






from __future__ import annotations


class        __UpperCamelCase    :







	def __init__(  self      :							Any       ,				_lowerCAmelCase      :							List[str]       ,				_lowerCAmelCase      :							Optional[Any]			)		-> List[str]:
		"""simple docstring"""







		__lowercase             =  text, pattern
		__lowercase             =  len(snake_case_			), len(snake_case_			)







	def  _a   (  self      :							List[str]       ,				_lowerCAmelCase      :							Dict			)		-> Union[str, Any]:
		"""simple docstring"""







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







	def  _a   (  self      :							Any       ,				_lowerCAmelCase      :							List[Any]			)		-> Union[str, 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  _a   (  self      :							Union[str, Any]			)		-> Tuple:
		"""simple docstring"""







		__lowercase             =  []
		for i in range(self.textLen - self.patLen + 1			):
			__lowercase             =  self.mismatch_in_text(snake_case_			)
			if mismatch_index == -1:
				positions.append(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      :      List[Any]     						=						"""ABAABA"""
__UpperCamelCase      :      str     						=						"""AB"""
__UpperCamelCase      :      List[Any]     						=						BoyerMooreSearch(text, pattern)
__UpperCamelCase      :      Any     						=						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,
)


__UpperCamelCase      :      Tuple     						=						{
    """configuration_swiftformer""": [
        """SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwiftFormerConfig""",
        """SwiftFormerOnnxConfig""",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__UpperCamelCase      :      Optional[Any]     						=						[
						    """SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """SwiftFormerForImageClassification""",
						    """SwiftFormerModel""",
						    """SwiftFormerPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_swiftformer import (
						    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SwiftFormerConfig,
						    SwiftFormerOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_swiftformer import (
												    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SwiftFormerForImageClassification,
												    SwiftFormerModel,
												    SwiftFormerPreTrainedModel,
												)

else:
						import sys

						__UpperCamelCase      :      List[Any]     						=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

