
'''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


lowercase    :							List[Any]      =					logging.get_logger(__name__)

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

lowercase    :							Dict      =					{
    "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"
        ),
    },
}

lowercase    :							Tuple      =					{
    "yjernite/retribert-base-uncased": 512,
}


lowercase    :							Optional[Any]      =					{
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}


class 						__UpperCAmelCase      (					_lowerCamelCase						):
							__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    ,   lowerCAmelCase_=None    ,   lowerCAmelCase_=None    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_="[UNK]"    ,   lowerCAmelCase_="[SEP]"    ,   lowerCAmelCase_="[PAD]"    ,   lowerCAmelCase_="[CLS]"    ,   lowerCAmelCase_="[MASK]"    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_=None    ,   **lowerCAmelCase_    ,   ):





								"""simple docstring"""






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

								_snake_case   						=		json.loads(self.backend_tokenizer.normalizer.__getstate__()  )
								if (
								    normalizer_state.get('lowercase'    ,   lowerCAmelCase_  ) != do_lower_case
								    or normalizer_state.get('strip_accents'    ,   lowerCAmelCase_  ) != strip_accents
								    or normalizer_state.get('handle_chinese_chars'    ,   lowerCAmelCase_  ) != tokenize_chinese_chars
								):
									_snake_case   						=		getattr(lowerCAmelCase_    ,   normalizer_state.pop('type'  )  )
									_snake_case   						=		do_lower_case
									_snake_case   						=		strip_accents
									_snake_case   						=		tokenize_chinese_chars
									_snake_case   						=		normalizer_class(**lowerCAmelCase_  )

								_snake_case   						=		do_lower_case


							def  lowerCamelCase				(       self    ,   lowerCAmelCase_    ,   lowerCAmelCase_=None  ):





								"""simple docstring"""






								_snake_case   						=		[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    ,   lowerCAmelCase_    ,   lowerCAmelCase_ = None  ):





								"""simple docstring"""






								_snake_case   						=		[self.sep_token_id]
								_snake_case   						=		[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    ,   lowerCAmelCase_    ,   lowerCAmelCase_ = None  ):





								"""simple docstring"""






								_snake_case   						=		self._tokenizer.model.save(lowerCAmelCase_    ,   name=lowerCAmelCase_  )
								return tuple(lowerCAmelCase_  )


from __future__ import annotations


class      lowerCamelCase    :
  """simple docstring"""







  def __init__(							self       :				Union[str, Any]     ,   __magic_name__       :				str     ,   __magic_name__       :				str      )     ->		Dict:
        SCREAMING_SNAKE_CASE_   ,       SCREAMING_SNAKE_CASE_      =     text, pattern
        SCREAMING_SNAKE_CASE_   ,       SCREAMING_SNAKE_CASE_      =     len(__magic_name__      ), len(__magic_name__      )







  def       __A   (							self       :				List[str]     ,   __magic_name__       :				str      )     ->		int:

        for i in range(self.patLen - 1     ,   -1     ,   -1      ):
              if char == self.pattern[i]:
                    return i
        return -1







  def       __A   (							self       :				Dict     ,   __magic_name__       :				int      )     ->		int:

        for i in range(self.patLen - 1     ,   -1     ,   -1      ):
              if self.pattern[i] != self.text[current_pos + i]:
                    return current_pos + i
        return -1







  def       __A   (							self       :				Tuple      )     ->		list[int]:
        # searches pattern in text and returns index positions
        SCREAMING_SNAKE_CASE_      =     []
        for i in range(self.textLen - self.patLen + 1      ):
              SCREAMING_SNAKE_CASE_      =     self.mismatch_in_text(__magic_name__      )
              if mismatch_index == -1:
                    positions.append(__magic_name__      )
              else:
                    SCREAMING_SNAKE_CASE_      =     self.match_in_pattern(self.text[mismatch_index]      )
                    SCREAMING_SNAKE_CASE_      =     (
                        mismatch_index - match_index
                    )  # shifting index lgtm [py/multiple-definition]
        return positions



A   :     Dict       =				"ABAABA"
A   :     Union[str, Any]       =				"AB"
A   :     str       =				BoyerMooreSearch(text, pattern)
A   :     Tuple       =				bms.bad_character_heuristic()

if len(positions) == 0:
      print("No match found")
else:
      print("Pattern found in following positions: ")
      print(positions)


