



'''simple docstring'''
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


snake_case_			:     str  	=  logging.get_logger(__name__)

snake_case_			:     Optional[int]  	=  {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

snake_case_			:     Union[str, Any]  	=  {
    'vocab_file': {
        'allegro/herbert-base-cased': 'https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json'
    },
    'merges_file': {
        'allegro/herbert-base-cased': 'https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt'
    },
}

snake_case_			:     Tuple  	=  {'allegro/herbert-base-cased': 514}
snake_case_			:     Tuple  	=  {}






class 							lowercase__     (							lowercase       ):
	lowercase__      =      VOCAB_FILES_NAMES
	lowercase__      =      PRETRAINED_VOCAB_FILES_MAP
	lowercase__      =      PRETRAINED_INIT_CONFIGURATION
	lowercase__      =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowercase__      =      HerbertTokenizer





	def __init__(			self :    Optional[int]			,lowerCamelCase__ :    List[str]=None			,lowerCamelCase__ :    Dict=None			,lowerCamelCase__ :    Tuple=None			,lowerCamelCase__ :    int="<s>"			,lowerCamelCase__ :    Dict="<unk>"			,lowerCamelCase__ :    List[str]="<pad>"			,lowerCamelCase__ :    Union[str, Any]="<mask>"			,lowerCamelCase__ :    str="</s>"			,**lowerCamelCase__ :    Tuple			,):







							'''simple docstring'''
							super().__init__(
							    lowerCamelCase__			,lowerCamelCase__			,tokenizer_file=lowerCamelCase__			,cls_token=lowerCamelCase__			,unk_token=lowerCamelCase__			,pad_token=lowerCamelCase__			,mask_token=lowerCamelCase__			,sep_token=lowerCamelCase__			,**lowerCamelCase__			,)





	def      UpperCamelCase_  (			self :    int			,lowerCamelCase__ :    List[int]			,lowerCamelCase__ :    Optional[List[int]] = None			):







							'''simple docstring'''
							_UpperCamelCase :		Optional[int]			    =       [self.cls_token_id]
							_UpperCamelCase :		Optional[int]			    =       [self.sep_token_id]
							if token_ids_a is None:
													return cls + token_ids_a + sep

							return cls + token_ids_a + sep + token_ids_a + sep





	def      UpperCamelCase_  (			self :    Tuple			,lowerCamelCase__ :    List[int]			,lowerCamelCase__ :    Optional[List[int]] = None			,lowerCamelCase__ :    bool = False			):







							'''simple docstring'''
							if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=lowerCamelCase__			,token_ids_a=lowerCamelCase__			,already_has_special_tokens=lowerCamelCase__			)

							if token_ids_a is None:
													return [1] + ([0] * len(lowerCamelCase__			)) + [1]
							return [1] + ([0] * len(lowerCamelCase__			)) + [1] + ([0] * len(lowerCamelCase__			)) + [1]





	def      UpperCamelCase_  (			self :    List[str]			,lowerCamelCase__ :    List[int]			,lowerCamelCase__ :    Optional[List[int]] = None			):







							'''simple docstring'''
							_UpperCamelCase :		Optional[Any]			    =       [self.sep_token_id]
							_UpperCamelCase :		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			) * [0] + len(token_ids_a + sep			) * [1]





	def      UpperCamelCase_  (			self :    Optional[Any]			,lowerCamelCase__ :    str			,lowerCamelCase__ :    Optional[str] = None			):







							'''simple docstring'''
							_UpperCamelCase :		List[str]			    =       self._tokenizer.model.save(lowerCamelCase__			,name=lowerCamelCase__			)
							return tuple(lowerCamelCase__			)







'''simple docstring'''
from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable


snake_case_			:     Any  	=  {
    'configuration_gpt_neox_japanese': ['GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXJapaneseConfig'],
    'tokenization_gpt_neox_japanese': ['GPTNeoXJapaneseTokenizer'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     Optional[int]  	=  [
					    'GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'GPTNeoXJapaneseForCausalLM',
					    'GPTNeoXJapaneseLayer',
					    'GPTNeoXJapaneseModel',
					    'GPTNeoXJapanesePreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
					from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gpt_neox_japanese import (
										    GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTNeoXJapaneseForCausalLM,
										    GPTNeoXJapaneseLayer,
										    GPTNeoXJapaneseModel,
										    GPTNeoXJapanesePreTrainedModel,
										)


else:
					import sys

					snake_case_			:     Any  	=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


