





'''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__      :   int      	=			logging.get_logger(__name__)


lowerCAmelCase__      :   Optional[Any]      	=			{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all MVP models at https://huggingface.co/models?filter=mvp
lowerCAmelCase__      :   List[Any]      	=			{
    "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__      :   List[Any]      	=			{
    "RUCAIBox/mvp": 10_24,
}


@lru_cache()
def 						__UpperCamelCase						(			):
		__UpperCAmelCase	:							List[Any]     =     (
		    list(range(ord("!"  ),       ord("~"  ) + 1  )  ) + list(range(ord("¡"  ),       ord("¬"  ) + 1  )  ) + list(range(ord("®"  ),       ord("ÿ"  ) + 1  )  )
		)
		__UpperCAmelCase	:							Optional[Any]     =     bs[:]
		__UpperCAmelCase	:							Dict     =     0
		for b in range(2**8  ):
				if b not in bs:
						bs.append(_UpperCAmelCase  )
						cs.append(2**8 + n  )
						n += 1
		__UpperCAmelCase	:							Any     =     [chr(_UpperCAmelCase  ) for n in cs]
		return dict(zip(_UpperCAmelCase,       _UpperCAmelCase  )  )


def 						__UpperCamelCase						(			_UpperCAmelCase  ):
		__UpperCAmelCase	:							Any     =     set()
		__UpperCAmelCase	:							Tuple     =     word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)  )
				__UpperCAmelCase	:							Any     =     char
		return pairs






class      SCREAMING_SNAKE_CASE__      (   __lowerCAmelCase		):







					"""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       :      List[Any]		,	UpperCAmelCase_       :      Tuple		,	UpperCAmelCase_       :      str		,	UpperCAmelCase_       :      int="replace"		,	UpperCAmelCase_       :      int="<s>"		,	UpperCAmelCase_       :      Tuple="</s>"		,	UpperCAmelCase_       :      str="</s>"		,	UpperCAmelCase_       :      Optional[int]="<s>"		,	UpperCAmelCase_       :      Tuple="<unk>"		,	UpperCAmelCase_       :      List[Any]="<pad>"		,	UpperCAmelCase_       :      int="<mask>"		,	UpperCAmelCase_       :      Dict=False		,	**UpperCAmelCase_       :      Any		,	):







							"""simple docstring"""
							__UpperCAmelCase	:							Dict     =     AddedToken(lowerCamelCase__		,	lstrip=lowerCamelCase__		,	rstrip=lowerCamelCase__		) if isinstance(lowerCamelCase__		,	lowerCamelCase__		) else bos_token
							__UpperCAmelCase	:							Union[str, Any]     =     AddedToken(lowerCamelCase__		,	lstrip=lowerCamelCase__		,	rstrip=lowerCamelCase__		) if isinstance(lowerCamelCase__		,	lowerCamelCase__		) else eos_token
							__UpperCAmelCase	:							Any     =     AddedToken(lowerCamelCase__		,	lstrip=lowerCamelCase__		,	rstrip=lowerCamelCase__		) if isinstance(lowerCamelCase__		,	lowerCamelCase__		) else sep_token
							__UpperCAmelCase	:							Dict     =     AddedToken(lowerCamelCase__		,	lstrip=lowerCamelCase__		,	rstrip=lowerCamelCase__		) if isinstance(lowerCamelCase__		,	lowerCamelCase__		) else cls_token
							__UpperCAmelCase	:							Any     =     AddedToken(lowerCamelCase__		,	lstrip=lowerCamelCase__		,	rstrip=lowerCamelCase__		) if isinstance(lowerCamelCase__		,	lowerCamelCase__		) else unk_token
							__UpperCAmelCase	:							str     =     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
							__UpperCAmelCase	:							List[str]     =     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:
									__UpperCAmelCase	:							Dict     =     json.load(lowerCamelCase__		)
							__UpperCAmelCase	:							List[str]     =     {v: k for k, v in self.encoder.items()}
							__UpperCAmelCase	:							Dict     =     errors  # how to handle errors in decoding
							__UpperCAmelCase	:							Tuple     =     bytes_to_unicode()
							__UpperCAmelCase	:							Tuple     =     {v: k for k, v in self.byte_encoder.items()}
							with open(lowerCamelCase__		,	encoding="utf-8"		) as merges_handle:
									__UpperCAmelCase	:							Tuple     =     merges_handle.read().split("\n"		)[1:-1]
							__UpperCAmelCase	:							Optional[int]     =     [tuple(merge.split()		) for merge in bpe_merges]
							__UpperCAmelCase	:							Tuple     =     dict(zip(lowerCamelCase__		,	range(len(lowerCamelCase__		)		)		)		)
							__UpperCAmelCase	:							Optional[Any]     =     {}
							__UpperCAmelCase	:							List[Any]     =     add_prefix_space

							# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
							__UpperCAmelCase	:							List[Any]     =     re.compile(R"\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"		)
					@property
					def 		lowerCamelCase_   (   self       :      Optional[int]		):







							"""simple docstring"""
							return len(self.encoder		)
					def 		lowerCamelCase_   (   self       :      Optional[Any]		):







							"""simple docstring"""
							return dict(self.encoder		,	**self.added_tokens_encoder		)
					def 		lowerCamelCase_   (   self       :      List[Any]		,	UpperCAmelCase_       :      str		):







							"""simple docstring"""






							if token in self.cache:
									return self.cache[token]
							__UpperCAmelCase	:							Any     =     tuple(lowerCamelCase__		)
							__UpperCAmelCase	:							Dict     =     get_pairs(lowerCamelCase__		)

							if not pairs:
									return token

							while True:
									__UpperCAmelCase	:							int     =     min(lowerCamelCase__		,	key=lambda UpperCAmelCase_		: self.bpe_ranks.get(lowerCamelCase__		,	float("inf"		)		)		)
									if bigram not in self.bpe_ranks:
											break
									__UpperCAmelCase	:							Any     =     bigram
									__UpperCAmelCase	:							Union[str, Any]     =     []
									__UpperCAmelCase	:							Dict     =     0
									while i < len(lowerCamelCase__		):
											try:
													__UpperCAmelCase	:							Tuple     =     word.index(lowerCamelCase__		,	lowerCamelCase__		)
											except ValueError:
													new_word.extend(word[i:]		)
													break
											else:
													new_word.extend(word[i:j]		)
													__UpperCAmelCase	:							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
									__UpperCAmelCase	:							str     =     tuple(lowerCamelCase__		)
									__UpperCAmelCase	:							str     =     new_word
									if len(lowerCamelCase__		) == 1:
											break
									else:
											__UpperCAmelCase	:							Optional[Any]     =     get_pairs(lowerCamelCase__		)
							__UpperCAmelCase	:							Optional[Any]     =     ''' '''.join(lowerCamelCase__		)
							__UpperCAmelCase	:							Optional[Any]     =     word
							return word
					def 		lowerCamelCase_   (   self       :      Any		,	UpperCAmelCase_       :      Union[str, Any]		):







							"""simple docstring"""
							__UpperCAmelCase	:							Any     =     []
							for token in re.findall(self.pat		,	lowerCamelCase__		):
									__UpperCAmelCase	:							Optional[int]     =     ''''''.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 		lowerCamelCase_   (   self       :      Tuple		,	UpperCAmelCase_       :      List[Any]		):







							"""simple docstring"""
							return self.encoder.get(lowerCamelCase__		,	self.encoder.get(self.unk_token		)		)
					def 		lowerCamelCase_   (   self       :      str		,	UpperCAmelCase_       :      int		):







							"""simple docstring"""
							return self.decoder.get(lowerCamelCase__		)
					def 		lowerCamelCase_   (   self       :      Optional[int]		,	UpperCAmelCase_       :      Optional[int]		):







