




"""simple docstring"""


import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase								=						logging.get_logger(__name__)


lowerCAmelCase								=						{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all MVP models at https://huggingface.co/models?filter=mvp
lowerCAmelCase								=						{
    """vocab_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json""",
    },
    """added_tokens.json""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json""",
    },
    """merges_file""": {
        """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt""",
    },
}

lowerCAmelCase								=						{
    """RUCAIBox/mvp""": 10_24,
}






@lru_cache()
def        lowerCAmelCase_       (		)       ->Tuple:
			lowerCamelCase__     :					List[str]		=(
			    list(range(ord('!'      )							,   ord('~'      ) + 1      )      ) + list(range(ord('¡'      )							,   ord('¬'      ) + 1      )      ) + list(range(ord('®'      )							,   ord('ÿ'      ) + 1      )      )
			)
			lowerCamelCase__     :					int		=bs[:]
			lowerCamelCase__     :					int		=0
			for b in range(2**8      ):
						if b not in bs:
									bs.append(snake_case_      )
									cs.append(2**8 + n      )
									n += 1
			lowerCamelCase__     :					Optional[Any]		=[chr(snake_case_      ) for n in cs]
			return dict(zip(snake_case_							,   snake_case_      )      )






def        lowerCAmelCase_       (		snake_case_		:      Dict      )       ->int:
			lowerCamelCase__     :					List[Any]		=set()
			lowerCamelCase__     :					List[Any]		=word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)      )
						lowerCamelCase__     :					int		=char
			return pairs

class    A_     (					A__       ):



							"""simple docstring"""






							SCREAMING_SNAKE_CASE_     				=       VOCAB_FILES_NAMES
							SCREAMING_SNAKE_CASE_     				=       PRETRAINED_VOCAB_FILES_MAP
							SCREAMING_SNAKE_CASE_     				=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							SCREAMING_SNAKE_CASE_     				=       ["""input_ids""", """attention_mask"""]





							def __init__(  self  :int					,							lowerCamelCase_  :Tuple					,							lowerCamelCase_  :Dict					,							lowerCamelCase_  :Union[str, Any]="replace"					,							lowerCamelCase_  :str="<s>"					,							lowerCamelCase_  :Optional[Any]="</s>"					,							lowerCamelCase_  :Any="</s>"					,							lowerCamelCase_  :Union[str, Any]="<s>"					,							lowerCamelCase_  :Union[str, Any]="<unk>"					,							lowerCamelCase_  :List[Any]="<pad>"					,							lowerCamelCase_  :Any="<mask>"					,							lowerCamelCase_  :Union[str, Any]=False					,							**lowerCamelCase_  :Tuple					,							):





										"""simple docstring"""

										lowerCamelCase__     :					int		=AddedToken(lowerCamelCase_					,							lstrip=lowerCamelCase_					,							rstrip=lowerCamelCase_	) if isinstance(lowerCamelCase_					,							lowerCamelCase_	) else bos_token
										lowerCamelCase__     :					Union[str, Any]		=AddedToken(lowerCamelCase_					,							lstrip=lowerCamelCase_					,							rstrip=lowerCamelCase_	) if isinstance(lowerCamelCase_					,							lowerCamelCase_	) else eos_token
										lowerCamelCase__     :					Optional[int]		=AddedToken(lowerCamelCase_					,							lstrip=lowerCamelCase_					,							rstrip=lowerCamelCase_	) if isinstance(lowerCamelCase_					,							lowerCamelCase_	) else sep_token
										lowerCamelCase__     :					Optional[int]		=AddedToken(lowerCamelCase_					,							lstrip=lowerCamelCase_					,							rstrip=lowerCamelCase_	) if isinstance(lowerCamelCase_					,							lowerCamelCase_	) else cls_token
										lowerCamelCase__     :					List[str]		=AddedToken(lowerCamelCase_					,							lstrip=lowerCamelCase_					,							rstrip=lowerCamelCase_	) if isinstance(lowerCamelCase_					,							lowerCamelCase_	) else unk_token
										lowerCamelCase__     :					Optional[Any]		=AddedToken(lowerCamelCase_					,							lstrip=lowerCamelCase_					,							rstrip=lowerCamelCase_	) if isinstance(lowerCamelCase_					,							lowerCamelCase_	) else pad_token

