




'''simple docstring'''






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

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


A_ 			=		logging.get_logger(__name__)

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

A_ 			=		{
    "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"},
}

A_ 			=		{
    "microsoft/biogpt": 1024,
}






def 		UpperCamelCase__			(		__SCREAMING_SNAKE_CASE		)						->      str:
      snake_case__					:      Optional[Any]  			=						set()
      snake_case__					:      Dict  			=						word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)		)
            snake_case__					:      Tuple  			=						char
      return pairs






class 					lowercase_			(	lowerCAmelCase_       ):
     A_       							= VOCAB_FILES_NAMES
     A_       							= PRETRAINED_VOCAB_FILES_MAP
     A_       							= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     A_       							= ["input_ids", "attention_mask"]





     def __init__(    self    :				Optional[int]    ,       __lowerCamelCase    :				Tuple    ,       __lowerCamelCase    :				List[str]    ,       __lowerCamelCase    :				Dict="<unk>"    ,       __lowerCamelCase    :				Dict="<s>"    ,       __lowerCamelCase    :				List[str]="</s>"    ,       __lowerCamelCase    :				str="</s>"    ,       __lowerCamelCase    :				Optional[Any]="<pad>"    ,       **__lowerCamelCase    :				int    ,       ):
           super().__init__(
               bos_token=__lowerCamelCase    ,       eos_token=__lowerCamelCase    ,       sep_token=__lowerCamelCase    ,       unk_token=__lowerCamelCase    ,       pad_token=__lowerCamelCase    ,       **__lowerCamelCase    ,       )

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

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





     @property
     def  _lowerCAmelCase			(    self    :				List[Any] ):
           return len(self.encoder )





     def  _lowerCAmelCase			(    self    :				int ):
           return dict(self.encoder    ,       **self.added_tokens_encoder )





     def  _lowerCAmelCase			(    self    :				List[Any]    ,       __lowerCamelCase    :				int    ,       __lowerCamelCase    :				int ):
           if lang not in self.cache_moses_tokenizer:
                 snake_case__					:      Union[str, Any]  			=						self.sm.MosesTokenizer(lang=__lowerCamelCase )
                 snake_case__					:      Tuple  			=						moses_tokenizer
           return self.cache_moses_tokenizer[lang].tokenize(
               __lowerCamelCase    ,       aggressive_dash_splits=__lowerCamelCase    ,       return_str=__lowerCamelCase    ,       escape=__lowerCamelCase )





     def  _lowerCAmelCase			(    self    :				List[str]    ,       __lowerCamelCase    :				Union[str, Any]    ,       __lowerCamelCase    :				Optional[Any] ):
           if lang not in self.cache_moses_detokenizer:
                 snake_case__					:      str  			=						self.sm.MosesDetokenizer(lang=__lowerCamelCase )
                 snake_case__					:      Optional[int]  			=						moses_detokenizer
           return self.cache_moses_detokenizer[lang].detokenize(__lowerCamelCase )





     def  _lowerCAmelCase			(    self    :				List[Any]    ,       __lowerCamelCase    :				List[Any] ):
           snake_case__					:      List[Any]  			=						tuple(token[:-1] ) + (token[-1] + '</w>',)
           if token in self.cache:
                 return self.cache[token]
           snake_case__					:      Union[str, Any]  			=						get_pairs(__lowerCamelCase )

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

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





     def  _lowerCAmelCase			(    self    :				Dict    ,       __lowerCamelCase    :				Any    ,       __lowerCamelCase    :				str=False ):
           if bypass_tokenizer:
                 snake_case__					:      List[str]  			=						text.split()
           else:
                 snake_case__					:      Optional[int]  			=						self.moses_tokenize(__lowerCamelCase    ,       self.lang )

           snake_case__					:      Optional[int]  			=						[]
           for token in text:
                 if token:
                       split_tokens.extend(list(self.bpe(__lowerCamelCase ).split(' ' ) ) )

           return split_tokens





     def  _lowerCAmelCase			(    self    :				int    ,       __lowerCamelCase    :				Optional[int] ):
           return self.encoder.get(__lowerCamelCase    ,       self.encoder.get(self.unk_token ) )





