




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


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

SCREAMING_SNAKE_CASE_    :       Optional[int]       =							{
    '''facebook/convnext-tiny-224''': '''https://huggingface.co/facebook/convnext-tiny-224/resolve/main/config.json''',
    # See all ConvNeXT models at https://huggingface.co/models?filter=convnext
}







class 		__UpperCAmelCase(		A_							,						A_			):





     """simple docstring"""



     __UpperCAmelCase						:			Dict							=     """convnext"""

     def __init__(   self			:							Dict    ,					A			:							Optional[int]=3    ,					A			:							str=4    ,					A			:							Union[str, Any]=4    ,					A			:							List[Any]=None    ,					A			:							Tuple=None    ,					A			:							Union[str, Any]="gelu"    ,					A			:							Optional[int]=0.0_2    ,					A			:							int=1E-12    ,					A			:							int=1E-6    ,					A			:							Optional[Any]=0.0    ,					A			:							int=2_24    ,					A			:							Dict=None    ,					A			:							Tuple=None    ,					**A			:							Union[str, Any]    ,					)      ->      Union[str, Any]:






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

         a__  			=							num_channels
         a__  			=							patch_size
         a__  			=							num_stages
         a__  			=							[96, 1_92, 3_84, 7_68] if hidden_sizes is None else hidden_sizes
         a__  			=							[3, 3, 9, 3] if depths is None else depths
         a__  			=							hidden_act
         a__  			=							initializer_range
         a__  			=							layer_norm_eps
         a__  			=							layer_scale_init_value
         a__  			=							drop_path_rate
         a__  			=							image_size
         a__  			=							['stem'] + [f"""stage{idx}""" for idx in range(1    ,					len(self.depths     ) + 1     )]
         a__  			=							get_aligned_output_features_output_indices(
             out_features=__lowerCamelCase    ,					out_indices=__lowerCamelCase    ,					stage_names=self.stage_names     )







class 		__UpperCAmelCase(		A_			):





     """simple docstring"""



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

     @property
     def 					__SCREAMING_SNAKE_CASE		(   self			:							List[Any]     )      ->      str:






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






     @property
     def 					__SCREAMING_SNAKE_CASE		(   self			:							Tuple     )      ->      Optional[int]:






         """simple docstring"""
         return 1E-5







"""simple docstring"""







from __future__ import annotations

import random
from collections.abc import Iterable
from typing import Any, Generic, TypeVar

lowerCamelCase      : List[str]       =TypeVar('''T''', bound=bool)






class 							__snake_case(					Generic[T]	):


    '''simple docstring'''





    def __init__(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         __A					:					T								=		value
         __A					:					RandomizedHeapNode[T] | None								=		None
         __A					:					RandomizedHeapNode[T] | None								=		None
    @property
    def 						_a							(  self	):




         '''simple docstring'''



         return self._value

    @staticmethod
    def 						_a							(  __lowerCamelCase					,       __lowerCamelCase	):




         '''simple docstring'''



         if not roota:
              return roota

         if not roota:
              return roota

         if roota.value > roota.value:
              __A						,		__A					:					List[str]								=		roota, roota

         if random.choice([True, False]	):
              __A						,		__A					:					Dict								=		roota.right, roota.left

         __A					:					Dict								=		RandomizedHeapNode.merge(roota.left					,       __lowerCamelCase	)

         return roota







class 							__snake_case(					Generic[T]	):


    '''simple docstring'''





    def __init__(  self					,       __lowerCamelCase = ()	):




         '''simple docstring'''



         __A					:					RandomizedHeapNode[T] | None								=		None

         if data:
              for item in data:
                   self.insert(__lowerCamelCase	)
    def 						_a							(  self					,       __lowerCamelCase	):




         '''simple docstring'''



         __A					:					List[str]								=		RandomizedHeapNode.merge(self._root					,       RandomizedHeapNode(__lowerCamelCase	)	)
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					int								=		self.top()

         if self._root is None:
              return None

         __A					:					Dict								=		RandomizedHeapNode.merge(self._root.left					,       self._root.right	)

         return result
    def 						_a							(  self	):




         '''simple docstring'''



         if not self._root:
              raise IndexError('Can\'t get top element for the empty heap.'	)
         return self._root.value
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Dict								=		None
    def 						_a							(  self	):




         '''simple docstring'''



         __A					:					Tuple								=		[]
         while self:
              result.append(self.pop()	)

         return result

    def __bool__(  self	):




         '''simple docstring'''



         return self._root is not None


if __name__ == "__main__":
       import doctest

       doctest.testmod()



