

from __future__ import annotations

class     __snake_case    :
       """simple docstring"""







       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase   )      ->							Tuple:






              """simple docstring"""


              __snake_case	,    __snake_case       	=							text, pattern
              __snake_case	,    __snake_case       	=							len(_UpperCamelCase   ), len(_UpperCamelCase   )


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


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


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


              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   )      ->							list[int]:






              """simple docstring"""


              __snake_case       	=							[]
              for i in range(self.textLen - self.patLen + 1   ):
                     __snake_case       	=							self.mismatch_in_text(_UpperCamelCase   )
                     if mismatch_index == -1:
                            positions.append(_UpperCamelCase   )
                     else:
                            __snake_case       	=							self.match_in_pattern(self.text[mismatch_index]   )
                            __snake_case       	=							(
                                mismatch_index - match_index
                            )  # shifting index lgtm [py/multiple-definition]
              return positions






UpperCamelCase__		 =     '''ABAABA'''
UpperCamelCase__		 =     '''AB'''
UpperCamelCase__		 =     BoyerMooreSearch(text, pattern)
UpperCamelCase__		 =     bms.bad_character_heuristic()

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




import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


UpperCamelCase__		 =     logging.get_logger(__name__)


UpperCamelCase__		 =     {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

# See all LED models at https://huggingface.co/models?filter=LED
UpperCamelCase__		 =     {
    '''vocab_file''': {
        '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json''',
    },
}

UpperCamelCase__		 =     {
    '''allenai/led-base-16384''': 16384,
}







@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 						lowerCamelCase__      ( ):


       """simple docstring"""




       __snake_case       	=							(
           list(range(ord("""!"""		)	,ord("""~"""		) + 1		)		) + list(range(ord("""¡"""		)	,ord("""¬"""		) + 1		)		) + list(range(ord("""®"""		)	,ord("""ÿ"""		) + 1		)		)
       )
       __snake_case       	=							bs[:]
       __snake_case       	=							0
       for b in range(2**8		):
              if b not in bs:
                     bs.append(__A		)
                     cs.append(2**8 + n		)
                     n += 1
       __snake_case       	=							[chr(__A		) for n in cs]
       return dict(zip(__A	,__A		)		)







def 						lowerCamelCase__      ( __A    :Dict		):


       """simple docstring"""




       __snake_case       	=							set()
       __snake_case       	=							word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)		)
              __snake_case       	=							char
       return pairs




class     __snake_case    (				snake_case__  ):
       """simple docstring"""







       __SCREAMING_SNAKE_CASE				    =							VOCAB_FILES_NAMES
       __SCREAMING_SNAKE_CASE				    =							PRETRAINED_VOCAB_FILES_MAP
       __SCREAMING_SNAKE_CASE				    =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __SCREAMING_SNAKE_CASE				    =							["input_ids", "attention_mask"]


       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase      , _UpperCamelCase="replace"      , _UpperCamelCase="<s>"      , _UpperCamelCase="</s>"      , _UpperCamelCase="</s>"      , _UpperCamelCase="<s>"      , _UpperCamelCase="<unk>"      , _UpperCamelCase="<pad>"      , _UpperCamelCase="<mask>"      , _UpperCamelCase=False      , **_UpperCamelCase      , )      ->							Optional[int]:






              """simple docstring"""


              __snake_case       	=							AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   ) if isinstance(_UpperCamelCase      , _UpperCamelCase   ) else bos_token
              __snake_case       	=							AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   ) if isinstance(_UpperCamelCase      , _UpperCamelCase   ) else eos_token
              __snake_case       	=							AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   ) if isinstance(_UpperCamelCase      , _UpperCamelCase   ) else sep_token
              __snake_case       	=							AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   ) if isinstance(_UpperCamelCase      , _UpperCamelCase   ) else cls_token
              __snake_case       	=							AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   ) if isinstance(_UpperCamelCase      , _UpperCamelCase   ) else unk_token
              __snake_case       	=							AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   ) if isinstance(_UpperCamelCase      , _UpperCamelCase   ) else pad_token

