


from __future__ import annotations

class   A__ :







    """simple docstring"""

    def __init__(	self      , __snake_case      , __snake_case   ):
         snake_case			,  snake_case					=    text, pattern
         snake_case			,  snake_case					=    len(__snake_case   ), len(__snake_case   )
    def 		a_      (	self      , __snake_case   ):

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

         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   ):
         # searches pattern in text and returns index positions
         snake_case					=    []
         for i in range(self.textLen - self.patLen + 1   ):
              snake_case					=    self.mismatch_in_text(__snake_case   )
              if mismatch_index == -1:
                   positions.append(__snake_case   )
              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






_SCREAMING_SNAKE_CASE      :			str      				=   "ABAABA"
_SCREAMING_SNAKE_CASE      :			Optional[int]      				=   "AB"
_SCREAMING_SNAKE_CASE      :			List[Any]      				=   BoyerMooreSearch(text, pattern)
_SCREAMING_SNAKE_CASE      :			Dict      				=   bms.bad_character_heuristic()

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








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_SCREAMING_SNAKE_CASE      :			int      				=   {
    "configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE      :			Dict      				=   [
     "TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TimesformerModel",
     "TimesformerForVideoClassification",
     "TimesformerPreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_timesformer import (
      TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TimesformerForVideoClassification,
      TimesformerModel,
      TimesformerPreTrainedModel,
  )

else:
 import sys

 _SCREAMING_SNAKE_CASE      :			int      				=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