							"""simple docstring"""
							__UpperCAmelCase	:							List[str]     =     ''''''.join(lowerCamelCase__		)
							__UpperCAmelCase	:							str     =     bytearray([self.byte_decoder[c] for c in text]		).decode("utf-8"		,	errors=self.errors		)
							return text
					def 		lowerCamelCase_   (   self       :      int		,	UpperCAmelCase_       :      str		,	UpperCAmelCase_       :      Optional[str] = None		):







							"""simple docstring"""






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

							__UpperCAmelCase	:							str     =     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 UpperCAmelCase_		: 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!"		)
													__UpperCAmelCase	:							str     =     token_index
											writer.write(" ".join(lowerCamelCase__		) + "\n"		)
											index += 1

							return vocab_file, merge_file
					def 		lowerCamelCase_   (   self       :      Optional[int]		,	UpperCAmelCase_       :      List[int]		,	UpperCAmelCase_       :      Optional[List[int]] = None		):







							"""simple docstring"""






							if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							__UpperCAmelCase	:							Any     =     [self.cls_token_id]
							__UpperCAmelCase	:							int     =     [self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep
					def 		lowerCamelCase_   (   self       :      Any		,	UpperCAmelCase_       :      List[int]		,	UpperCAmelCase_       :      Optional[List[int]] = None		,	UpperCAmelCase_       :      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 		lowerCamelCase_   (   self       :      str		,	UpperCAmelCase_       :      List[int]		,	UpperCAmelCase_       :      Optional[List[int]] = None		):







							"""simple docstring"""
							__UpperCAmelCase	:							str     =     [self.sep_token_id]
							__UpperCAmelCase	:							str     =     [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 		lowerCamelCase_   (   self       :      Optional[Any]		,	UpperCAmelCase_       :      Tuple		,	UpperCAmelCase_       :      Tuple=False		,	**UpperCAmelCase_       :      Optional[Any]		):







							"""simple docstring"""
							__UpperCAmelCase	:							Optional[Any]     =     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()):
									__UpperCAmelCase	:							int     =     ''' ''' + text
							return (text, kwargs)








from typing import TYPE_CHECKING

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


__UpperCamelCase							:							List[Any]    							=					{
    "configuration_mpnet": ["MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "MPNetConfig"],
    "tokenization_mpnet": ["MPNetTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase							:							Union[str, Any]    							=					["MPNetTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase							:							Union[str, Any]    							=					[
           "MPNET_PRETRAINED_MODEL_ARCHIVE_LIST",
           "MPNetForMaskedLM",
           "MPNetForMultipleChoice",
           "MPNetForQuestionAnswering",
           "MPNetForSequenceClassification",
           "MPNetForTokenClassification",
           "MPNetLayer",
           "MPNetModel",
           "MPNetPreTrainedModel",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase							:							List[Any]    							=					[
           "TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFMPNetEmbeddings",
           "TFMPNetForMaskedLM",
           "TFMPNetForMultipleChoice",
           "TFMPNetForQuestionAnswering",
           "TFMPNetForSequenceClassification",
           "TFMPNetForTokenClassification",
           "TFMPNetMainLayer",
           "TFMPNetModel",
           "TFMPNetPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
       from .tokenization_mpnet import MPNetTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_mpnet_fast import MPNetTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mpnet import (
                  MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MPNetForMaskedLM,
                  MPNetForMultipleChoice,
                  MPNetForQuestionAnswering,
                  MPNetForSequenceClassification,
                  MPNetForTokenClassification,
                  MPNetLayer,
                  MPNetModel,
                  MPNetPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_mpnet import (
                  TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFMPNetEmbeddings,
                  TFMPNetForMaskedLM,
                  TFMPNetForMultipleChoice,
                  TFMPNetForQuestionAnswering,
                  TFMPNetForSequenceClassification,
                  TFMPNetForTokenClassification,
                  TFMPNetMainLayer,
                  TFMPNetModel,
                  TFMPNetPreTrainedModel,
              )

else:
       import sys

       __UpperCamelCase							:							Tuple    							=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