              # Mask token behave like a normal word, i.e. include the space before it
              __snake_case       	=							AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   ) if isinstance(_UpperCamelCase      , _UpperCamelCase   ) else mask_token

              super().__init__(
                  errors=_UpperCamelCase      , bos_token=_UpperCamelCase      , eos_token=_UpperCamelCase      , unk_token=_UpperCamelCase      , sep_token=_UpperCamelCase      , cls_token=_UpperCamelCase      , pad_token=_UpperCamelCase      , mask_token=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , **_UpperCamelCase      , )

              with open(_UpperCamelCase      , encoding="""utf-8"""   ) as vocab_handle:
                     __snake_case       	=							json.load(_UpperCamelCase   )
              __snake_case       	=							{v: k for k, v in self.encoder.items()}
              __snake_case       	=							errors  # how to handle errors in decoding
              __snake_case       	=							bytes_to_unicode()
              __snake_case       	=							{v: k for k, v in self.byte_encoder.items()}
              with open(_UpperCamelCase      , encoding="""utf-8"""   ) as merges_handle:
                     __snake_case       	=							merges_handle.read().split("""\n"""   )[1:-1]
              __snake_case       	=							[tuple(merge.split()   ) for merge in bpe_merges]
              __snake_case       	=							dict(zip(_UpperCamelCase      , range(len(_UpperCamelCase   )   )   )   )
              __snake_case       	=							{}
              __snake_case       	=							add_prefix_space

              # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
              __snake_case       	=							re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""   )


       @property
       # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
       def 			a		(		self   )      ->							List[Any]:






              """simple docstring"""


              return len(self.encoder   )


       def 			a		(		self   )      ->							List[str]:






              """simple docstring"""


              return dict(self.encoder      , **self.added_tokens_encoder   )


       def 			a		(		self      , _UpperCamelCase   )      ->							str:






              """simple docstring"""


              if token in self.cache:
                     return self.cache[token]
              __snake_case       	=							tuple(_UpperCamelCase   )
              __snake_case       	=							get_pairs(_UpperCamelCase   )

              if not pairs:
                     return token

              while True:
                     __snake_case       	=							min(_UpperCamelCase      , key=lambda _UpperCamelCase   : self.bpe_ranks.get(_UpperCamelCase      , float("""inf"""   )   )   )
                     if bigram not in self.bpe_ranks:
                            break
                     __snake_case	,    __snake_case       	=							bigram
                     __snake_case       	=							[]
                     __snake_case       	=							0
                     while i < len(_UpperCamelCase   ):
                            try:
                                   __snake_case       	=							word.index(_UpperCamelCase      , _UpperCamelCase   )
                            except ValueError:
                                   new_word.extend(word[i:]   )
                                   break
                            else:
                                   new_word.extend(word[i:j]   )
                                   __snake_case       	=							j

                            if word[i] == first and i < len(_UpperCamelCase   ) - 1 and word[i + 1] == second:
                                   new_word.append(first + second   )
                                   i += 2
                            else:
                                   new_word.append(word[i]   )
                                   i += 1
                     __snake_case       	=							tuple(_UpperCamelCase   )
                     __snake_case       	=							new_word
                     if len(_UpperCamelCase   ) == 1:
                            break
                     else:
                            __snake_case       	=							get_pairs(_UpperCamelCase   )
              __snake_case       	=							""" """.join(_UpperCamelCase   )
              __snake_case       	=							word
              return word


       def 			a		(		self      , _UpperCamelCase   )      ->							List[Any]:






              """simple docstring"""


              __snake_case       	=							[]
              for token in re.findall(self.pat      , _UpperCamelCase   ):
                     __snake_case       	=							"""""".join(
                         self.byte_encoder[b] for b in token.encode("""utf-8"""   )   )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
                     bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_UpperCamelCase   ).split(""" """   )   )
              return bpe_tokens


       def 			a		(		self      , _UpperCamelCase   )      ->							Optional[Any]:






              """simple docstring"""


              return self.encoder.get(_UpperCamelCase      , self.encoder.get(self.unk_token   )   )


       def 			a		(		self      , _UpperCamelCase   )      ->							Any:






              """simple docstring"""


              return self.decoder.get(_UpperCamelCase   )


       def 			a		(		self      , _UpperCamelCase   )      ->							str:






              """simple docstring"""


              __snake_case       	=							"""""".join(_UpperCamelCase   )
              __snake_case       	=							bytearray([self.byte_decoder[c] for c in text]   ).decode("""utf-8"""      , errors=self.errors   )
              return text


