

"""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


_SCREAMING_SNAKE_CASE       :  Tuple        = logging.get_logger(__name__)

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

_SCREAMING_SNAKE_CASE       :  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"""
        ),
    },
}

_SCREAMING_SNAKE_CASE       :  Tuple        = {
    """roberta-base""": 5_1_2,
    """roberta-large""": 5_1_2,
    """roberta-large-mnli""": 5_1_2,
    """distilroberta-base""": 5_1_2,
    """roberta-base-openai-detector""": 5_1_2,
    """roberta-large-openai-detector""": 5_1_2,
}



@lru_cache()
def        _lowerCAmelCase      (						):


     '''simple docstring'''






     UpperCamelCase__		:    Union[str, Any]         =(
         list(range(ord('''!'''				)      ,							ord('''~'''				) + 1				)				) + list(range(ord('''¡'''				)      ,							ord('''¬'''				) + 1				)				) + list(range(ord('''®'''				)      ,							ord('''ÿ'''				) + 1				)				)
     )
     UpperCamelCase__		:    Optional[int]         =bs[:]
     UpperCamelCase__		:    str         =0
     for b in range(2**8				):
          if b not in bs:
               bs.append(UpperCAmelCase				)
               cs.append(2**8 + n				)
               n += 1
     UpperCamelCase__		:    Union[str, Any]         =[chr(UpperCAmelCase				) for n in cs]
     return dict(zip(UpperCAmelCase      ,							UpperCAmelCase				)				)



def        _lowerCAmelCase      (						UpperCAmelCase     :							Optional[int]				):


     '''simple docstring'''






     UpperCamelCase__		:    Any         =set()
     UpperCamelCase__		:    Optional[int]         =word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)				)
          UpperCamelCase__		:    str         =char
     return pairs







class     __a   (      UpperCamelCase__    ):

   """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]						,  lowercase_     :					Tuple						,  lowercase_     :					List[str]						,  lowercase_     :					Optional[int]="replace"						,  lowercase_     :					Optional[Any]="<s>"						,  lowercase_     :					Optional[int]="</s>"						,  lowercase_     :					Any="</s>"						,  lowercase_     :					str="<s>"						,  lowercase_     :					Dict="<unk>"						,  lowercase_     :					Dict="<pad>"						,  lowercase_     :					List[Any]="<mask>"						,  lowercase_     :					Any=False						,  **lowercase_     :					Union[str, Any]						,  ):
        UpperCamelCase__		:    Tuple         =AddedToken(lowerCAmelCase__						,  lstrip=lowerCAmelCase__						,  rstrip=lowerCAmelCase__						) if isinstance(lowerCAmelCase__						,  lowerCAmelCase__						) else bos_token
        UpperCamelCase__		:    List[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__		:    int         =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__		:    Tuple         =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__		:    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:
             UpperCamelCase__		:    Optional[Any]         =json.load(lowerCAmelCase__						)
        UpperCamelCase__		:    int         ={v: k for k, v in self.encoder.items()}
        UpperCamelCase__		:    Dict         =errors  # how to handle errors in decoding
        UpperCamelCase__		:    int         =bytes_to_unicode()
        UpperCamelCase__		:    List[Any]         ={v: k for k, v in self.byte_encoder.items()}
        with open(lowerCAmelCase__						,  encoding='''utf-8'''						) as merges_handle:
             UpperCamelCase__		:    List[Any]         =merges_handle.read().split('''\n'''						)[1:-1]
        UpperCamelCase__		:    int         =[tuple(merge.split()						) for merge in bpe_merges]
        UpperCamelCase__		:    Tuple         =dict(zip(lowerCAmelCase__						,  range(len(lowerCAmelCase__						)						)						)						)
        UpperCamelCase__		:    Tuple         ={}
        UpperCamelCase__		:    Dict         =add_prefix_space

        # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
        UpperCamelCase__		:    Union[str, 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     :					Dict						):
        return len(self.encoder						)






   def    _lowerCAmelCase			(							self     :					Optional[Any]						):
        return dict(self.encoder						,  **self.added_tokens_encoder						)






   def    _lowerCAmelCase			(							self     :					List[str]						,  lowercase_     :					List[str]						):




        if token in self.cache:
             return self.cache[token]
        UpperCamelCase__		:    Tuple         =tuple(lowerCAmelCase__						)
        UpperCamelCase__		:    List[Any]         =get_pairs(lowerCAmelCase__						)

        if not pairs:
             return token

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






   def    _lowerCAmelCase			(							self     :					str						,  lowercase_     :					Any						):
        UpperCamelCase__		:    Optional[int]         =[]
        for token in re.findall(self.pat						,  lowerCAmelCase__						):
             UpperCamelCase__		:    Optional[Any]         ="".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						,  lowercase_     :					int						):
        return self.encoder.get(lowerCAmelCase__						,  self.encoder.get(self.unk_token						)						)






   def    _lowerCAmelCase			(							self     :					Optional[int]						,  lowercase_     :					Tuple						):
        return self.decoder.get(lowerCAmelCase__						)






   def    _lowerCAmelCase			(							self     :					Optional[Any]						,  lowercase_     :					Tuple						):
        UpperCamelCase__		:    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     :					str						,  lowercase_     :					int						,  lowercase_     :					Dict = None						):




        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__		:    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__		:    Optional[int]         =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 lowercase_						: 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__		:    Union[str, Any]         =token_index
                  writer.write(''' '''.join(lowerCAmelCase__						) + '''\n'''						)
                  index += 1

        return vocab_file, merge_file






   def    _lowerCAmelCase			(							self     :					Optional[int]						,  lowercase_     :					Optional[int]						,  lowercase_     :					Optional[Any] = None						):




        if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        UpperCamelCase__		:    Union[str, Any]         =[self.cls_token_id]
        UpperCamelCase__		:    List[str]         =[self.sep_token_id]
        return cls + token_ids_a + sep + sep + token_ids_a + sep






   def    _lowerCAmelCase			(							self     :					List[str]						,  lowercase_     :					Union[str, Any]						,  lowercase_     :					Optional[Any] = None						,  lowercase_     :					List[Any] = False						):




        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     :					Dict						,  lowercase_     :					int						,  lowercase_     :					Tuple = None						):
        UpperCamelCase__		:    List[Any]         =[self.sep_token_id]
        UpperCamelCase__		:    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    _lowerCAmelCase			(							self     :					List[str]						,  lowercase_     :					Dict						,  lowercase_     :					int=False						,  **lowercase_     :					int						):
        UpperCamelCase__		:    List[str]         =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__		:    List[Any]         =" " + text
        return (text, kwargs)





"""simple docstring"""





from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE       :  List[Any]        = {"""configuration_t5""": ["""T5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """T5Config""", """T5OnnxConfig"""]}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE       :  Optional[Any]        = ["""T5Tokenizer"""]

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE       :  str        = ["""T5TokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE       :  Dict        = [
				    """T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """T5EncoderModel""",
				    """T5ForConditionalGeneration""",
				    """T5Model""",
				    """T5PreTrainedModel""",
				    """load_tf_weights_in_t5""",
				    """T5ForQuestionAnswering""",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE       :  Dict        = [
				    """TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """TFT5EncoderModel""",
				    """TFT5ForConditionalGeneration""",
				    """TFT5Model""",
				    """TFT5PreTrainedModel""",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE       :  Any        = [
				    """FlaxT5EncoderModel""",
				    """FlaxT5ForConditionalGeneration""",
				    """FlaxT5Model""",
				    """FlaxT5PreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_ta import TaTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_ta_fast import TaTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_ta import (
								    T5_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TaEncoderModel,
								    TaForConditionalGeneration,
								    TaForQuestionAnswering,
								    TaModel,
								    TaPreTrainedModel,
								    load_tf_weights_in_ta,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_ta import (
								    TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFTaEncoderModel,
								    TFTaForConditionalGeneration,
								    TFTaModel,
								    TFTaPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_ta import (
								    FlaxTaEncoderModel,
								    FlaxTaForConditionalGeneration,
								    FlaxTaModel,
								    FlaxTaPreTrainedModel,
								)


else:
				import sys

				_SCREAMING_SNAKE_CASE       :  str        = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


