





from __future__ import annotations

from collections import deque






class     lowercase__       :

   '''simple docstring'''


   def __init__(    self,		__magic_name__							) ->      Tuple:






       """simple docstring"""
       UpperCamelCase__							:				list[dict]          =      []
       self.adlist.append(
           {'''value''': '''''', '''next_states''': [], '''fail_state''': 0, '''output''': []}							)

       for keyword in keywords:
           self.add_keyword(__magic_name__							)
       self.set_fail_transitions()




   def       UpperCamelCase__  (    self,		__magic_name__,		__magic_name__							) ->      int | None:






       """simple docstring"""
       for state in self.adlist[current_state]["next_states"]:
           if char == self.adlist[state]["value"]:
               return state
       return None




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      None:






       """simple docstring"""
       UpperCamelCase__							:				Optional[int]          =      0
       for character in keyword:
           UpperCamelCase__							:				List[Any]          =      self.find_next_state(__magic_name__,		__magic_name__							)
           if next_state is None:
               self.adlist.append(
                   {
                       '''value''': character,
                       '''next_states''': [],
                       '''fail_state''': 0,
                       '''output''': [],
                   }							)
               self.adlist[current_state]["next_states"].append(len(self.adlist							) - 1							)
               UpperCamelCase__							:				Any          =      len(self.adlist							) - 1
           else:
               UpperCamelCase__							:				int          =      next_state
       self.adlist[current_state]["output"].append(__magic_name__							)




   def       UpperCamelCase__  (    self							) ->      None:






       """simple docstring"""
       UpperCamelCase__							:				deque          =      deque()
       for node in self.adlist[0]["next_states"]:
           q.append(__magic_name__							)
           UpperCamelCase__							:				str          =      0
       while q:
           UpperCamelCase__							:				List[Any]          =      q.popleft()
           for child in self.adlist[r]["next_states"]:
               q.append(__magic_name__							)
               UpperCamelCase__							:				List[str]          =      self.adlist[r]['''fail_state''']
               while (
                   self.find_next_state(__magic_name__,		self.adlist[child]['''value''']							) is None
                   and state != 0
               ):
                   UpperCamelCase__							:				int          =      self.adlist[state]['''fail_state''']
               UpperCamelCase__							:				int          =      self.find_next_state(
                   __magic_name__,		self.adlist[child]['''value''']							)
               if self.adlist[child]["fail_state"] is None:
                   UpperCamelCase__							:				str          =      0
               UpperCamelCase__							:				Optional[Any]          =      (
                   self.adlist[child]['''output''']
                   + self.adlist[self.adlist[child]['''fail_state''']]['''output''']
               )




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      dict[str, list[int]]:






       """simple docstring"""
       UpperCamelCase__							:				dict          =      {}  # returns a dict with keywords and list of its occurrences
       UpperCamelCase__							:				List[str]          =      0
       for i in range(len(__magic_name__							)							):
           while (
               self.find_next_state(__magic_name__,		string[i]							) is None
               and current_state != 0
           ):
               UpperCamelCase__							:				Optional[Any]          =      self.adlist[current_state]['''fail_state''']
           UpperCamelCase__							:				Optional[Any]          =      self.find_next_state(__magic_name__,		string[i]							)
           if next_state is None:
               UpperCamelCase__							:				Union[str, Any]          =      0
           else:
               UpperCamelCase__							:				Optional[Any]          =      next_state
               for key in self.adlist[current_state]["output"]:
                   if key not in result:
                       UpperCamelCase__							:				Optional[int]          =      []
                   result[key].append(i - len(__magic_name__							) + 1							)
       return result


if __name__ == "__main__":
  import doctest

  doctest.testmod()








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


UpperCAmelCase_     							= logging.get_logger(__name__)

UpperCAmelCase_     							= {
    'google/mobilenet_v2_1.4_224': 'https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json',
    'google/mobilenet_v2_1.0_224': 'https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json',
    'google/mobilenet_v2_0.75_160': 'https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json',
    'google/mobilenet_v2_0.35_96': 'https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}






class     lowercase__       (	__lowerCamelCase				):

   '''simple docstring'''


   a						:							List[str]   		=		"mobilenet_v2"




   def __init__(    self,		__magic_name__=3,		__magic_name__=224,		__magic_name__=1.0,		__magic_name__=8,		__magic_name__=8,		__magic_name__=6,		__magic_name__=32,		__magic_name__=True,		__magic_name__=True,		__magic_name__="relu6",		__magic_name__=True,		__magic_name__=0.8,		__magic_name__=0.02,		__magic_name__=0.001,		__magic_name__=255,		**__magic_name__,		) ->      List[Any]:






       """simple docstring"""
       super().__init__(**__magic_name__							)

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

       UpperCamelCase__							:				Union[str, Any]          =      num_channels
       UpperCamelCase__							:				int          =      image_size
       UpperCamelCase__							:				int          =      depth_multiplier
       UpperCamelCase__							:				Tuple          =      depth_divisible_by
       UpperCamelCase__							:				List[str]          =      min_depth
       UpperCamelCase__							:				Optional[int]          =      expand_ratio
       UpperCamelCase__							:				Optional[int]          =      output_stride
       UpperCamelCase__							:				Tuple          =      first_layer_is_expansion
       UpperCamelCase__							:				Union[str, Any]          =      finegrained_output
       UpperCamelCase__							:				str          =      hidden_act
       UpperCamelCase__							:				Optional[Any]          =      tf_padding
       UpperCamelCase__							:				Optional[int]          =      classifier_dropout_prob
       UpperCamelCase__							:				int          =      initializer_range
       UpperCamelCase__							:				Union[str, Any]          =      layer_norm_eps
       UpperCamelCase__							:				Tuple          =      semantic_loss_ignore_index






class     lowercase__       (	__lowerCamelCase				):

   '''simple docstring'''


   a						:							Union[str, Any]   		=		version.parse("1.11"				)




   @property
   def       UpperCamelCase__  (    self							) ->      Mapping[str, Mapping[int, str]]:






       """simple docstring"""
       return OrderedDict([('''pixel_values''', {0: '''batch'''})]							)




   @property
   def       UpperCamelCase__  (    self							) ->      Mapping[str, Mapping[int, str]]:






       """simple docstring"""
       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							) ->      float:






       """simple docstring"""
       return 1E-4

