





'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A_		:  List[str]		 =						logging.get_logger(__name__)

A_		:  Dict		 =						{
    "google/mobilenet_v1_1.0_224": "https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json",
    "google/mobilenet_v1_0.75_192": "https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}
class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      '''mobilenet_v1'''

   def __init__(							self	,		__SCREAMING_SNAKE_CASE=3	,		__SCREAMING_SNAKE_CASE=2_2_4	,		__SCREAMING_SNAKE_CASE=1.0	,		__SCREAMING_SNAKE_CASE=8	,		__SCREAMING_SNAKE_CASE="relu6"	,		__SCREAMING_SNAKE_CASE=True	,		__SCREAMING_SNAKE_CASE=0.999	,		__SCREAMING_SNAKE_CASE=0.02	,		__SCREAMING_SNAKE_CASE=0.001	,		**__SCREAMING_SNAKE_CASE	,		):
    super().__init__(**__SCREAMING_SNAKE_CASE       )

    if depth_multiplier <= 0:
     raise ValueError("""depth_multiplier must be greater than zero."""       )

    snake_case__     :					Optional[Any]    =  num_channels
    snake_case__     :					Tuple    =  image_size
    snake_case__     :					str    =  depth_multiplier
    snake_case__     :					Tuple    =  min_depth
    snake_case__     :					List[Any]    =  hidden_act
    snake_case__     :					int    =  tf_padding
    snake_case__     :					Tuple    =  classifier_dropout_prob
    snake_case__     :					Optional[Any]    =  initializer_range
    snake_case__     :					List[Any]    =  layer_norm_eps



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      version.parse('''1.11'''							)

   @property
   def 		__UpperCamelCase						(							self       ):
    return OrderedDict([("""pixel_values""", {0: """batch"""})]       )

   @property
   def 		__UpperCamelCase						(							self       ):
    if self.task == "image-classification":
     return OrderedDict([("""logits""", {0: """batch"""})]       )
    else:
     return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]       )


   @property
   def 		__UpperCamelCase						(							self       ):
    return 1e-4









from __future__ import annotations






class     __a			:



	def __init__(    self				:     List[Any]					,						snake_case_				:     str					,						snake_case_				:     str)->				Optional[int]:
						__lowerCAmelCase ,						__lowerCAmelCase						 =text, pattern
						__lowerCAmelCase ,						__lowerCAmelCase						 =len(snake_case_), len(snake_case_)



	def 		UpperCamelCase				(    self				:     List[Any]					,						snake_case_				:     str)->				int:

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



	def 		UpperCamelCase				(    self				:     List[str]					,						snake_case_				:     int)->				int:

						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 		UpperCamelCase				(    self				:     Dict)->				list[int]:
						# searches pattern in text and returns index positions
						__lowerCAmelCase						 =[]
						for i in range(self.textLen - self.patLen + 1):
											__lowerCAmelCase						 =self.mismatch_in_text(snake_case_)
											if mismatch_index == -1:
																positions.append(snake_case_)
											else:
																__lowerCAmelCase						 =self.match_in_pattern(self.text[mismatch_index])
																__lowerCAmelCase						 =(
																    mismatch_index - match_index
																)  # shifting index lgtm [py/multiple-definition]
						return positions


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

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




