_       :  Any="<unk>"							,			lowerCAmelCase_       :  List[str]=[]							,			**lowerCAmelCase_       :  List[Any]							,			)			->							Dict:


														"""simple docstring"""


														super().__init__(
														    lowerCAmelCase_							,			tokenizer_file=lowerCAmelCase_							,			eos_token=lowerCAmelCase_							,			unk_token=lowerCAmelCase_							,			additional_special_tokens=lowerCAmelCase_							,			**lowerCAmelCase_							,			)

														_a	     =				vocab_file
														_a	     =				False if not self.vocab_file else True







							def    __lowerCAmelCase			(  self       :  List[Any]							,			lowerCAmelCase_       :  str							,			lowerCAmelCase_       :  Optional[str] = None					)			->							Tuple[str]:


														"""simple docstring"""


														if not self.can_save_slow_tokenizer:
																					raise ValueError(
																					    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
																					    '''tokenizer.'''					)

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

														if os.path.abspath(self.vocab_file					) != os.path.abspath(lowerCAmelCase_					):
																					copyfile(self.vocab_file							,			lowerCAmelCase_					)

														return (out_vocab_file,)