     def  _lowerCAmelCase			(    self    :				Dict    ,       __lowerCamelCase    :				List[str] ):
           return self.decoder.get(__lowerCamelCase    ,       self.unk_token )





     def  _lowerCAmelCase			(    self    :				Union[str, Any]    ,       __lowerCamelCase    :				Dict ):
           snake_case__					:      Optional[Any]  			=						[t.replace(' '    ,       '' ).replace('</w>'    ,       ' ' ) for t in tokens]
           snake_case__					:      Tuple  			=						''.join(__lowerCamelCase ).split()
           # detokenize
           snake_case__					:      List[str]  			=						self.moses_detokenize(__lowerCamelCase    ,       self.lang )
           return text





     def  _lowerCAmelCase			(    self    :				str    ,       __lowerCamelCase    :				List[int]    ,       __lowerCamelCase    :				Optional[List[int]] = None ):
           if token_ids_a is None:
                 return [self.sep_token_id] + token_ids_a
           snake_case__					:      Optional[int]  			=						[self.sep_token_id]
           return sep + token_ids_a + sep + token_ids_a





     def  _lowerCAmelCase			(    self    :				Union[str, Any]    ,       __lowerCamelCase    :				List[int]    ,       __lowerCamelCase    :				Optional[List[int]] = None    ,       __lowerCamelCase    :				bool = 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 )
           # no bos used in fairseq
           if token_ids_a is not None:
                 return [1] + ([0] * len(__lowerCamelCase )) + [1] + ([0] * len(__lowerCamelCase ))
           return [1] + ([0] * len(__lowerCamelCase ))





     def  _lowerCAmelCase			(    self    :				Dict    ,       __lowerCamelCase    :				List[int]    ,       __lowerCamelCase    :				Optional[List[int]] = None ):
           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  _lowerCAmelCase			(    self    :				Any    ,       __lowerCamelCase    :				str    ,       __lowerCamelCase    :				Optional[str] = None ):
           if not os.path.isdir(__lowerCamelCase ):
                 logger.error(F"Vocabulary path ({save_directory}) should be a directory" )
                 return
           snake_case__					:      Optional[Any]  			=						os.path.join(
               __lowerCamelCase    ,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )
           snake_case__					:      List[str]  			=						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' )

           snake_case__					:      str  			=						0
           with open(__lowerCamelCase    ,       'w'    ,       encoding='utf-8' ) as writer:
                 for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,       key=lambda __lowerCamelCase : 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!' )
                             snake_case__					:      Tuple  			=						token_index
                       writer.write(' '.join(__lowerCamelCase ) + '\n' )
                       index += 1

           return vocab_file, merge_file





     def __getstate__(    self    :				List[Any] ):
           snake_case__					:      List[Any]  			=						self.__dict__.copy()
           snake_case__					:      List[Any]  			=						None
           return state





     def __setstate__(    self    :				Optional[Any]    ,       __lowerCamelCase    :				List[str] ):
           snake_case__					:      int  			=						d

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

           snake_case__					:      Dict  			=						sacremoses






'''simple docstring'''






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


A_ 			=		{
    "configuration_ernie_m": ["ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieMConfig"],
}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A_ 			=		["ErnieMTokenizer"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A_ 			=		[
          "ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ErnieMForMultipleChoice",
          "ErnieMForQuestionAnswering",
          "ErnieMForSequenceClassification",
          "ErnieMForTokenClassification",
          "ErnieMModel",
          "ErnieMPreTrainedModel",
          "ErnieMForInformationExtraction",
      ]


if TYPE_CHECKING:
      from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_ernie_m import ErnieMTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_ernie_m import (
                ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
                ErnieMForInformationExtraction,
                ErnieMForMultipleChoice,
                ErnieMForQuestionAnswering,
                ErnieMForSequenceClassification,
                ErnieMForTokenClassification,
                ErnieMModel,
                ErnieMPreTrainedModel,
            )


else:
      import sys

      A_ 			=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
