code: 
  
  
  
  
  
  
  """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
  from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
  
  
  lowercase__      =				logging.get_logger(__name__)
  
  lowercase__      =				{
      """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 	__lowerCamelCase       (				__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE    ):
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  		a_			:       str      =							"""convnext"""
  
  
  
  
  
  		def __init__(     self							:			Dict		,    a_							:			Optional[int]=3		,    a_							:			List[str]=4		,    a_							:			List[Any]=4		,    a_							:			str=None		,    a_							:			Optional[int]=None		,    a_							:			Tuple="gelu"		,    a_							:			List[Any]=0.02		,    a_							:			Tuple=1e-1_2		,    a_							:			Tuple=1e-6		,    a_							:			int=0.0		,    a_							:			Optional[Any]=2_24		,    a_							:			Union[str, Any]=None		,    a_							:			int=None		,    **a_							:			List[Any]		,    ):
  				super().__init__(**UpperCamelCase__			)
  
  				lowerCAmelCase_     :							Union[str, Any]             =    num_channels
  				lowerCAmelCase_     :							Any             =    patch_size
  				lowerCAmelCase_     :							Any             =    num_stages
  				lowerCAmelCase_     :							int             =    [96, 1_92, 3_84, 7_68] if hidden_sizes is None else hidden_sizes
  				lowerCAmelCase_     :							Optional[Any]             =    [3, 3, 9, 3] if depths is None else depths
  				lowerCAmelCase_     :							int             =    hidden_act
  				lowerCAmelCase_     :							Tuple             =    initializer_range
  				lowerCAmelCase_     :							str             =    layer_norm_eps
  				lowerCAmelCase_     :							List[Any]             =    layer_scale_init_value
  				lowerCAmelCase_     :							str             =    drop_path_rate
  				lowerCAmelCase_     :							Optional[Any]             =    image_size
  				lowerCAmelCase_     :							Optional[int]             =    ['''stem'''] + [f'''stage{idx}''' for idx in range(1		,    len(self.depths			) + 1			)]
  				lowerCAmelCase_     :							List[str]             =    get_aligned_output_features_output_indices(
  				    out_features=UpperCamelCase__		,    out_indices=UpperCamelCase__		,    stage_names=self.stage_names			)
  
  
  
  
  
  
  
  class 	__lowerCamelCase       (				__SCREAMING_SNAKE_CASE    ):
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  		a_			:       Optional[int]      =							version.parse("""1.11"""    )
  
  
  
  
  
  		@property
  		def      lowerCamelCase (     self							:			Union[str, Any]			):
  				return OrderedDict(
  				    [
  				        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
  				    ]			)
  
  
  
  
  
  		@property
  		def      lowerCamelCase (     self							:			Optional[int]			):
  				return 1e-5
  
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  
  from __future__ import annotations
  
  import random
  
  # Adjacency list representation of this graph:
  # https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
  lowercase__      =				{
      """1""": ["""2""", """3""", """4""", """5"""],
      """2""": ["""1""", """3""", """4""", """5"""],
      """3""": ["""1""", """2""", """4""", """5""", """10"""],
      """4""": ["""1""", """2""", """3""", """5""", """6"""],
      """5""": ["""1""", """2""", """3""", """4""", """7"""],
      """6""": ["""7""", """8""", """9""", """10""", """4"""],
      """7""": ["""6""", """8""", """9""", """10""", """5"""],
      """8""": ["""6""", """7""", """9""", """10"""],
      """9""": ["""6""", """7""", """8""", """10"""],
      """10""": ["""6""", """7""", """8""", """9""", """3"""],
  }
  
  def 	__lowerCamelCase			(						__UpperCamelCase )		->					set[tuple[str, str]]:
  
  		"""simple docstring"""
  
  
  
  
  
  
  
  		lowerCAmelCase_     :							Union[str, Any]             =    {node: {node} for node in graph}
  
  		lowerCAmelCase_     :							List[str]             =    {node: graph[node][:] for node in graph}
  
  		while len(__UpperCamelCase ) > 2:
  				# Choose a random edge.
  				lowerCAmelCase_     :							int             =    random.choice(list(graph_copy.keys() ) )
  				lowerCAmelCase_     :							Any             =    random.choice(graph_copy[u] )
  
  				# Contract edge (u, v) to new node uv
  				lowerCAmelCase_     :							Union[str, Any]             =    u + v
  				lowerCAmelCase_     :							List[Any]             =    list(set(graph_copy[u] + graph_copy[v] ) )
  				uv_neighbors.remove(__UpperCamelCase )
  				uv_neighbors.remove(__UpperCamelCase )
  				lowerCAmelCase_     :							str             =    uv_neighbors
  				for neighbor in uv_neighbors:
  						graph_copy[neighbor].append(__UpperCamelCase )
  
  				lowerCAmelCase_     :							Optional[int]             =    set(contracted_nodes[u].union(contracted_nodes[v] ) )
  
  				# Remove nodes u and v.
  				del graph_copy[u]
  				del graph_copy[v]
  				for neighbor in uv_neighbors:
  						if u in graph_copy[neighbor]:
  								graph_copy[neighbor].remove(__UpperCamelCase )
  						if v in graph_copy[neighbor]:
  								graph_copy[neighbor].remove(__UpperCamelCase )
  
      # Find cutset.
  		lowerCAmelCase_     :							Union[str, Any]             =    [contracted_nodes[node] for node in graph_copy]
  		return {
  		    (node, neighbor)
  		    for node in groups[0]
  		    for neighbor in graph[node]
  		    if neighbor in groups[1]
  		}
  
  
  if __name__ == "__main__":
  					print(partition_graph(TEST_GRAPH))
  