





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


A_												=     logging.get_logger(__name__)

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

A_												=     {
    "vocab_file": {
        "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt",
        "distilbert-base-uncased-distilled-squad": (
            "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt"
        ),
        "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt",
        "distilbert-base-cased-distilled-squad": (
            "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt"
        ),
        "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt",
        "distilbert-base-multilingual-cased": (
            "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json",
        "distilbert-base-uncased-distilled-squad": (
            "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json"
        ),
        "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json",
        "distilbert-base-cased-distilled-squad": (
            "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json"
        ),
        "distilbert-base-german-cased": (
            "https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json"
        ),
        "distilbert-base-multilingual-cased": (
            "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json"
        ),
    },
}

A_												=     {
    "distilbert-base-uncased": 5_1_2,
    "distilbert-base-uncased-distilled-squad": 5_1_2,
    "distilbert-base-cased": 5_1_2,
    "distilbert-base-cased-distilled-squad": 5_1_2,
    "distilbert-base-german-cased": 5_1_2,
    "distilbert-base-multilingual-cased": 5_1_2,
}


A_												=     {
    "distilbert-base-uncased": {"do_lower_case": True},
    "distilbert-base-uncased-distilled-squad": {"do_lower_case": True},
    "distilbert-base-cased": {"do_lower_case": False},
    "distilbert-base-cased-distilled-squad": {"do_lower_case": False},
    "distilbert-base-german-cased": {"do_lower_case": False},
    "distilbert-base-multilingual-cased": {"do_lower_case": False},
}

class SCREAMING_SNAKE_CASE_ (					__UpperCAmelCase   ):





					"""simple docstring"""


					A__				 =    VOCAB_FILES_NAMES
					A__				 =    PRETRAINED_VOCAB_FILES_MAP
					A__				 =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A__				 =    PRETRAINED_INIT_CONFIGURATION
					A__				 =    ["input_ids", "attention_mask"]
					A__				 =    DistilBertTokenizer





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

										lowerCamelCase__       =       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
										):
															lowerCamelCase__       =       getattr(lowerCAmelCase_	,  normalizer_state.pop("type"	)	)
															lowerCamelCase__       =       do_lower_case
															lowerCamelCase__       =       strip_accents
															lowerCamelCase__       =       tokenize_chinese_chars
															lowerCamelCase__       =       normalizer_class(**lowerCAmelCase_	)

										lowerCamelCase__       =       do_lower_case





					def 					__magic_name__ ( self	,  _lowerCAmelCase	,  _lowerCAmelCase=None	):
										lowerCamelCase__       =       [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 					__magic_name__ ( self	,  _lowerCAmelCase	,  _lowerCAmelCase = None	):
										lowerCamelCase__       =       [self.sep_token_id]
										lowerCamelCase__       =       [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 					__magic_name__ ( self	,  _lowerCAmelCase	,  _lowerCAmelCase = None	):
										lowerCamelCase__       =       self._tokenizer.model.save(lowerCAmelCase_	,  name=lowerCAmelCase_	)
										return tuple(lowerCAmelCase_	)








from __future__ import annotations

class SCREAMING_SNAKE_CASE_ :





					"""simple docstring"""


					def __init__( self	,  _lowerCAmelCase	,  _lowerCAmelCase	):
										lowerCamelCase__    ,		lowerCamelCase__       =       text, pattern
										lowerCamelCase__    ,		lowerCamelCase__       =       len(_lowerCAmelCase	), len(_lowerCAmelCase	)





					def 					__magic_name__ ( self	,  _lowerCAmelCase	):

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





					def 					__magic_name__ ( self	,  _lowerCAmelCase	):

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

A_												=     "ABAABA"
A_												=     "AB"
A_												=     BoyerMooreSearch(text, pattern)
A_												=     bms.bad_character_heuristic()

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

