




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


lowercase__      :			Tuple           =					logging.get_logger(__name__)

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

lowercase__      :			Tuple           =					{
    "vocab_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/vocab.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/vocab.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/vocab.json",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/merges.txt",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/merges.txt",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/merges.txt",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt"
        ),
    },
}

lowercase__      :			Dict           =					{
    "roberta-base": 512,
    "roberta-large": 512,
    "roberta-large-mnli": 512,
    "distilroberta-base": 512,
    "roberta-base-openai-detector": 512,
    "roberta-large-openai-detector": 512,
}

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

def 					SCREAMING_SNAKE_CASE							(   __UpperCamelCase)			->     Tuple:
     a      =      set()
     a      =      word[0]
     for char in word[1:]:
          pairs.add((prev_char, char))
          a      =      char
     return pairs





class 			a__       (					UpperCamelCase__      ):
     a		:			Any							=	VOCAB_FILES_NAMES
     a		:			str							=	PRETRAINED_VOCAB_FILES_MAP
     a		:			Tuple							=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     a		:			List[str]							=	["""input_ids""", """attention_mask"""]







     def __init__(	self  ,		A  ,		A  ,		A="replace"  ,		A="<s>"  ,		A="</s>"  ,		A="</s>"  ,		A="<s>"  ,		A="<unk>"  ,		A="<pad>"  ,		A="<mask>"  ,		A=False  ,		**A  ,		)  ->    int:



          '''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 sep_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 unk_token
          a      =      AddedToken(A  ,		lstrip=A  ,		rstrip=A ) if isinstance(A  ,		A ) else pad_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__(
              errors=A  ,		bos_token=A  ,		eos_token=A  ,		unk_token=A  ,		sep_token=A  ,		cls_token=A  ,		pad_token=A  ,		mask_token=A  ,		add_prefix_space=A  ,		**A  ,		)

          with open(A  ,		encoding="utf-8" ) as vocab_handle:
               a      =      json.load(A )
          a      =      {v: k for k, v in self.encoder.items()}
          a      =      errors  # how to handle errors in decoding
          a      =      bytes_to_unicode()
          a      =      {v: k for k, v in self.byte_encoder.items()}
          with open(A  ,		encoding="utf-8" ) as merges_handle:
               a      =      merges_handle.read().split("\n" )[1:-1]
          a      =      [tuple(merge.split() ) for merge in bpe_merges]
          a      =      dict(zip(A  ,		range(len(A ) ) ) )
          a      =      {}
          a      =      add_prefix_space

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          a      =      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 )  ->    Tuple:



          '''simple docstring'''



          return len(self.encoder )







     def 			lowerCAmelCase_				(	self )  ->    List[Any]:



          '''simple docstring'''



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







     def 			lowerCAmelCase_				(	self  ,		A )  ->    List[Any]:



          '''simple docstring'''



          if token in self.cache:
               return self.cache[token]
          a      =      tuple(A )
          a      =      get_pairs(A )

          if not pairs:
               return token

          while True:
               a      =      min(A  ,		key=lambda A : self.bpe_ranks.get(A  ,		float("inf" ) ) )
               if bigram not in self.bpe_ranks:
                    break
               a  ,      a      =      bigram
               a      =      []
               a      =      0
               while i < len(A ):
                    try:
                         a      =      word.index(A  ,		A )
                    except ValueError:
                         new_word.extend(word[i:] )
                         break
                    else:
                         new_word.extend(word[i:j] )
                         a      =      j

                    if word[i] == first and i < len(A ) - 1 and word[i + 1] == second:
                         new_word.append(first + second )
                         i += 2
                    else:
                         new_word.append(word[i] )
                         i += 1
               a      =      tuple(A )
               a      =      new_word
               if len(A ) == 1:
                    break
               else:
                    a      =      get_pairs(A )
          a      =      " ".join(A )
          a      =      word
          return word







     def 			lowerCAmelCase_				(	self  ,		A )  ->    Optional[int]:



          '''simple docstring'''



          a      =      []
          for token in re.findall(self.pat  ,		A ):
               a      =      "".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(A ).split(" " ) )
          return bpe_tokens







     def 			lowerCAmelCase_				(	self  ,		A )  ->    Any:



          '''simple docstring'''



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







     def 			lowerCAmelCase_				(	self  ,		A )  ->    Union[str, Any]:



          '''simple docstring'''



          return self.decoder.get(A )







     def 			lowerCAmelCase_				(	self  ,		A )  ->    List[Any]:



          '''simple docstring'''



          a      =      "".join(A )
          a      =      bytearray([self.byte_decoder[c] for c in text] ).decode("utf-8"  ,		errors=self.errors )
          return text







     def 			lowerCAmelCase_				(	self  ,		A  ,		A = None )  ->    Tuple[str]:



          '''simple docstring'''



          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"] )
          a      =      os.path.join(
              A  ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"] )

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

          a      =      0
          with open(A  ,		"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 A : 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!" )
                         a      =      token_index
                    writer.write(" ".join(A ) + "\n" )
                    index += 1

          return vocab_file, merge_file







     def 			lowerCAmelCase_				(	self  ,		A  ,		A = None )  ->    List[int]:



          '''simple docstring'''



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







     def 			lowerCAmelCase_				(	self  ,		A  ,		A = None  ,		A = False )  ->    List[int]:



          '''simple docstring'''



          if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=A  ,		token_ids_a=A  ,		already_has_special_tokens=A )

          if token_ids_a is None:
               return [1] + ([0] * len(A )) + [1]
          return [1] + ([0] * len(A )) + [1, 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 + sep + token_ids_a + sep ) * [0]







     def 			lowerCAmelCase_				(	self  ,		A  ,		A=False  ,		**A )  ->    Any:



          '''simple docstring'''



          a      =      kwargs.pop("add_prefix_space"  ,		self.add_prefix_space )
          if (is_split_into_words or add_prefix_space) and (len(A ) > 0 and not text[0].isspace()):
               a      =      " " + text
          return (text, kwargs)







import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 			a__       (					UpperCamelCase__   ,					unittest.TestCase      ):
     a		:			Dict							=	MPNetTokenizer
     a		:			Dict							=	MPNetTokenizerFast
     a		:			Optional[int]							=	True
     a		:			Any							=	True







     def 			lowerCAmelCase_				(	self )  ->    Any:



          '''simple docstring'''



          super().setUp()

          a      =      [
              "[UNK]",
              "[CLS]",
              "[SEP]",
              "[PAD]",
              "[MASK]",
              "want",
              "##want",
              "##ed",
              "wa",
              "un",
              "runn",
              "##ing",
              ",",
              "low",
              "lowest",
          ]
          a      =      os.path.join(self.tmpdirname  ,		VOCAB_FILES_NAMES["vocab_file"] )
          with open(self.vocab_file  ,		"w"  ,		encoding="utf-8" ) as vocab_writer:
               vocab_writer.write("".join([x + "\n" for x in vocab_tokens] ) )







     def 			lowerCAmelCase_				(	self  ,		A )  ->    Any:



          '''simple docstring'''



          a      =      "UNwant\u00E9d,running"
          a      =      "unwanted, running"
          return input_text, output_text







     def 			lowerCAmelCase_				(	self )  ->    List[Any]:



          '''simple docstring'''



          a      =      self.tokenizer_class(self.vocab_file )

          a      =      tokenizer.tokenize("UNwant\u00E9d,running" )
          self.assertListEqual(A  ,		["un", "##want", "##ed", ",", "runn", "##ing"] )
          self.assertListEqual(tokenizer.convert_tokens_to_ids(A )  ,		[9, 6, 7, 12, 10, 11] )







     @slow
     def 			lowerCAmelCase_				(	self )  ->    Dict:



          '''simple docstring'''



          a      =      self.tokenizer_class.from_pretrained("microsoft/mpnet-base" )

          a      =      tokenizer.encode("sequence builders"  ,		add_special_tokens=A )
          a      =      tokenizer.encode("multi-sequence build"  ,		add_special_tokens=A )

          a      =      tokenizer.build_inputs_with_special_tokens(A )
          a      =      tokenizer.build_inputs_with_special_tokens(A  ,		A )

          assert encoded_sentence == [0] + text + [2]
          assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]

