
'''simple docstring'''
import json
import os
from typing import List, Optional, Tuple

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


A__ :		Optional[Any]					=logging.get_logger(__name__)

A__ :		str					={
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

A__ :		Dict					={
    '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__ :		Dict					={
    'microsoft/biogpt': 1_024,
}







def 							A_  (    __SCREAMING_SNAKE_CASE    :	Union[str, Any]			)					->							List[Any]:





  """simple docstring"""

  __A		:  Optional[Any]       				=		set()
  __A		:  Tuple       				=		word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)			)
    __A		:  Dict       				=		char
  return pairs







class 			__A					(			A__      ):
 lowerCamelCase												=VOCAB_FILES_NAMES
 lowerCamelCase												=PRETRAINED_VOCAB_FILES_MAP
 lowerCamelCase												=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowerCamelCase												=['''input_ids''', '''attention_mask''']
 def __init__( self      :     List[Any]					, lowerCamelCase      :     Union[str, Any]					, lowerCamelCase      :     Any					, lowerCamelCase      :     Dict="<unk>"					, lowerCamelCase      :     Any="<s>"					, lowerCamelCase      :     Tuple="</s>"					, lowerCamelCase      :     List[Any]="</s>"					, lowerCamelCase      :     Optional[int]="<pad>"					, **lowerCamelCase      :     Tuple					, ):



   """simple docstring"""





   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."""							)

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



   """simple docstring"""





   return len(self.encoder							)
 def 		lowercase_( self      :     Optional[Any]							):



   """simple docstring"""





   return dict(self.encoder					, **self.added_tokens_encoder							)
 def 		lowercase_( self      :     Dict					, lowerCamelCase      :     Tuple					, lowerCamelCase      :     List[Any]							):



   """simple docstring"""





   if lang not in self.cache_moses_tokenizer:
     __A		:  Dict       				=		self.sm.MosesTokenizer(lang=_lowerCAmelCase							)
     __A		:  List[str]       				=		moses_tokenizer
   return self.cache_moses_tokenizer[lang].tokenize(
       _lowerCAmelCase					, aggressive_dash_splits=_lowerCAmelCase					, return_str=_lowerCAmelCase					, escape=_lowerCAmelCase							)
 def 		lowercase_( self      :     str					, lowerCamelCase      :     Dict					, lowerCamelCase      :     str							):



   """simple docstring"""





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



   """simple docstring"""





   __A		:  str       				=		tuple(token[:-1]							) + (token[-1] + """</w>""",)
   if token in self.cache:
     return self.cache[token]
   __A		:  Any       				=		get_pairs(_lowerCAmelCase							)

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

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



   """simple docstring"""





   if bypass_tokenizer:
     __A		:  Dict       				=		text.split()
   else:
     __A		:  List[Any]       				=		self.moses_tokenize(_lowerCAmelCase					, self.lang							)

   __A		:  Optional[int]       				=		[]
   for token in text:
     if token:
       split_tokens.extend(list(self.bpe(_lowerCAmelCase							).split(""" """							)							)							)

   return split_tokens
 def 		lowercase_( self      :     List[str]					, lowerCamelCase      :     int							):



   """simple docstring"""





   return self.encoder.get(_lowerCAmelCase					, self.encoder.get(self.unk_token							)							)
 def 		lowercase_( self      :     Dict					, lowerCamelCase      :     Tuple							):



   """simple docstring"""





   return self.decoder.get(_lowerCAmelCase					, self.unk_token							)
 def 		lowercase_( self      :     int					, lowerCamelCase      :     Dict							):



   """simple docstring"""





   __A		:  Union[str, Any]       				=		[t.replace(""" """					, """"""							).replace("""</w>"""					, """ """							) for t in tokens]
   __A		:  Union[str, Any]       				=		"""""".join(_lowerCAmelCase							).split()
   # detokenize
   __A		:  List[str]       				=		self.moses_detokenize(_lowerCAmelCase					, self.lang							)
   return text
 def 		lowercase_( self      :     str					, lowerCamelCase      :     List[int]					, lowerCamelCase      :     Optional[List[int]] = None							):



   """simple docstring"""





   if token_ids_a is None:
     return [self.sep_token_id] + token_ids_a
   __A		:  List[Any]       				=		[self.sep_token_id]
   return sep + token_ids_a + sep + token_ids_a
 def 		lowercase_( self      :     Optional[Any]					, lowerCamelCase      :     List[int]					, lowerCamelCase      :     Optional[List[int]] = None					, lowerCamelCase      :     bool = False							):



   """simple docstring"""





   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 		lowercase_( self      :     List[Any]					, lowerCamelCase      :     List[int]					, lowerCamelCase      :     Optional[List[int]] = None							):



   """simple docstring"""





   __A		:  Union[str, 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 		lowercase_( self      :     Optional[int]					, lowerCamelCase      :     str					, lowerCamelCase      :     Optional[str] = None							):



   """simple docstring"""





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

   __A		:  List[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!"""							)
         __A		:  List[str]       				=		token_index
       writer.write(""" """.join(_lowerCAmelCase							) + """\n"""							)
       index += 1

   return vocab_file, merge_file
 def __getstate__( self      :     Optional[Any]							):



   """simple docstring"""





   __A		:  Optional[int]       				=		self.__dict__.copy()
   __A		:  Optional[int]       				=		None
   return state






 def __setstate__( self      :     Optional[Any]					, lowerCamelCase      :     Optional[int]							):



   """simple docstring"""





   __A		:  Dict       				=		d

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

   __A		:  List[Any]       				=		sacremoses










'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowerCamelCase					:						Dict					     =							{
    'configuration_donut_swin': ['DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DonutSwinConfig'],
    'processing_donut': ['DonutProcessor'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						List[str]					     =							[
				    'DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'DonutSwinModel',
				    'DonutSwinPreTrainedModel',
				]

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						Any					     =							['DonutFeatureExtractor']
				_lowerCamelCase					:						Union[str, Any]					     =							['DonutImageProcessor']


if TYPE_CHECKING:
				from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
				from .processing_donut import DonutProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_donut_swin import (
								    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DonutSwinModel,
								    DonutSwinPreTrainedModel,
								)

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_donut import DonutFeatureExtractor
								from .image_processing_donut import DonutImageProcessor

else:
				import sys

				_lowerCamelCase					:						Optional[int]					     =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

