


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


__UpperCAmelCase : Dict 			=				logging.get_logger(__name__)

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

__UpperCAmelCase : Tuple 			=				{
    "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"
        ),
    },
}

__UpperCAmelCase : Optional[Any] 			=				{
    "yjernite/retribert-base-uncased": 512,
}


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



class    UpperCAmelCase_	(							_a):
       '''simple docstring'''
       __UpperCamelCase      :     Dict							=					VOCAB_FILES_NAMES
       __UpperCamelCase      :     Dict							=					PRETRAINED_VOCAB_FILES_MAP
       __UpperCamelCase      :     Optional[int]							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __UpperCamelCase      :     Any							=					PRETRAINED_INIT_CONFIGURATION
       __UpperCamelCase      :     List[Any]							=					RetriBertTokenizer
       __UpperCamelCase      :     Tuple							=					["input_ids", "attention_mask"]






       def __init__(     self ,					__SCREAMING_SNAKE_CASE=None ,					__SCREAMING_SNAKE_CASE=None ,					__SCREAMING_SNAKE_CASE=True ,					__SCREAMING_SNAKE_CASE="[UNK]" ,					__SCREAMING_SNAKE_CASE="[SEP]" ,					__SCREAMING_SNAKE_CASE="[PAD]" ,					__SCREAMING_SNAKE_CASE="[CLS]" ,					__SCREAMING_SNAKE_CASE="[MASK]" ,					__SCREAMING_SNAKE_CASE=True ,					__SCREAMING_SNAKE_CASE=None ,					**__SCREAMING_SNAKE_CASE ,					):




              """simple docstring"""




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

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

              UpperCamelCase    :	List[Any]   	=		do_lower_case






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE=None						):




              """simple docstring"""




              UpperCamelCase    :	Optional[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  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE = None						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		[self.sep_token_id]
              UpperCamelCase    :	List[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  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE = None						):




              """simple docstring"""




              UpperCamelCase    :	str   	=		self._tokenizer.model.save(__SCREAMING_SNAKE_CASE ,					name=__SCREAMING_SNAKE_CASE						)
              return tuple(__SCREAMING_SNAKE_CASE						)





import re
from pathlib import Path
from unittest import TestCase

import pytest



@pytest.mark.integration
class    UpperCAmelCase_	(							_a):
       '''simple docstring'''






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              with open(__SCREAMING_SNAKE_CASE ,					encoding='''utf-8'''						) as input_file:
                     UpperCamelCase    :	str   	=		re.compile(R'''(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)'''						)
                     UpperCamelCase    :	Optional[int]   	=		input_file.read()
                     UpperCamelCase    :	Union[str, Any]   	=		regexp.search(__SCREAMING_SNAKE_CASE						)

              return match






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              with open(__SCREAMING_SNAKE_CASE ,					encoding='''utf-8'''						) as input_file:
                     UpperCamelCase    :	Optional[int]   	=		re.compile(R'''#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()''' ,					re.DOTALL						)
                     UpperCamelCase    :	Tuple   	=		input_file.read()
                     # use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
                     UpperCamelCase    :	Dict   	=		regexp.finditer(__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	int   	=		[match for match in matches if match is not None and match.group(1						) is not None]
              return matches[0] if matches else None






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	int   	=		Path('''./datasets'''						)
              UpperCamelCase    :	Tuple   	=		list(dataset_paths.absolute().glob('''**/*.py'''						)						)

              for dataset in dataset_files:
                     if self._no_encoding_on_file_open(str(__SCREAMING_SNAKE_CASE						)						):
                            raise AssertionError(f"""open(...) must use utf-8 encoding in {dataset}"""						)






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Optional[int]   	=		Path('''./datasets'''						)
              UpperCamelCase    :	Tuple   	=		list(dataset_paths.absolute().glob('''**/*.py'''						)						)

              for dataset in dataset_files:
                     if self._no_print_statements(str(__SCREAMING_SNAKE_CASE						)						):
                            raise AssertionError(f"""print statement found in {dataset}. Use datasets.logger/logging instead."""						)

