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

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


if is_sentencepiece_available():
		from .tokenization_pegasus import PegasusTokenizer
else:
		lowercase   =	None


lowercase   =	logging.get_logger(__name__)


lowercase   =	'''▁'''

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

lowercase   =	{
    '''vocab_file''': {'''google/pegasus-xsum''': '''https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'''},
    '''tokenizer_file''': {
        '''google/pegasus-xsum''': '''https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json'''
    },
}

lowercase   =	{
    '''google/pegasus-xsum''': 5_1_2,
}





class    __A(					UpperCAmelCase							):
					SCREAMING_SNAKE_CASE           =     VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE           =     PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE           =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE           =     PegasusTokenizer
					SCREAMING_SNAKE_CASE           =     ['''input_ids''', '''attention_mask''']

					def __init__(						self       :  Dict ,       __UpperCamelCase       :  List[Any]=None ,       __UpperCamelCase       :  Any=None ,       __UpperCamelCase       :  Optional[Any]="<pad>" ,       __UpperCamelCase       :  List[Any]="</s>" ,       __UpperCamelCase       :  Dict="<unk>" ,       __UpperCamelCase       :  Any="<mask_2>" ,       __UpperCamelCase       :  Dict="<mask_1>" ,       __UpperCamelCase       :  Any=None ,       __UpperCamelCase       :  Optional[int]=1_0_3 ,       **__UpperCamelCase       :  int ,       ):
												lowerCamelCase_					=       offset

												if additional_special_tokens is not None:
																			if not isinstance(__UpperCamelCase ,       __UpperCamelCase ):
																										raise TypeError(
																										    F'''additional_special_tokens should be of type {type(__UpperCamelCase )}, but is'''
																										    F''' {type(__UpperCamelCase )}''' )

																			lowerCamelCase_					=       (
																			    ([mask_token_sent] + additional_special_tokens)
																			    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
																			    else additional_special_tokens
																			)
																			# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
																			additional_special_tokens_extended += [
																			    F'''<unk_{i}>''' for i in range(len(__UpperCamelCase ) ,       self.offset - 1 )
																			]

																			if len(set(__UpperCamelCase ) ) != len(__UpperCamelCase ):
																										raise ValueError(
																										    """Please make sure that the provided additional_special_tokens do not contain an incorrectly"""
																										    F''' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.''' )
																			lowerCamelCase_					=       additional_special_tokens_extended
												else:
																			lowerCamelCase_					=       [mask_token_sent] if mask_token_sent is not None else []
																			additional_special_tokens += [F'''<unk_{i}>''' for i in range(2 ,       self.offset )]

												super().__init__(
												    __UpperCamelCase ,       tokenizer_file=__UpperCamelCase ,       pad_token=__UpperCamelCase ,       eos_token=__UpperCamelCase ,       unk_token=__UpperCamelCase ,       mask_token=__UpperCamelCase ,       mask_token_sent=__UpperCamelCase ,       offset=__UpperCamelCase ,       additional_special_tokens=__UpperCamelCase ,       **__UpperCamelCase ,       )
												lowerCamelCase_					=       vocab_file
												lowerCamelCase_					=       False if not self.vocab_file else True

					def  lowercase__   (						self       :  Optional[Any] ,       __UpperCamelCase       :  Dict ):
												lowerCamelCase_					=       set(self.all_special_ids )  # call it once instead of inside list comp
												all_special_ids.remove(self.unk_token_id )  # <unk> is only sometimes special

												if all_special_ids != set(range(len(self.additional_special_tokens ) + 3 ) ):
																			raise ValueError(
																			    """There should be 3 special tokens: mask_token, pad_token, and eos_token +"""
																			    F''' {len(self.additional_special_tokens )} additional_special_tokens, but got {all_special_ids}''' )

												return [1 if x in all_special_ids else 0 for x in seq]

					def  lowercase__   (						self       :  int ,       __UpperCamelCase       :  List ,       __UpperCamelCase       :  Optional[List] = None ,       __UpperCamelCase       :  bool = False ):
												if already_has_special_tokens:
																			return self._special_token_mask(__UpperCamelCase )
												elif token_ids_a is None:
																			return self._special_token_mask(__UpperCamelCase ) + [1]
												else:
																			return self._special_token_mask(token_ids_a + token_ids_a ) + [1]

					def  lowercase__   (						self       :  List[Any] ,       __UpperCamelCase       :  int ,       __UpperCamelCase       :  str=None ):
												if token_ids_a is None:
																			return token_ids_a + [self.eos_token_id]
												# We don't expect to process pairs, but leave the pair logic for API consistency
												return token_ids_a + token_ids_a + [self.eos_token_id]



					def  lowercase__   (						self       :  Dict ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  Optional[str] = None ):
												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(__UpperCamelCase ):
																			logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
																			return
												lowerCamelCase_					=       os.path.join(
												    __UpperCamelCase ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

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

												return (out_vocab_file,)







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


lowercase   =	{
    '''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LayoutLMv2Config'''],
    '''processing_layoutlmv2''': ['''LayoutLMv2Processor'''],
    '''tokenization_layoutlmv2''': ['''LayoutLMv2Tokenizer'''],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	['''LayoutLMv2TokenizerFast''']

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	['''LayoutLMv2FeatureExtractor''']
		lowercase   =	['''LayoutLMv2ImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	[
		    '''LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''LayoutLMv2ForQuestionAnswering''',
		    '''LayoutLMv2ForSequenceClassification''',
		    '''LayoutLMv2ForTokenClassification''',
		    '''LayoutLMv2Layer''',
		    '''LayoutLMv2Model''',
		    '''LayoutLMv2PreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
		from .processing_layoutlmva import LayoutLMvaProcessor
		from .tokenization_layoutlmva import LayoutLMvaTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_layoutlmva import (
				    LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    LayoutLMvaForQuestionAnswering,
				    LayoutLMvaForSequenceClassification,
				    LayoutLMvaForTokenClassification,
				    LayoutLMvaLayer,
				    LayoutLMvaModel,
				    LayoutLMvaPreTrainedModel,
				)
else:
		import sys

		lowercase   =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