										# Mask token behave like a normal word, i.e. include the space before it
										lowerCamelCase__     :					Optional[int]		=AddedToken(lowerCamelCase_					,							lstrip=lowerCamelCase_					,							rstrip=lowerCamelCase_	) if isinstance(lowerCamelCase_					,							lowerCamelCase_	) else mask_token

										super().__init__(
										    errors=lowerCamelCase_					,							bos_token=lowerCamelCase_					,							eos_token=lowerCamelCase_					,							unk_token=lowerCamelCase_					,							sep_token=lowerCamelCase_					,							cls_token=lowerCamelCase_					,							pad_token=lowerCamelCase_					,							mask_token=lowerCamelCase_					,							add_prefix_space=lowerCamelCase_					,							**lowerCamelCase_					,							)
										with open(lowerCamelCase_					,							encoding='utf-8'	) as vocab_handle:
													lowerCamelCase__     :					Dict		=json.load(lowerCamelCase_	)
										lowerCamelCase__     :					Optional[int]		={v: k for k, v in self.encoder.items()}
										lowerCamelCase__     :					int		=errors  # how to handle errors in decoding
										lowerCamelCase__     :					Any		=bytes_to_unicode()
										lowerCamelCase__     :					Optional[Any]		={v: k for k, v in self.byte_encoder.items()}
										with open(lowerCamelCase_					,							encoding='utf-8'	) as merges_handle:
													lowerCamelCase__     :					Tuple		=merges_handle.read().split('\n'	)[1:-1]
										lowerCamelCase__     :					List[str]		=[tuple(merge.split()	) for merge in bpe_merges]
										lowerCamelCase__     :					Any		=dict(zip(lowerCamelCase_					,							range(len(lowerCamelCase_	)	)	)	)
										lowerCamelCase__     :					str		={}
										lowerCamelCase__     :					int		=add_prefix_space

										# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
										lowerCamelCase__     :					Tuple		=re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'	)





							@property
							def 				UpperCAmelCase__							(  self  :int	):





										"""simple docstring"""

										return len(self.encoder	)





							def 				UpperCAmelCase__							(  self  :List[str]	):





										"""simple docstring"""

										return dict(self.encoder					,							**self.added_tokens_encoder	)





							def 				UpperCAmelCase__							(  self  :int					,							lowerCamelCase_  :Dict	):





										"""simple docstring"""

										if token in self.cache:
													return self.cache[token]
										lowerCamelCase__     :					List[Any]		=tuple(lowerCamelCase_	)
										lowerCamelCase__     :					str		=get_pairs(lowerCamelCase_	)

										if not pairs:
													return token

										while True:
													lowerCamelCase__     :					List[Any]		=min(lowerCamelCase_					,							key=lambda lowerCamelCase_	: self.bpe_ranks.get(lowerCamelCase_					,							float('inf'	)	)	)
													if bigram not in self.bpe_ranks:
																break
													lowerCamelCase__     :					Any		=bigram
													lowerCamelCase__     :					Optional[int]		=[]
													lowerCamelCase__     :					str		=0
													while i < len(lowerCamelCase_	):
																try:
																			lowerCamelCase__     :					Optional[Any]		=word.index(lowerCamelCase_					,							lowerCamelCase_	)
																except ValueError:
																			new_word.extend(word[i:]	)
																			break
																else:
																			new_word.extend(word[i:j]	)
																			lowerCamelCase__     :					Optional[Any]		=j

																if word[i] == first and i < len(lowerCamelCase_	) - 1 and word[i + 1] == second:
																			new_word.append(first + second	)
																			i += 2
																else:
																			new_word.append(word[i]	)
																			i += 1
													lowerCamelCase__     :					Optional[int]		=tuple(lowerCamelCase_	)
													lowerCamelCase__     :					Any		=new_word
													if len(lowerCamelCase_	) == 1:
																break
													else:
																lowerCamelCase__     :					List[str]		=get_pairs(lowerCamelCase_	)
										lowerCamelCase__     :					str		=' '.join(lowerCamelCase_	)
										lowerCamelCase__     :					Tuple		=word
										return word





							def 				UpperCAmelCase__							(  self  :Dict					,							lowerCamelCase_  :Tuple	):





										"""simple docstring"""

										lowerCamelCase__     :					Tuple		=[]
										for token in re.findall(self.pat					,							lowerCamelCase_	):
													lowerCamelCase__     :					List[str]		=''.join(
													    self.byte_encoder[b] for b in token.encode('utf-8'	)	)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
													bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase_	).split(' '	)	)
										return bpe_tokens





							def 				UpperCAmelCase__							(  self  :str					,							lowerCamelCase_  :Tuple	):





										"""simple docstring"""

										return self.encoder.get(lowerCamelCase_					,							self.encoder.get(self.unk_token	)	)





							def 				UpperCAmelCase__							(  self  :Union[str, Any]					,							lowerCamelCase_  :str	):





										"""simple docstring"""

										return self.decoder.get(lowerCamelCase_	)





							def 				UpperCAmelCase__							(  self  :int					,							lowerCamelCase_  :str	):





										"""simple docstring"""

										lowerCamelCase__     :					List[Any]		=''.join(lowerCamelCase_	)
										lowerCamelCase__     :					List[Any]		=bytearray([self.byte_decoder[c] for c in text]	).decode('utf-8'					,							errors=self.errors	)
										return text





							def 				UpperCAmelCase__							(  self  :Any					,							lowerCamelCase_  :str					,							lowerCamelCase_  :Optional[str] = None	):





