




from __future__ import annotations

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					list[int]:  # This function is recursive
     a     =				len(__UpperCamelCase)
     # If the array contains only one element, we return it (it's the stop condition of
     # recursion)
     if array_length <= 1:
          return array
          # Else
     a     =				array[0]
     a     =				False
     a     =				1
     a     =				[]
     while not is_found and i < array_length:
          if array[i] < pivot:
               a     =				True
               a     =				[element for element in array[i:] if element >= array[i]]
               a     =				longest_subsequence(__UpperCamelCase)
               if len(__UpperCamelCase) > len(__UpperCamelCase):
                    a     =				temp_array
          else:
               i += 1

     a     =				[element for element in array[1:] if element >= pivot]
     a     =				[pivot, *longest_subsequence(__UpperCamelCase)]
     if len(__UpperCamelCase) > len(__UpperCamelCase):
          return temp_array
     else:
          return longest_subseq


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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowercase__				:      Tuple	   = logging.get_logger(__name__)

lowercase__				:      int	   = {
    "microsoft/resnet-50": "https://huggingface.co/microsoft/resnet-50/blob/main/config.json",
}




class       a__	( UpperCamelCase__       , UpperCamelCase__				):
     a		:      Any		 =     """resnet"""
     a		:      Tuple		 =     ["""basic""", """bottleneck"""]







     def __init__(     self  ,		A=3  ,		A=64  ,		A=[256, 512, 1024, 2048]  ,		A=[3, 4, 6, 3]  ,		A="bottleneck"  ,		A="relu"  ,		A=False  ,		A=None  ,		A=None  ,		**A  ,		)  ->   Any:



          '''simple docstring'''



          super().__init__(**A			)
          if layer_type not in self.layer_types:
               raise ValueError(F'''layer_type={layer_type} is not one of {",".join(self.layer_types			)}'''			)
          a     =				num_channels
          a     =				embedding_size
          a     =				hidden_sizes
          a     =				depths
          a     =				layer_type
          a     =				hidden_act
          a     =				downsample_in_first_stage
          a     =				["stem"] + [F'''stage{idx}''' for idx in range(1  ,		len(A			) + 1			)]
          a  ,				a     =				get_aligned_output_features_output_indices(
              out_features=A  ,		out_indices=A  ,		stage_names=self.stage_names			)







class       a__	( UpperCamelCase__				):
     a		:      Optional[int]		 =     version.parse("""1.11"""				)







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



          '''simple docstring'''



          return OrderedDict(
              [
                  ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
              ]			)







     @property
     def       lowerCAmelCase_    (     self			)  ->   float:



          '''simple docstring'''



          return 1e-3

