

"""simple docstring"""



import json
import os
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

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


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation

SCREAMING_SNAKE_CASE_       :						str					=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_       :						Dict					=    {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

SCREAMING_SNAKE_CASE_       :						int					=    {
    'vocab_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'
        ),
    },
}

SCREAMING_SNAKE_CASE_       :						List[Any]					=    {
    'microsoft/deberta-base': 5_1_2,
    'microsoft/deberta-large': 5_1_2,
    'microsoft/deberta-xlarge': 5_1_2,
    'microsoft/deberta-base-mnli': 5_1_2,
    'microsoft/deberta-large-mnli': 5_1_2,
    'microsoft/deberta-xlarge-mnli': 5_1_2,
}

SCREAMING_SNAKE_CASE_       :						Dict					=    {
    'microsoft/deberta-base': {'do_lower_case': False},
    'microsoft/deberta-large': {'do_lower_case': False},
}





def 			_snake_case  (     ):
     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 			_snake_case  (     UpperCAmelCase_	:       str      ):
     A__				      =	set()
     A__				      =	word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)      )
          A__				      =	char
     return pairs



class        a    (							_lowerCamelCase					):



    """simple docstring"""



    UpperCAmelCase    			=       VOCAB_FILES_NAMES
    UpperCAmelCase    			=       PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase    			=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase    			=       ["input_ids", "attention_mask", "token_type_ids"]

    def __init__(  self:			Optional[Any]     ,    UpperCamelCase:			Dict     ,    UpperCamelCase:			Optional[Any]     ,    UpperCamelCase:			Tuple="replace"     ,    UpperCamelCase:			Any="[CLS]"     ,    UpperCamelCase:			Any="[SEP]"     ,    UpperCamelCase:			Optional[Any]="[SEP]"     ,    UpperCamelCase:			List[str]="[CLS]"     ,    UpperCamelCase:			Union[str, Any]="[UNK]"     ,    UpperCamelCase:			Optional[Any]="[PAD]"     ,    UpperCamelCase:			str="[MASK]"     ,    UpperCamelCase:			Tuple=False     ,    UpperCamelCase:			List[str]=False     ,    **UpperCamelCase:			Any     ,    ):






         """simple docstring"""


         A__				      =	AddedToken(UpperCamelCase     ,    lstrip=UpperCamelCase     ,    rstrip=UpperCamelCase							) if isinstance(UpperCamelCase     ,    UpperCamelCase							) else bos_token
         A__				      =	AddedToken(UpperCamelCase     ,    lstrip=UpperCamelCase     ,    rstrip=UpperCamelCase							) if isinstance(UpperCamelCase     ,    UpperCamelCase							) else eos_token
         A__				      =	AddedToken(UpperCamelCase     ,    lstrip=UpperCamelCase     ,    rstrip=UpperCamelCase							) if isinstance(UpperCamelCase     ,    UpperCamelCase							) else sep_token
         A__				      =	AddedToken(UpperCamelCase     ,    lstrip=UpperCamelCase     ,    rstrip=UpperCamelCase							) if isinstance(UpperCamelCase     ,    UpperCamelCase							) else cls_token
         A__				      =	AddedToken(UpperCamelCase     ,    lstrip=UpperCamelCase     ,    rstrip=UpperCamelCase							) if isinstance(UpperCamelCase     ,    UpperCamelCase							) else unk_token
         A__				      =	AddedToken(UpperCamelCase     ,    lstrip=UpperCamelCase     ,    rstrip=UpperCamelCase							) if isinstance(UpperCamelCase     ,    UpperCamelCase							) else pad_token

         # Mask token behave like a normal word, i.e. include the space before it
         A__				      =	AddedToken(UpperCamelCase     ,    lstrip=UpperCamelCase     ,    rstrip=UpperCamelCase							) if isinstance(UpperCamelCase     ,    UpperCamelCase							) else mask_token

         super().__init__(
             errors=UpperCamelCase     ,    bos_token=UpperCamelCase     ,    eos_token=UpperCamelCase     ,    unk_token=UpperCamelCase     ,    sep_token=UpperCamelCase     ,    cls_token=UpperCamelCase     ,    pad_token=UpperCamelCase     ,    mask_token=UpperCamelCase     ,    add_prefix_space=UpperCamelCase     ,    add_bos_token=UpperCamelCase     ,    **UpperCamelCase     ,    )
         A__				      =	add_bos_token

         with open(UpperCamelCase     ,    encoding="""utf-8"""							) as vocab_handle:
              A__				      =	json.load(UpperCamelCase							)
         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(UpperCamelCase     ,    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(UpperCamelCase     ,    range(len(UpperCamelCase							)							)							)							)
         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
    # Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
    def 					UpperCamelCase						(  self:			int							):






         """simple docstring"""


         return len(self.encoder							)

    def 					UpperCamelCase						(  self:			List[Any]							):






         """simple docstring"""


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

    def 					UpperCamelCase						(  self:			List[Any]     ,    UpperCamelCase:			Tuple							):






