






"""simple docstring"""




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

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


if is_sentencepiece_available():
					from .tokenization_big_bird import BigBirdTokenizer
else:
					UpperCamelCase							       =    None

UpperCamelCase							       =    logging.get_logger(__name__)
UpperCamelCase							       =    {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

UpperCamelCase							       =    {
    """vocab_file""": {
        """google/bigbird-roberta-base""": """https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model""",
        """google/bigbird-roberta-large""": (
            """https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"""
        ),
        """google/bigbird-base-trivia-itc""": (
            """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"""
        ),
    },
    """tokenizer_file""": {
        """google/bigbird-roberta-base""": (
            """https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json"""
        ),
        """google/bigbird-roberta-large""": (
            """https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json"""
        ),
        """google/bigbird-base-trivia-itc""": (
            """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json"""
        ),
    },
}

UpperCamelCase							       =    {
    """google/bigbird-roberta-base""": 4_096,
    """google/bigbird-roberta-large""": 4_096,
    """google/bigbird-base-trivia-itc""": 4_096,
}


UpperCamelCase							       =    """▁"""




class    lowercase_    (_UpperCAmelCase     ):
						A__	:		int       			=				VOCAB_FILES_NAMES
						A__	:		str       			=				PRETRAINED_VOCAB_FILES_MAP
						A__	:		str       			=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						A__	:		Any       			=				BigBirdTokenizer
						A__	:		str       			=				['''input_ids''', '''attention_mask''']
						A__	:		List[int]       			=				[]






						def __init__(    self     ,     a_=None     ,     a_=None     ,     a_="<unk>"     ,     a_="<s>"     ,     a_="</s>"     ,     a_="<pad>"     ,     a_="[SEP]"     ,     a_="[MASK]"     ,     a_="[CLS]"     ,     **a_     ,     )	->Any:







								'''simple docstring'''


								_a							=	AddedToken(a_     ,     lstrip=a_     ,     rstrip=a_	) if isinstance(a_     ,     a_	) else bos_token
								_a							=	AddedToken(a_     ,     lstrip=a_     ,     rstrip=a_	) if isinstance(a_     ,     a_	) else eos_token
								_a							=	AddedToken(a_     ,     lstrip=a_     ,     rstrip=a_	) if isinstance(a_     ,     a_	) else unk_token
								_a							=	AddedToken(a_     ,     lstrip=a_     ,     rstrip=a_	) if isinstance(a_     ,     a_	) else pad_token
								_a							=	AddedToken(a_     ,     lstrip=a_     ,     rstrip=a_	) if isinstance(a_     ,     a_	) else cls_token
								_a							=	AddedToken(a_     ,     lstrip=a_     ,     rstrip=a_	) if isinstance(a_     ,     a_	) else sep_token

								# Mask token behave like a normal word, i.e. include the space before it
								_a							=	AddedToken(a_     ,     lstrip=a_     ,     rstrip=a_	) if isinstance(a_     ,     a_	) else mask_token

								super().__init__(
								    a_     ,     tokenizer_file=a_     ,     bos_token=a_     ,     eos_token=a_     ,     unk_token=a_     ,     sep_token=a_     ,     pad_token=a_     ,     cls_token=a_     ,     mask_token=a_     ,     **a_     ,     )

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






						def 			lowerCamelCase__    (    self     ,     a_     ,     a_ = None	)	->List[int]:







								'''simple docstring'''


								_a							=	[self.sep_token_id]
								_a							=	[self.cls_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 			lowerCamelCase__    (    self     ,     a_     ,     a_ = None     ,     a_ = False	)	->List[int]:







								'''simple docstring'''


								if already_has_special_tokens:
										if token_ids_a is not None:
												raise ValueError(
												    "You should not supply a second sequence if the provided sequence of "
												    "ids is already formatted with special tokens for the model."	)
										return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

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






						def 			lowerCamelCase__    (    self     ,     a_     ,     a_ = 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	) * [0] + len(token_ids_a + sep	) * [1]






						def 			lowerCamelCase__    (    self     ,     a_     ,     a_ = 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(a_	):
										logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
										return
								_a							=	os.path.join(
								    a_     ,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)

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

								return (out_vocab_file,)










"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_yolos import YolosImageProcessor


UpperCamelCase							       =    logging.get_logger(__name__)




class    lowercase_    (_UpperCAmelCase     ):






      def __init__(    self     ,     *a_     ,     **a_	)	->None:







        '''simple docstring'''


        warnings.warn(
            "The class YolosFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
            " use YolosImageProcessor instead."     ,     a_     ,     )
        super().__init__(*a_     ,     **a_	)


