




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 				__UpperCamelCase      (			__UpperCAmelCase	):





				'''simple docstring'''



				__a				:			str					    =VOCAB_FILES_NAMES
				__a				:			Dict					    =PRETRAINED_VOCAB_FILES_MAP
				__a				:			Any					    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__a				:			int					    =["""input_ids""", """attention_mask"""]
				__a				:			int					    =LongformerTokenizer



				def __init__(			self							,			UpperCAmelCase_=None							,			UpperCAmelCase_=None							,			UpperCAmelCase_=None							,			UpperCAmelCase_="replace"							,			UpperCAmelCase_="<s>"							,			UpperCAmelCase_="</s>"							,			UpperCAmelCase_="</s>"							,			UpperCAmelCase_="<s>"							,			UpperCAmelCase_="<unk>"							,			UpperCAmelCase_="<pad>"							,			UpperCAmelCase_="<mask>"							,			UpperCAmelCase_=False							,			UpperCAmelCase_=True							,			**UpperCAmelCase_							,			):
											super().__init__(
											    UpperCAmelCase_							,			UpperCAmelCase_							,			tokenizer_file=UpperCAmelCase_							,			errors=UpperCAmelCase_							,			bos_token=UpperCAmelCase_							,			eos_token=UpperCAmelCase_							,			sep_token=UpperCAmelCase_							,			cls_token=UpperCAmelCase_							,			unk_token=UpperCAmelCase_							,			pad_token=UpperCAmelCase_							,			mask_token=UpperCAmelCase_							,			add_prefix_space=UpperCAmelCase_							,			trim_offsets=UpperCAmelCase_							,			**UpperCAmelCase_							,			)

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

											lowerCAmelCase =		add_prefix_space

											lowerCAmelCase =		'''post_processor'''
											lowerCAmelCase =		getattr(self.backend_tokenizer							,			UpperCAmelCase_							,			UpperCAmelCase_    )
											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'''							,			UpperCAmelCase_    ) != add_prefix_space:
																									lowerCAmelCase =		add_prefix_space
																									lowerCAmelCase =		True

																		if state.get('''trim_offsets'''							,			UpperCAmelCase_    ) != trim_offsets:
																									lowerCAmelCase =		trim_offsets
																									lowerCAmelCase =		True

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



				@property
				def    __snake_case		(			self    ):
											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    __snake_case		(			self							,			UpperCAmelCase_    ):
											lowerCAmelCase =		AddedToken(UpperCAmelCase_							,			lstrip=UpperCAmelCase_							,			rstrip=UpperCAmelCase_    ) if isinstance(UpperCAmelCase_							,			UpperCAmelCase_    ) else value
											lowerCAmelCase =		value



				def    __snake_case		(			self							,			*UpperCAmelCase_							,			**UpperCAmelCase_    ):
											lowerCAmelCase =		kwargs.get('''is_split_into_words'''							,			UpperCAmelCase_    )
											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(*UpperCAmelCase_							,			**UpperCAmelCase_    )



				def    __snake_case		(			self							,			*UpperCAmelCase_							,			**UpperCAmelCase_    ):
											lowerCAmelCase =		kwargs.get('''is_split_into_words'''							,			UpperCAmelCase_    )

											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(*UpperCAmelCase_							,			**UpperCAmelCase_    )



				def    __snake_case		(			self							,			UpperCAmelCase_							,			UpperCAmelCase_ = None    ):
											lowerCAmelCase =		self._tokenizer.model.save(UpperCAmelCase_							,			name=UpperCAmelCase_    )
											return tuple(UpperCAmelCase_    )



				def    __snake_case		(			self							,			UpperCAmelCase_							,			UpperCAmelCase_=None    ):
											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    __snake_case		(			self							,			UpperCAmelCase_							,			UpperCAmelCase_ = None    ):
											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]









from typing import TYPE_CHECKING

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


UpperCAmelCase_    ={"""configuration_vilt""": ["""VILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViltConfig"""]}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase_    =["""ViltFeatureExtractor"""]
		UpperCAmelCase_    =["""ViltImageProcessor"""]
		UpperCAmelCase_    =["""ViltProcessor"""]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase_    =[
		    """VILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """ViltForImageAndTextRetrieval""",
		    """ViltForImagesAndTextClassification""",
		    """ViltForTokenClassification""",
		    """ViltForMaskedLM""",
		    """ViltForQuestionAnswering""",
		    """ViltLayer""",
		    """ViltModel""",
		    """ViltPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_vilt import ViltFeatureExtractor
				from .image_processing_vilt import ViltImageProcessor
				from .processing_vilt import ViltProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vilt import (
				    VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViltForImageAndTextRetrieval,
				    ViltForImagesAndTextClassification,
				    ViltForMaskedLM,
				    ViltForQuestionAnswering,
				    ViltForTokenClassification,
				    ViltLayer,
				    ViltModel,
				    ViltPreTrainedModel,
				)


else:
		import sys

		UpperCAmelCase_    =_LazyModule(__name__, globals()["""__file__"""], _import_structure)