         """simple docstring"""


         if token in self.cache:
              return self.cache[token]
         A__				      =	tuple(UpperCamelCase							)
         A__				      =	get_pairs(UpperCamelCase							)

         if not pairs:
              return token

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

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

    def 					UpperCamelCase						(  self:			List[str]     ,    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]
         A__				      =	[self.cls_token_id]
         A__				      =	[self.sep_token_id]
         return cls + token_ids_a + sep + token_ids_a + sep

    def 					UpperCamelCase						(  self:			int     ,    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=UpperCamelCase     ,    token_ids_a=UpperCamelCase     ,    already_has_special_tokens=UpperCamelCase							)

         if token_ids_a is None:
              return [1] + ([0] * len(UpperCamelCase							)) + [1]
         return [1] + ([0] * len(UpperCamelCase							)) + [1] + ([0] * len(UpperCamelCase							)) + [1]

    def 					UpperCamelCase						(  self:			Tuple     ,    UpperCamelCase:			List[int]     ,    UpperCamelCase:			Optional[List[int]] = None							):






         """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							) * [0] + len(token_ids_a + sep							) * [1]

    def 					UpperCamelCase						(  self:			int     ,    UpperCamelCase:			List[Any]							):






         """simple docstring"""


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

    def 					UpperCamelCase						(  self:			Union[str, Any]     ,    UpperCamelCase:			Optional[Any]							):






         """simple docstring"""


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

    def 					UpperCamelCase						(  self:			List[Any]     ,    UpperCamelCase:			List[str]							):






         """simple docstring"""


         return self.decoder.get(UpperCamelCase							)

    def 					UpperCamelCase						(  self:			List[Any]     ,    UpperCamelCase:			List[Any]							):






         """simple docstring"""


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

    def 					UpperCamelCase						(  self:			List[Any]     ,    UpperCamelCase:			str     ,    UpperCamelCase:			Optional[str] = None							):






         """simple docstring"""


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

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

         A__				      =	0
         with open(UpperCamelCase     ,    """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!"""							)
                        A__				      =	token_index
                   writer.write(""" """.join(UpperCamelCase							) + """\n"""							)
                   index += 1

         return vocab_file, merge_file

    def 					UpperCamelCase						(  self:			Any     ,    UpperCamelCase:			Dict     ,    UpperCamelCase:			str=False     ,    **UpperCamelCase:			List[str]							):






         """simple docstring"""


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





    def 					UpperCamelCase						(  self:			List[Any]     ,    UpperCamelCase:			"Conversation"							):






         """simple docstring"""


         A__				      =	[]
         for is_user, text in conversation.iter_texts():
              input_ids.extend(self.encode(UpperCamelCase     ,    add_special_tokens=UpperCamelCase							) + [self.eos_token_id]							)
         if len(UpperCamelCase							) > self.model_max_length:
              A__				      =	input_ids[-self.model_max_length :]
         return input_ids









"""simple docstring"""



from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers



class        a    :



    """simple docstring"""



    def __init__(  self:			List[Any]     ,    UpperCamelCase:			str							):






         """simple docstring"""


         A__				      =	vocab
         A__				      =	normalizers.BertNormalizer(
             clean_text=UpperCamelCase     ,    handle_chinese_chars=UpperCamelCase     ,    strip_accents=UpperCamelCase     ,    lowercase=UpperCamelCase     ,    )
         try:
              import rjieba
         except ImportError:
              raise ImportError(
                  """You need to install rjieba to use RoFormerTokenizer. """
                  """See https://pypi.org/project/rjieba/ for installation."""							)
         A__				      =	rjieba

    def 					UpperCamelCase						(  self:			Optional[Any]     ,    UpperCamelCase:			int     ,    UpperCamelCase:			NormalizedString							):






         """simple docstring"""


         A__				      =	[]

         # this code slice normalized_string is too slow (6s) but test_alignement_methods can pass
         for token, start, end in self.jieba.tokenize(str(UpperCamelCase							)     ,    hmm=UpperCamelCase							):
              if token in self.vocab:
                   splits.append(normalized_string[start:end]							)
              else:
                   A__				      =	self.normalizers.normalize_str(UpperCamelCase							).split()
                   for token in token_list:
                        if token:
                             A__				      =	start + len(UpperCamelCase							)
                             splits.append(normalized_string[start:end]							)
                             A__				      =	end

        # this code test_alignement_methods can't pass but fast (300ms)
        # for token in self.jieba.cut(str(normalized_string), False):
        #     if token in self.vocab:
        #         splits.append(NormalizedString(token))
        #     else:
        #         token_list = self.normalizers.normalize_str(token).split()
        #         for token in token_list:
        #             if token:
        #                 splits.append(NormalizedString(token))

         return splits





    def 					UpperCamelCase						(  self:			Tuple     ,    UpperCamelCase:			PreTokenizedString							):






         """simple docstring"""


         pretok.split(self.jieba_split							)






