





from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
SCREAMING_SNAKE_CASE__			      =						1_0






def       _A  (      lowerCamelCase							, lowerCamelCase							, lowerCamelCase							, lowerCamelCase   ):
   for i in range(snake_case_							, snake_case_   ):
      if array[i] == target:
         return i
   return -1






def       _A  (      lowerCamelCase							, lowerCamelCase   ):
   a__	:						Any      		=  0
   a__	:						int      		=  len(snake_case_   )
   while left <= right:
      if right - left < precision:
         return lin_search(snake_case_							, snake_case_							, snake_case_							, snake_case_   )

      a__	:						List[Any]      		=  (left + right) // 3 + 1
      a__	:						Any      		=  2 * (left + right) // 3 + 1

      if array[one_third] == target:
         return one_third
      elif array[two_third] == target:
         return two_third

      elif target < array[one_third]:
         a__	:						Union[str, Any]      		=  one_third - 1
      elif array[two_third] < target:
         a__	:						List[str]      		=  two_third + 1

      else:
         a__	:						List[str]      		=  one_third + 1
         a__	:						Union[str, Any]      		=  two_third - 1
   else:
      return -1






def       _A  (      lowerCamelCase							, lowerCamelCase							, lowerCamelCase							, lowerCamelCase   ):
   if left < right:
      if right - left < precision:
         return lin_search(snake_case_							, snake_case_							, snake_case_							, snake_case_   )
      a__	:						str      		=  (left + right) // 3 + 1
      a__	:						Optional[Any]      		=  2 * (left + right) // 3 + 1

      if array[one_third] == target:
         return one_third
      elif array[two_third] == target:
         return two_third

      elif target < array[one_third]:
         return rec_ternary_search(snake_case_							, one_third - 1							, snake_case_							, snake_case_   )
      elif array[two_third] < target:
         return rec_ternary_search(two_third + 1							, snake_case_							, snake_case_							, snake_case_   )
      else:
         return rec_ternary_search(one_third + 1							, two_third - 1							, snake_case_							, snake_case_   )
   else:
      return -1


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  SCREAMING_SNAKE_CASE__			      =						input("""Enter numbers separated by comma:\n""").strip()
  SCREAMING_SNAKE_CASE__			      =						[int(item.strip()) for item in user_input.split(""",""")]
  assert collection == sorted(collection), f"List must be ordered.\n{collection}."
  SCREAMING_SNAKE_CASE__			      =						int(input("""Enter the number to be found in the list:\n""").strip())
  SCREAMING_SNAKE_CASE__			      =						ite_ternary_search(collection, target)
  SCREAMING_SNAKE_CASE__			      =						rec_ternary_search(0, len(collection) - 1, collection, target)
  if resulta != -1:
    print(f'Iterative search: {target} found at positions: {resulta}')
    print(f'Recursive search: {target} found at positions: {resulta}')
  else:
    print("""Not found""")








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


SCREAMING_SNAKE_CASE__       :			Dict			      =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       :			Any			      =						{
    """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   __lowerCAmelCase			(					_UpperCamelCase  ):
   _UpperCamelCase :						Optional[int]     		=				"""mobilenet_v2"""





   def __init__( self					,			snake_case=3					,			snake_case=224					,			snake_case=1.0					,			snake_case=8					,			snake_case=8					,			snake_case=6					,			snake_case=32					,			snake_case=True					,			snake_case=True					,			snake_case="relu6"					,			snake_case=True					,			snake_case=0.8					,			snake_case=0.02					,			snake_case=0.001					,			snake_case=255					,			**snake_case					,			)				->  int:
      """simple docstring"""





      super().__init__(**snake_case      )

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

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







class   __lowerCAmelCase			(					_UpperCamelCase  ):
   _UpperCamelCase :						Any     		=				version.parse("""1.11"""  )





   @property
   def 	_snake_case ( self      )				->  Mapping[str, Mapping[int, str]]:
      """simple docstring"""





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





   @property
   def 	_snake_case ( 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 	_snake_case ( self      )				->  float:
      """simple docstring"""





      return 1E-4