										"""simple docstring"""

										if not os.path.isdir(lowerCamelCase_	):
													logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
													return
										lowerCamelCase__     :					List[str]		=os.path.join(
										    lowerCamelCase_					,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
										lowerCamelCase__     :					Any		=os.path.join(
										    lowerCamelCase_					,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']	)

										with open(lowerCamelCase_					,							'w'					,							encoding='utf-8'	) as f:
													f.write(json.dumps(self.encoder					,							indent=2					,							sort_keys=lowerCamelCase_					,							ensure_ascii=lowerCamelCase_	) + '\n'	)

										lowerCamelCase__     :					Optional[Any]		=0
										with open(lowerCamelCase_					,							'w'					,							encoding='utf-8'	) as writer:
													writer.write('#version: 0.2\n'	)
													for bpe_tokens, token_index in sorted(self.bpe_ranks.items()					,							key=lambda lowerCamelCase_	: kv[1]	):
																if index != token_index:
																			logger.warning(
																			    f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
																			    ' Please check that the tokenizer is not corrupted!'	)
																			lowerCamelCase__     :					str		=token_index
																writer.write(' '.join(lowerCamelCase_	) + '\n'	)
																index += 1

										return vocab_file, merge_file





							def 				UpperCAmelCase__							(  self  :Dict					,							lowerCamelCase_  :List[int]					,							lowerCamelCase_  :Optional[List[int]] = None	):





										"""simple docstring"""

										if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										lowerCamelCase__     :					Optional[Any]		=[self.cls_token_id]
										lowerCamelCase__     :					Any		=[self.sep_token_id]
										return cls + token_ids_a + sep + sep + token_ids_a + sep





							def 				UpperCAmelCase__							(  self  :str					,							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, 1] + ([0] * len(lowerCamelCase_	)) + [1]





							def 				UpperCAmelCase__							(  self  :Dict					,							lowerCamelCase_  :List[int]					,							lowerCamelCase_  :Optional[List[int]] = None	):





										"""simple docstring"""

										lowerCamelCase__     :					int		=[self.sep_token_id]
										lowerCamelCase__     :					List[Any]		=[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]





							def 				UpperCAmelCase__							(  self  :Optional[int]					,							lowerCamelCase_  :Dict					,							lowerCamelCase_  :List[str]=False					,							**lowerCamelCase_  :Tuple	):





										"""simple docstring"""

										lowerCamelCase__     :					Tuple		=kwargs.pop('add_prefix_space'					,							self.add_prefix_space	)
										if (is_split_into_words or add_prefix_space) and (len(lowerCamelCase_	) > 0 and not text[0].isspace()):
													lowerCamelCase__     :					str		=' ' + text
										return (text, kwargs)

"""simple docstring"""


from typing import TYPE_CHECKING

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


lowerCAmelCase								=						{
    """configuration_deberta_v2""": ["""DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DebertaV2Config""", """DebertaV2OnnxConfig"""],
    """tokenization_deberta_v2""": ["""DebertaV2Tokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						["""DebertaV2TokenizerFast"""]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						[
							    """TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFDebertaV2ForMaskedLM""",
							    """TFDebertaV2ForQuestionAnswering""",
							    """TFDebertaV2ForSequenceClassification""",
							    """TFDebertaV2ForTokenClassification""",
							    """TFDebertaV2Model""",
							    """TFDebertaV2PreTrainedModel""",
							]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						[
							    """DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """DebertaV2ForMaskedLM""",
							    """DebertaV2ForMultipleChoice""",
							    """DebertaV2ForQuestionAnswering""",
							    """DebertaV2ForSequenceClassification""",
							    """DebertaV2ForTokenClassification""",
							    """DebertaV2Model""",
							    """DebertaV2PreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_deberta_va import (
							    DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    DebertaVaConfig,
							    DebertaVaOnnxConfig,
							)
							from .tokenization_deberta_va import DebertaVaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_deberta_va import (
														    TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFDebertaVaForMaskedLM,
														    TFDebertaVaForQuestionAnswering,
														    TFDebertaVaForSequenceClassification,
														    TFDebertaVaForTokenClassification,
														    TFDebertaVaModel,
														    TFDebertaVaPreTrainedModel,
														)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_deberta_va import (
														    DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DebertaVaForMaskedLM,
														    DebertaVaForMultipleChoice,
														    DebertaVaForQuestionAnswering,
														    DebertaVaForSequenceClassification,
														    DebertaVaForTokenClassification,
														    DebertaVaModel,
														    DebertaVaPreTrainedModel,
														)

else:
							import sys

							lowerCAmelCase								=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)