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

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase_											=	logging.get_logger(__name__)

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

lowercase_											=	{
    """vocab_file""": {
        """microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json""",
    },
    """merges_file""": {"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt"""},
}

lowercase_											=	{
    """microsoft/biogpt""": 1_024,
}


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						set()
  __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)    )
    __SCREAMING_SNAKE_CASE     :					str			=						char
  return pairs





class   __UpperCamelCase				(    lowerCAmelCase__   ):






     """simple docstring"""







     lowerCAmelCase_     =	VOCAB_FILES_NAMES
     lowerCAmelCase_     =	PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase_     =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase_     =	['''input_ids''', '''attention_mask''']



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







       """simple docstring"""




       super().__init__(
           bos_token=_A      ,		eos_token=_A      ,		sep_token=_A      ,		unk_token=_A      ,		pad_token=_A      ,		**_A      ,		)

       try:
         import sacremoses
       except ImportError:
         raise ImportError(
             '''You need to install sacremoses to use BioGptTokenizer. '''
             '''See https://pypi.org/project/sacremoses/ for installation.'''				)

       __SCREAMING_SNAKE_CASE     :					Dict			=						'''en'''
       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						sacremoses
       # cache of sm.MosesTokenizer instance
       __SCREAMING_SNAKE_CASE     :					Tuple			=						{}
       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						{}
       with open(_A      ,		encoding='''utf-8'''				) as vocab_handle:
         __SCREAMING_SNAKE_CASE     :					Any			=						json.load(_A				)
       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						{v: k for k, v in self.encoder.items()}
       with open(_A      ,		encoding='''utf-8'''				) as merges_handle:
         __SCREAMING_SNAKE_CASE     :					List[str]			=						merges_handle.read().split('''\n'''				)[:-1]
       __SCREAMING_SNAKE_CASE     :					int			=						[tuple(merge.split()[:2]				) for merge in merges]
       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						dict(zip(_A      ,		range(len(_A				)				)				)				)
       __SCREAMING_SNAKE_CASE     :					int			=						{}



     @property
     def 				UpperCAmelCase__    (							self    :    List[Any]				):







       """simple docstring"""




       return len(self.encoder				)



     def 				UpperCAmelCase__    (							self    :    int				):







       """simple docstring"""




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



     def 				UpperCAmelCase__    (							self    :    Any      ,		_A    :    str      ,		_A    :    Dict				):







       """simple docstring"""




       if lang not in self.cache_moses_tokenizer:
         __SCREAMING_SNAKE_CASE     :					Dict			=						self.sm.MosesTokenizer(lang=_A				)
         __SCREAMING_SNAKE_CASE     :					Optional[int]			=						moses_tokenizer
       return self.cache_moses_tokenizer[lang].tokenize(
           _A      ,		aggressive_dash_splits=_A      ,		return_str=_A      ,		escape=_A				)



     def 				UpperCAmelCase__    (							self    :    List[str]      ,		_A    :    Optional[Any]      ,		_A    :    Tuple				):







       """simple docstring"""




       if lang not in self.cache_moses_detokenizer:
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						self.sm.MosesDetokenizer(lang=_A				)
         __SCREAMING_SNAKE_CASE     :					List[Any]			=						moses_detokenizer
       return self.cache_moses_detokenizer[lang].detokenize(_A				)



     def 				UpperCAmelCase__    (							self    :    int      ,		_A    :    List[Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					str			=						tuple(token[:-1]				) + (token[-1] + '''</w>''',)
       if token in self.cache:
         return self.cache[token]
       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						get_pairs(_A				)

       if not pairs:
         return token + "</w>"

       while True:
         __SCREAMING_SNAKE_CASE     :					str			=						min(_A      ,		key=lambda _A				: self.bpe_ranks.get(_A      ,		float('''inf'''				)				)				)
         if bigram not in self.bpe_ranks:
           break
         __SCREAMING_SNAKE_CASE,						__SCREAMING_SNAKE_CASE     :					List[Any]			=						bigram
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						[]
         __SCREAMING_SNAKE_CASE     :					str			=						0
         while i < len(_A				):
           try:
             __SCREAMING_SNAKE_CASE     :					List[str]			=						word.index(_A      ,		_A				)
           except ValueError:
             new_word.extend(word[i:]				)
             break
           else:
             new_word.extend(word[i:j]				)
             __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						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
         __SCREAMING_SNAKE_CASE     :					Any			=						tuple(_A				)
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						new_word
         if len(_A				) == 1:
           break
         else:
           __SCREAMING_SNAKE_CASE     :					Dict			=						get_pairs(_A				)
       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						''' '''.join(_A				)
       if word == "\n  </w>":
         __SCREAMING_SNAKE_CASE     :					Any			=						'''\n</w>'''
       __SCREAMING_SNAKE_CASE     :					str			=						word
       return word



     def 				UpperCAmelCase__    (							self    :    int      ,		_A    :    Union[str, Any]      ,		_A    :    Dict=False				):







