


"""simple docstring"""

from __future__ import annotations





class  lowerCamelCase__    :
      def __init__(		self						:						Union[str, Any]   ,							A_						:						Tuple   ,							A_						:						int				):






       '''simple docstring'''


       __lowercase				,		__lowercase						=						text, pattern
       __lowercase				,		__lowercase						=						len(_SCREAMING_SNAKE_CASE				), len(_SCREAMING_SNAKE_CASE				)
      def SCREAMING_SNAKE_CASE_						(		self						:						int   ,							A_						:						Tuple				):






       '''simple docstring'''


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






       '''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 SCREAMING_SNAKE_CASE_						(		self						:						Dict				):






       '''simple docstring'''


       __lowercase						=						[]
       for i in range(self.textLen - self.patLen + 1				):
        __lowercase						=						self.mismatch_in_text(_SCREAMING_SNAKE_CASE				)
        if mismatch_index == -1:
         positions.append(_SCREAMING_SNAKE_CASE				)
        else:
         __lowercase						=						self.match_in_pattern(self.text[mismatch_index]				)
         __lowercase						=						(
             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)




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase__    :Tuple       =				{'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeiTConfig''', '''DeiTOnnxConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__    :List[Any]       =				['''DeiTFeatureExtractor''']
		lowerCAmelCase__    :Union[str, Any]       =				['''DeiTImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__    :Tuple       =				[
		    '''DEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''DeiTForImageClassification''',
		    '''DeiTForImageClassificationWithTeacher''',
		    '''DeiTForMaskedImageModeling''',
		    '''DeiTModel''',
		    '''DeiTPreTrainedModel''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__    :Union[str, Any]       =				[
		    '''TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TFDeiTForImageClassification''',
		    '''TFDeiTForImageClassificationWithTeacher''',
		    '''TFDeiTForMaskedImageModeling''',
		    '''TFDeiTModel''',
		    '''TFDeiTPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_deit import DeiTFeatureExtractor
				from .image_processing_deit import DeiTImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_deit import (
				    DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DeiTForImageClassification,
				    DeiTForImageClassificationWithTeacher,
				    DeiTForMaskedImageModeling,
				    DeiTModel,
				    DeiTPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_deit import (
				    TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFDeiTForImageClassification,
				    TFDeiTForImageClassificationWithTeacher,
				    TFDeiTForMaskedImageModeling,
				    TFDeiTModel,
				    TFDeiTPreTrainedModel,
				)


else:
		import sys

		lowerCAmelCase__    :List[str]       =				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
