






'''simple docstring'''



import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase_					(    __A				,       unittest.TestCase				):




      """simple docstring"""




      UpperCamelCase_								=			BioGptTokenizer
      UpperCamelCase_								=			False






      def 				A__      ( self			:		Optional[int]		)  ->  Optional[int]:


       '''simple docstring'''

       super().setUp()

       # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
       lowercase					:   Tuple				  =[
           '''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>''',
           '''<unk>''',
       ]
       lowercase					:   List[Any]				  =dict(zip(UpperCAmelCase     ,      range(len(UpperCAmelCase		)		)		)		)
       lowercase					:   int				  =['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

       lowercase					:   Union[str, Any]				  =os.path.join(self.tmpdirname     ,      VOCAB_FILES_NAMES['''vocab_file''']		)
       lowercase					:   Tuple				  =os.path.join(self.tmpdirname     ,      VOCAB_FILES_NAMES['''merges_file''']		)
       with open(self.vocab_file     ,      '''w'''		) as fp:
        fp.write(json.dumps(UpperCAmelCase		)		)
       with open(self.merges_file     ,      '''w'''		) as fp:
        fp.write('''\n'''.join(UpperCAmelCase		)		)






      def 				A__      ( self			:		str     ,      UpperCAmelCase			:		Tuple		)  ->  Tuple:


       '''simple docstring'''

       lowercase					:   Dict				  ='''lower newer'''
       lowercase					:   Optional[int]				  ='''lower newer'''
       return input_text, output_text






      def 				A__      ( self			:		str		)  ->  List[str]:


       '''simple docstring'''

       lowercase					:   Any				  =BioGptTokenizer(self.vocab_file     ,      self.merges_file		)

       lowercase					:   str				  ='''lower'''
       lowercase					:   str				  =['''low''', '''er</w>''']
       lowercase					:   List[str]				  =tokenizer.tokenize(UpperCAmelCase		)
       self.assertListEqual(UpperCAmelCase     ,      UpperCAmelCase		)

       lowercase					:   Optional[Any]				  =tokens + ['''<unk>''']
       lowercase					:   Dict				  =[14, 15, 20]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase		)     ,      UpperCAmelCase		)






      @slow
      def 				A__      ( self			:		Tuple		)  ->  List[Any]:


       '''simple docstring'''

       lowercase					:   List[str]				  =BioGptTokenizer.from_pretrained('''microsoft/biogpt'''		)

       lowercase					:   int				  =tokenizer.encode('''sequence builders'''     ,      add_special_tokens=UpperCAmelCase		)
       lowercase					:   List[Any]				  =tokenizer.encode('''multi-sequence build'''     ,      add_special_tokens=UpperCAmelCase		)

       lowercase					:   str				  =tokenizer.build_inputs_with_special_tokens(UpperCAmelCase		)
       lowercase					:   List[str]				  =tokenizer.build_inputs_with_special_tokens(UpperCAmelCase     ,      UpperCAmelCase		)

       self.assertTrue(encoded_sentence == [2] + text		)
       self.assertTrue(encoded_pair == [2] + text + [2] + text_a		)











'''simple docstring'''



from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


SCREAMING_SNAKE_CASE						=	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						=	{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

SCREAMING_SNAKE_CASE						=	{
    'vocab_file': {
        'allegro/herbert-base-cased': 'https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json'
    },
    'merges_file': {
        'allegro/herbert-base-cased': 'https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt'
    },
}

SCREAMING_SNAKE_CASE						=	{'allegro/herbert-base-cased': 514}
SCREAMING_SNAKE_CASE						=	{}
class UpperCAmelCase_					(    __A				):




      """simple docstring"""




      UpperCamelCase_								=			VOCAB_FILES_NAMES
      UpperCamelCase_								=			PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase_								=			PRETRAINED_INIT_CONFIGURATION
      UpperCamelCase_								=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase_								=			HerbertTokenizer






      def __init__( self			:		Dict     ,      UpperCAmelCase			:		Optional[Any]=None     ,      UpperCAmelCase			:		Optional[int]=None     ,      UpperCAmelCase			:		Any=None     ,      UpperCAmelCase			:		Tuple="<s>"     ,      UpperCAmelCase			:		List[Any]="<unk>"     ,      UpperCAmelCase			:		str="<pad>"     ,      UpperCAmelCase			:		Optional[Any]="<mask>"     ,      UpperCAmelCase			:		List[str]="</s>"     ,      **UpperCAmelCase			:		List[str]     ,      )  ->  Dict:


       '''simple docstring'''

       super().__init__(
           UpperCAmelCase     ,      UpperCAmelCase     ,      tokenizer_file=UpperCAmelCase     ,      cls_token=UpperCAmelCase     ,      unk_token=UpperCAmelCase     ,      pad_token=UpperCAmelCase     ,      mask_token=UpperCAmelCase     ,      sep_token=UpperCAmelCase     ,      **UpperCAmelCase     ,      )






      def 				A__      ( self			:		int     ,      UpperCAmelCase			:		List[int]     ,      UpperCAmelCase			:		Optional[List[int]] = None		)  ->  List[int]:


       '''simple docstring'''

       lowercase					:   List[Any]				  =[self.cls_token_id]
       lowercase					:   Any				  =[self.sep_token_id]
       if token_ids_a is None:
        return cls + token_ids_a + sep

       return cls + token_ids_a + sep + token_ids_a + sep






      def 				A__      ( self			:		Any     ,      UpperCAmelCase			:		List[int]     ,      UpperCAmelCase			:		Optional[List[int]] = None     ,      UpperCAmelCase			:		bool = False		)  ->  List[int]:


       '''simple docstring'''

       if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=UpperCAmelCase     ,      token_ids_a=UpperCAmelCase     ,      already_has_special_tokens=UpperCAmelCase		)

       if token_ids_a is None:
        return [1] + ([0] * len(UpperCAmelCase		)) + [1]
       return [1] + ([0] * len(UpperCAmelCase		)) + [1] + ([0] * len(UpperCAmelCase		)) + [1]






      def 				A__      ( self			:		Optional[int]     ,      UpperCAmelCase			:		List[int]     ,      UpperCAmelCase			:		Optional[List[int]] = None		)  ->  List[int]:


       '''simple docstring'''

       lowercase					:   Optional[Any]				  =[self.sep_token_id]
       lowercase					:   Dict				  =[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		) * [0] + len(token_ids_a + sep		) * [1]






      def 				A__      ( self			:		Union[str, Any]     ,      UpperCAmelCase			:		str     ,      UpperCAmelCase			:		Optional[str] = None		)  ->  Tuple[str]:


       '''simple docstring'''

       lowercase					:   List[Any]				  =self._tokenizer.model.save(UpperCAmelCase     ,      name=UpperCAmelCase		)
       return tuple(UpperCAmelCase		)