       """simple docstring"""




       if bypass_tokenizer:
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						text.split()
       else:
         __SCREAMING_SNAKE_CASE     :					Any			=						self.moses_tokenize(_A      ,		self.lang				)

       __SCREAMING_SNAKE_CASE     :					str			=						[]
       for token in text:
         if token:
           split_tokens.extend(list(self.bpe(_A				).split(''' '''				)				)				)

       return split_tokens



     def 				UpperCAmelCase__    (							self    :    List[Any]      ,		_A    :    Optional[Any]				):







       """simple docstring"""




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



     def 				UpperCAmelCase__    (							self    :    Dict      ,		_A    :    str				):







       """simple docstring"""




       return self.decoder.get(_A      ,		self.unk_token				)



     def 				UpperCAmelCase__    (							self    :    Optional[Any]      ,		_A    :    Any				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					str			=						[t.replace(''' '''      ,		''''''				).replace('''</w>'''      ,		''' '''				) for t in tokens]
       __SCREAMING_SNAKE_CASE     :					str			=						''''''.join(_A				).split()
       # detokenize
       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						self.moses_detokenize(_A      ,		self.lang				)
       return text



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







       """simple docstring"""




       if token_ids_a is None:
         return [self.sep_token_id] + token_ids_a
       __SCREAMING_SNAKE_CASE     :					Tuple			=						[self.sep_token_id]
       return sep + token_ids_a + sep + token_ids_a



     def 				UpperCAmelCase__    (							self    :    List[str]      ,		_A    :    List[int]      ,		_A    :    Optional[List[int]] = None      ,		_A    :    bool = False				):







       """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				)
       # no bos used in fairseq
       if token_ids_a is not None:
         return [1] + ([0] * len(_A				)) + [1] + ([0] * len(_A				))
       return [1] + ([0] * len(_A				))



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







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						[self.sep_token_id]

       # no bos used in fairseq
       if token_ids_a is None:
         return len(token_ids_a + sep				) * [0]
       return len(token_ids_a + sep				) * [0] + len(token_ids_a + sep				) * [1]



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







       """simple docstring"""




       if not os.path.isdir(_A				):
         logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''				)
         return
       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						os.path.join(
           _A      ,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)
       __SCREAMING_SNAKE_CASE     :					List[str]			=						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'''				)

       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						0
       with open(_A      ,		'''w'''      ,		encoding='''utf-8'''				) as writer:
         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!'''				)
             __SCREAMING_SNAKE_CASE     :					str			=						token_index
           writer.write(''' '''.join(_A				) + '''\n'''				)
           index += 1

       return vocab_file, merge_file



     def __getstate__(							self    :    str				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						self.__dict__.copy()
       __SCREAMING_SNAKE_CASE     :					Dict			=						None
       return state




     def __setstate__(							self    :    Tuple      ,		_A    :    int				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					str			=						d

       try:
         import sacremoses
       except ImportError:
         raise ImportError(
             '''You need to install sacremoses to use XLMTokenizer. '''
             '''See https://pypi.org/project/sacremoses/ for installation.'''				)

       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						sacremoses


from typing import Optional

from ..utils.logging import get_logger
from .audio_classificiation import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModeling
from .question_answering import QuestionAnsweringExtractive
from .summarization import Summarization
from .text_classification import TextClassification


lowercase_											=	[
    """AutomaticSpeechRecognition""",
    """AudioClassification""",
    """ImageClassification""",
    """LanguageModeling""",
    """QuestionAnsweringExtractive""",
    """Summarization""",
    """TaskTemplate""",
    """TextClassification""",
]

lowercase_											=	get_logger(__name__)


lowercase_											=	{
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					str			=						task_template_dict.get('''task'''    )
  if task_name is None:
    logger.warning(F'''Couldn\'t find template for task \'{task_name}\'. Available templates: {list(snake_case    )}'''    )
    return None
  __SCREAMING_SNAKE_CASE     :					Any			=						NAMEaTEMPLATE.get(snake_case    )
  return template.from_dict(snake_case    )