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None   )      ->							Tuple[str]:






              """simple docstring"""


              if not os.path.isdir(_UpperCamelCase   ):
                     logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
                     return
              __snake_case       	=							os.path.join(
                  _UpperCamelCase      , (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]   )
              __snake_case       	=							os.path.join(
                  _UpperCamelCase      , (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]   )

              with open(_UpperCamelCase      , """w"""      , encoding="""utf-8"""   ) as f:
                     f.write(json.dumps(self.encoder      , indent=2      , sort_keys=_UpperCamelCase      , ensure_ascii=_UpperCamelCase   ) + """\n"""   )

              __snake_case       	=							0
              with open(_UpperCamelCase      , """w"""      , encoding="""utf-8"""   ) as writer:
                     writer.write("""#version: 0.2\n"""   )
                     for bpe_tokens, token_index in sorted(self.bpe_ranks.items()      , key=lambda _UpperCamelCase   : kv[1]   ):
                            if index != token_index:
                                   logger.warning(
                                       F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                                       """ Please check that the tokenizer is not corrupted!"""   )
                                   __snake_case       	=							token_index
                            writer.write(""" """.join(_UpperCamelCase   ) + """\n"""   )
                            index += 1

              return vocab_file, merge_file


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None   )      ->							List[int]:






              """simple docstring"""


              if token_ids_a is None:
                     return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
              __snake_case       	=							[self.cls_token_id]
              __snake_case       	=							[self.sep_token_id]
              return cls + token_ids_a + sep + sep + token_ids_a + sep


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None      , _UpperCamelCase = False   )      ->							List[int]:






              """simple docstring"""


              if already_has_special_tokens:
                     return super().get_special_tokens_mask(
                         token_ids_a=_UpperCamelCase      , token_ids_a=_UpperCamelCase      , already_has_special_tokens=_UpperCamelCase   )

              if token_ids_a is None:
                     return [1] + ([0] * len(_UpperCamelCase   )) + [1]
              return [1] + ([0] * len(_UpperCamelCase   )) + [1, 1] + ([0] * len(_UpperCamelCase   )) + [1]


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None   )      ->							List[int]:






              """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 + sep + token_ids_a + sep   ) * [0]


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase=False      , **_UpperCamelCase   )      ->							List[str]:






              """simple docstring"""


              __snake_case       	=							kwargs.pop("""add_prefix_space"""      , self.add_prefix_space   )
              if (is_split_into_words or add_prefix_space) and (len(_UpperCamelCase   ) > 0 and not text[0].isspace()):
                     __snake_case       	=							""" """ + text
              return (text, kwargs)






       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None      , _UpperCamelCase = PaddingStrategy.DO_NOT_PAD      , _UpperCamelCase = None      , _UpperCamelCase = None      , )      ->							dict:






              """simple docstring"""


              __snake_case       	=							super()._pad(
                  encoded_inputs=_UpperCamelCase      , max_length=_UpperCamelCase      , padding_strategy=_UpperCamelCase      , pad_to_multiple_of=_UpperCamelCase      , return_attention_mask=_UpperCamelCase      , )

              # Load from model defaults
              if return_attention_mask is None:
                     __snake_case       	=							"""attention_mask""" in self.model_input_names

              if return_attention_mask and "global_attention_mask" in encoded_inputs:
                     __snake_case       	=							encoded_inputs[self.model_input_names[0]]
                     # `global_attention_mask` need to have the same length as other (sequential) inputs.
                     __snake_case       	=							len(encoded_inputs["""global_attention_mask"""]   ) != len(_UpperCamelCase   )

                     if needs_to_be_padded:
                            __snake_case       	=							len(_UpperCamelCase   ) - len(encoded_inputs["""global_attention_mask"""]   )

                            if self.padding_side == "right":
                                   # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                                   __snake_case       	=							(
                                       encoded_inputs["""global_attention_mask"""] + [-1] * difference
                                   )
                            elif self.padding_side == "left":
                                   __snake_case       	=							[-1] * difference + encoded_inputs[
                                       """global_attention_mask"""
                                   ]
                            else:
                                   raise ValueError("""Invalid padding strategy:""" + str(self.padding_side   )   )

              return encoded_inputs

