





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


lowerCAmelCase_    =				logging.get_logger(__name__)

lowerCAmelCase_    =				{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase_    =				{
    '''vocab_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

lowerCAmelCase_    =				{
    '''yjernite/retribert-base-uncased''': 5_1_2,
}


lowerCAmelCase_    =				{
    '''yjernite/retribert-base-uncased''': {'''do_lower_case''': True},
}



class 					__lowerCAmelCase       (			_a     ):
			lowerCamelCase_     :     List[Any]       			=      VOCAB_FILES_NAMES
			lowerCamelCase_     :     Optional[Any]       			=      PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase_     :     Union[str, Any]       			=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase_     :     Dict       			=      PRETRAINED_INIT_CONFIGURATION
			lowerCamelCase_     :     Optional[Any]       			=      RetriBertTokenizer
			lowerCamelCase_     :     Dict       			=      ['''input_ids''', '''attention_mask''']






			def __init__(self					,							__magic_name__=None					,							__magic_name__=None					,							__magic_name__=True					,							__magic_name__="[UNK]"					,							__magic_name__="[SEP]"					,							__magic_name__="[PAD]"					,							__magic_name__="[CLS]"					,							__magic_name__="[MASK]"					,							__magic_name__=True					,							__magic_name__=None					,							**__magic_name__					,							)     ->   Optional[Any]:


							'''simple docstring'''



							super().__init__(
							    __magic_name__					,							tokenizer_file=__magic_name__					,							do_lower_case=__magic_name__					,							unk_token=__magic_name__					,							sep_token=__magic_name__					,							pad_token=__magic_name__					,							cls_token=__magic_name__					,							mask_token=__magic_name__					,							tokenize_chinese_chars=__magic_name__					,							strip_accents=__magic_name__					,							**__magic_name__					,							)

							snake_case_						:    Union[str, Any]				=  json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
							if (
							    normalizer_state.get('''lowercase'''					,							__magic_name__    ) != do_lower_case
							    or normalizer_state.get('''strip_accents'''					,							__magic_name__    ) != strip_accents
							    or normalizer_state.get('''handle_chinese_chars'''					,							__magic_name__    ) != tokenize_chinese_chars
							):
											snake_case_						:    int				=  getattr(__magic_name__					,							normalizer_state.pop('''type'''    )    )
											snake_case_						:    Union[str, Any]				=  do_lower_case
											snake_case_						:    Union[str, Any]				=  strip_accents
											snake_case_						:    int				=  tokenize_chinese_chars
											snake_case_						:    Tuple				=  normalizer_class(**__magic_name__    )

							snake_case_						:    Dict				=  do_lower_case






			def 			lowerCamelCase  (self					,							__magic_name__					,							__magic_name__=None    )     ->   Any:


							'''simple docstring'''



							snake_case_						:    List[str]				=  [self.cls_token_id] + token_ids_a + [self.sep_token_id]

							if token_ids_a:
											output += token_ids_a + [self.sep_token_id]

							return output






			def 			lowerCamelCase  (self					,							__magic_name__					,							__magic_name__ = None    )     ->   List[int]:


							'''simple docstring'''



							snake_case_						:    Optional[int]				=  [self.sep_token_id]
							snake_case_						:    List[Any]				=  [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 			lowerCamelCase  (self					,							__magic_name__					,							__magic_name__ = None    )     ->   Tuple[str]:


							'''simple docstring'''



							snake_case_						:    Any				=  self._tokenizer.model.save(__magic_name__					,							name=__magic_name__    )
							return tuple(__magic_name__    )







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 					__lowerCAmelCase       (			_a,     unittest.TestCase     ):
			lowerCamelCase_     :     Any       			=      BioGptTokenizer
			lowerCamelCase_     :     Optional[Any]       			=      False






			def 			lowerCamelCase  (self    )     ->   List[Any]:


							'''simple docstring'''



							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							snake_case_						:    Optional[Any]				=  [
							    '''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>''',
							]
							snake_case_						:    Union[str, Any]				=  dict(zip(__magic_name__					,							range(len(__magic_name__    )    )    )    )
							snake_case_						:    Union[str, Any]				=  ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

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






			def 			lowerCamelCase  (self					,							__magic_name__    )     ->   int:


							'''simple docstring'''



							snake_case_						:    str				=  '''lower newer'''
							snake_case_						:    Dict				=  '''lower newer'''
							return input_text, output_text






			def 			lowerCamelCase  (self    )     ->   Union[str, Any]:


							'''simple docstring'''



							snake_case_						:    Optional[int]				=  BioGptTokenizer(self.vocab_file					,							self.merges_file    )

							snake_case_						:    Union[str, Any]				=  '''lower'''
							snake_case_						:    Optional[int]				=  ['''low''', '''er</w>''']
							snake_case_						:    Any				=  tokenizer.tokenize(__magic_name__    )
							self.assertListEqual(__magic_name__					,							__magic_name__    )

							snake_case_						:    Optional[int]				=  tokens + ['''<unk>''']
							snake_case_						:    List[str]				=  [14, 15, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__    )					,							__magic_name__    )






			@slow
			def 			lowerCamelCase  (self    )     ->   Optional[Any]:


							'''simple docstring'''



							snake_case_						:    Optional[int]				=  BioGptTokenizer.from_pretrained('''microsoft/biogpt'''    )

							snake_case_						:    List[Any]				=  tokenizer.encode('''sequence builders'''					,							add_special_tokens=__magic_name__    )
							snake_case_						:    str				=  tokenizer.encode('''multi-sequence build'''					,							add_special_tokens=__magic_name__    )

							snake_case_						:    str				=  tokenizer.build_inputs_with_special_tokens(__magic_name__    )
							snake_case_						:    List[str]				=  tokenizer.build_inputs_with_special_tokens(__magic_name__					,							__magic_name__    )

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