
"""simple docstring"""


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''': 10_24,
}






def  _snake_case			(						snake_case__				:       Dict       ):
 A  				=				set()
 A  				=				word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)       )
  A  				=				char
 return pairs







class 			lowerCAmelCase_			( _lowercase      ):



      '''simple docstring'''


      _lowerCamelCase:      Tuple =      VOCAB_FILES_NAMES
      _lowerCamelCase:      Optional[int] =      PRETRAINED_VOCAB_FILES_MAP
      _lowerCamelCase:      int =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowerCamelCase:      int =      ['''input_ids''', '''attention_mask''']


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

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


      @property
      def   _SCREAMING_SNAKE_CASE (	self       : str )       ->				Dict:
       return len(self.encoder )


      def   _SCREAMING_SNAKE_CASE (	self       : Any )       ->				List[str]:
       return dict(self.encoder					,**self.added_tokens_encoder )


      def   _SCREAMING_SNAKE_CASE (	self       : List[str]					,A_       : Optional[int]					,A_       : Dict )       ->				Optional[int]:
       if lang not in self.cache_moses_tokenizer:
        A  				=				self.sm.MosesTokenizer(lang=A_ )
        A  				=				moses_tokenizer
       return self.cache_moses_tokenizer[lang].tokenize(
           A_					,aggressive_dash_splits=A_					,return_str=A_					,escape=A_ )


      def   _SCREAMING_SNAKE_CASE (	self       : Optional[int]					,A_       : Dict					,A_       : Tuple )       ->				str:
       if lang not in self.cache_moses_detokenizer:
        A  				=				self.sm.MosesDetokenizer(lang=A_ )
        A  				=				moses_detokenizer
       return self.cache_moses_detokenizer[lang].detokenize(A_ )


      def   _SCREAMING_SNAKE_CASE (	self       : Dict					,A_       : Tuple )       ->				Optional[Any]:
       A  				=				tuple(token[:-1] ) + (token[-1] + '</w>',)
       if token in self.cache:
        return self.cache[token]
       A  				=				get_pairs(A_ )

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

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


      def   _SCREAMING_SNAKE_CASE (	self       : Dict					,A_       : str					,A_       : Tuple=False )       ->				Any:
       if bypass_tokenizer:
        A  				=				text.split()
       else:
        A  				=				self.moses_tokenize(A_					,self.lang )

       A  				=				[]
       for token in text:
        if token:
         split_tokens.extend(list(self.bpe(A_ ).split(' ' ) ) )

       return split_tokens


      def   _SCREAMING_SNAKE_CASE (	self       : Dict					,A_       : Optional[Any] )       ->				int:
       return self.encoder.get(A_					,self.encoder.get(self.unk_token ) )


      def   _SCREAMING_SNAKE_CASE (	self       : Optional[Any]					,A_       : int )       ->				Dict:
       return self.decoder.get(A_					,self.unk_token )


      def   _SCREAMING_SNAKE_CASE (	self       : Union[str, Any]					,A_       : Tuple )       ->				str:
       A  				=				[t.replace(' '					,'' ).replace('</w>'					,' ' ) for t in tokens]
       A  				=				''.join(A_ ).split()
       # detokenize
       A  				=				self.moses_detokenize(A_					,self.lang )
       return text


      def   _SCREAMING_SNAKE_CASE (	self       : Optional[Any]					,A_       : List[int]					,A_       : Optional[List[int]] = None )       ->				List[int]:
       if token_ids_a is None:
        return [self.sep_token_id] + token_ids_a
       A  				=				[self.sep_token_id]
       return sep + token_ids_a + sep + token_ids_a


      def   _SCREAMING_SNAKE_CASE (	self       : Optional[Any]					,A_       : List[int]					,A_       : Optional[List[int]] = None					,A_       : bool = False )       ->				List[int]:
       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   _SCREAMING_SNAKE_CASE (	self       : List[Any]					,A_       : List[int]					,A_       : Optional[List[int]] = None )       ->				List[int]:
       A  				=				[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   _SCREAMING_SNAKE_CASE (	self       : Optional[Any]					,A_       : str					,A_       : Optional[str] = None )       ->				Tuple[str]:
       if not os.path.isdir(A_ ):
        logger.error(F'Vocabulary path ({save_directory}) should be a directory' )
        return
       A  				=				os.path.join(
           A_					,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )
       A  				=				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' )

