




"""simple docstring"""


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


A_						=				logging.get_logger(__name__)

A_						=				{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

A_						=				{
    "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"
        ),
    },
}

A_						=				{
    "yjernite/retribert-base-uncased": 5_12,
}


A_						=				{
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}






class 					lowercase(     __lowerCamelCase ):







 '''simple docstring'''





 lowercase__ 					=					VOCAB_FILES_NAMES
 lowercase__ 					=					PRETRAINED_VOCAB_FILES_MAP
 lowercase__ 					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase__ 					=					PRETRAINED_INIT_CONFIGURATION
 lowercase__ 					=					RetriBertTokenizer
 lowercase__ 					=					["input_ids", "attention_mask"]


 def __init__(				self:		Optional[Any],      a_:		Optional[int]=None,      a_:		str=None,      a_:		Optional[Any]=True,      a_:		Any="[UNK]",      a_:		Optional[int]="[SEP]",      a_:		Optional[int]="[PAD]",      a_:		List[Any]="[CLS]",      a_:		Optional[Any]="[MASK]",      a_:		Tuple=True,      a_:		Union[str, Any]=None,      **a_:		str,      ):




   '''simple docstring'''



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

   _snake_case							:		Dict								=  json.loads(self.backend_tokenizer.normalizer.__getstate__()		)
   if (
       normalizer_state.get("""lowercase""",      a_		) != do_lower_case
       or normalizer_state.get("""strip_accents""",      a_		) != strip_accents
       or normalizer_state.get("""handle_chinese_chars""",      a_		) != tokenize_chinese_chars
   ):
     _snake_case							:		Dict								=  getattr(a_,      normalizer_state.pop("""type"""		)		)
     _snake_case							:		Dict								=  do_lower_case
     _snake_case							:		str								=  strip_accents
     _snake_case							:		Any								=  tokenize_chinese_chars
     _snake_case							:		List[str]								=  normalizer_class(**a_		)

   _snake_case							:		Dict								=  do_lower_case


 def  UpperCamelCase_   (				self:		int,      a_:		Union[str, Any],      a_:		Optional[int]=None		):




   '''simple docstring'''



   _snake_case							:		List[Any]								=  [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  UpperCamelCase_   (				self:		Union[str, Any],      a_:		List[int],      a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   _snake_case							:		Optional[int]								=  [self.sep_token_id]
   _snake_case							:		str								=  [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  UpperCamelCase_   (				self:		str,      a_:		str,      a_:		Optional[str] = None		):




   '''simple docstring'''



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









import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin







class     __snake_case       (							unittest.TestCase   ,			__lowerCamelCase			):





       '''simple docstring'''







       def 							UpperCAmelCase__ (  self :    Union[str, Any]		):
         __snake_case:						Optional[int]   =						load_tool("""text-classification"""		)
         self.tool.setup()
         __snake_case:						Dict   =						load_tool("""text-classification"""							,				remote=A		)




       def 							UpperCAmelCase__ (  self :    Optional[int]		):
         __snake_case:						List[str]   =						self.tool("""That's quite cool"""							,				["""positive""", """negative"""]		)
         self.assertEqual(A							,				"""positive"""		)




       def 							UpperCAmelCase__ (  self :    Dict		):
         __snake_case:						List[str]   =						self.remote_tool("""That's quite cool"""							,				["""positive""", """negative"""]		)
         self.assertEqual(A							,				"""positive"""		)




       def 							UpperCAmelCase__ (  self :    Optional[Any]		):
         __snake_case:						Optional[Any]   =						self.tool(text="""That's quite cool"""							,				labels=["""positive""", """negative"""]		)
         self.assertEqual(A							,				"""positive"""		)






       def 							UpperCAmelCase__ (  self :    Tuple		):
         __snake_case:						int   =						self.remote_tool(text="""That's quite cool"""							,				labels=["""positive""", """negative"""]		)
         self.assertEqual(A							,				"""positive"""		)