       A  				=				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!' )
          A  				=				token_index
         writer.write(' '.join(A_ ) + '\n' )
         index += 1

       return vocab_file, merge_file


      def __getstate__(	self       : Tuple )       ->				Tuple:
       A  				=				self.__dict__.copy()
       A  				=				None
       return state




      def __setstate__(	self       : Dict					,A_       : int )       ->				int:
       A  				=				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  				=				sacremoses

"""simple docstring"""


import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 			lowerCAmelCase_			( _lowercase						,   unittest.TestCase      ):



						'''simple docstring'''


						_lowerCamelCase:      List[str] =      HerbertTokenizer
						_lowerCamelCase:      Any =      HerbertTokenizerFast
						_lowerCamelCase:      Optional[int] =      True


						def   _SCREAMING_SNAKE_CASE (	self       : Dict )       ->				Tuple:
							super().setUp()

							# Use a simpler test file without japanese/chinese characters
							with open(F'{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'					,encoding='utf-8' ) as f_data:
								A  				=				f_data.read().replace('\n\n'					,'\n' ).strip()

							A  				=				[
							    '<s>',
							    '</s>',
							    'l',
							    'o',
							    'w',
							    'e',
							    'r',
							    's',
							    't',
							    'i',
							    'd',
							    'n',
							    'w</w>',
							    'r</w>',
							    't</w>',
							    'lo',
							    'low',
							    'er</w>',
							    'low</w>',
							    'lowest</w>',
							    'newer</w>',
							    'wider</w>',
							    ',</w>',
							    '<unk>',
							]
							A  				=				dict(zip(A_					,range(len(A_ ) ) ) )
							A  				=				['l o 123', 'lo w 1456', 'e r</w> 1789', '']

							A  				=				os.path.join(self.tmpdirname					,VOCAB_FILES_NAMES['vocab_file'] )
							A  				=				os.path.join(self.tmpdirname					,VOCAB_FILES_NAMES['merges_file'] )
							with open(self.vocab_file					,'w' ) as fp:
								fp.write(json.dumps(A_ ) )
							with open(self.merges_file					,'w' ) as fp:
								fp.write('\n'.join(A_ ) )


						def   _SCREAMING_SNAKE_CASE (	self       : Tuple					,A_       : List[str] )       ->				int:
							A  				=				'lower newer'
							A  				=				'lower newer'
							return input_text, output_text


						def   _SCREAMING_SNAKE_CASE (	self       : List[Any] )       ->				int:
							A  				=				self.tokenizer_class(vocab_file=self.vocab_file					,merges_file=self.merges_file )

							A  				=				'lower'
							A  				=				['low', 'er</w>']
							A  				=				tokenizer.tokenize(A_ )
							self.assertListEqual(A_					,A_ )

							A  				=				tokens + ['<unk>']
							A  				=				[16, 17, 23]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(A_ )					,A_ )


						def   _SCREAMING_SNAKE_CASE (	self       : Dict )       ->				Optional[int]:
							if not self.test_rust_tokenizer:
								return

							A  				=				self.get_tokenizer()
							A  				=				self.get_rust_tokenizer()

							A  				=				'lower,newer'

							A  				=				tokenizer.tokenize(A_ )
							A  				=				rust_tokenizer.tokenize(A_ )
							self.assertListEqual(A_					,A_ )

							A  				=				tokenizer.encode(A_					,add_special_tokens=A_ )
							A  				=				rust_tokenizer.encode(A_					,add_special_tokens=A_ )
							self.assertListEqual(A_					,A_ )

							A  				=				self.get_rust_tokenizer()
							A  				=				tokenizer.encode(A_ )
							A  				=				rust_tokenizer.encode(A_ )
							self.assertListEqual(A_					,A_ )




						@slow
						def   _SCREAMING_SNAKE_CASE (	self       : str )       ->				List[Any]:
							A  				=				self.tokenizer_class.from_pretrained('allegro/herbert-base-cased' )

							A  				=				tokenizer.encode('konstruowanie sekwencji'					,add_special_tokens=A_ )
							A  				=				tokenizer.encode('konstruowanie wielu sekwencji'					,add_special_tokens=A_ )

							A  				=				tokenizer.build_inputs_with_special_tokens(A_ )
							A  				=				tokenizer.build_inputs_with_special_tokens(A_					,A_ )

							assert encoded_sentence == [0] + text + [2]
							assert encoded_pair == [0] + text + [2] + text_a + [2]