


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


snake_case							:       Dict										=	logging.get_logger(__name__)

snake_case							:       Optional[Any]										=	{
    '''microsoft/resnet-50''': '''https://huggingface.co/microsoft/resnet-50/blob/main/config.json''',
}







class 						_snake_case    ( _snake_case		,       _snake_case				):
 SCREAMING_SNAKE_CASE__ =			'resnet'
 SCREAMING_SNAKE_CASE__ =			['basic', 'bottleneck']




 def __init__(						self   ,    _lowerCamelCase=3   ,    _lowerCamelCase=64   ,    _lowerCamelCase=[256, 512, 1024, 2048]   ,    _lowerCamelCase=[3, 4, 6, 3]   ,    _lowerCamelCase="bottleneck"   ,    _lowerCamelCase="relu"   ,    _lowerCamelCase=False   ,    _lowerCamelCase=None   ,    _lowerCamelCase=None   ,    **_lowerCamelCase   ,    ):
       super().__init__(**_lowerCamelCase       )
       if layer_type not in self.layer_types:
             raise ValueError(F'''layer_type={layer_type} is not one of {','.join(self.layer_types       )}'''       )
       a		:Any									=			num_channels
       a		:Optional[int]									=			embedding_size
       a		:Optional[int]									=			hidden_sizes
       a		:List[Any]									=			depths
       a		:Dict									=			layer_type
       a		:int									=			hidden_act
       a		:Dict									=			downsample_in_first_stage
       a		:List[Any]									=			['''stem'''] + [F'''stage{idx}''' for idx in range(1   ,    len(_lowerCamelCase       ) + 1       )]
       a				,							a		:str									=			get_aligned_output_features_output_indices(
           out_features=_lowerCamelCase   ,    out_indices=_lowerCamelCase   ,    stage_names=self.stage_names       )







class 						_snake_case    ( _snake_case				):
 SCREAMING_SNAKE_CASE__ =			version.parse('1.11'				)




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       return OrderedDict(
           [
               ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
           ]       )




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       return 1e-3









from __future__ import annotations

from typing import Any







class 						_snake_case    ( _snake_case				):
 pass







class 						_snake_case    :




 def __init__(						self   ,    _lowerCamelCase       ):
       a		:Any									=			data
       a		:Node | None									=			None




 def __iter__(						self       ):
       a		:Dict									=			self
       a		:Optional[int]									=			[]
       while node:
             if node in visited:
                   raise ContainsLoopError
             visited.append(_lowerCamelCase       )
             yield node.data
             a		:str									=			node.next_node




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       try:
             list(self       )
             return False
       except ContainsLoopError:
             return True


if __name__ == "__main__":
     snake_case							:       int										=	Node(1)
     snake_case							:       int										=	Node(2)
     snake_case							:       Optional[int]										=	Node(3)
     snake_case							:       List[str]										=	Node(4)
     print(root_node.has_loop)  # False
     snake_case							:       Optional[Any]										=	root_node.next_node
     print(root_node.has_loop)  # True

     snake_case							:       Dict										=	Node(5)
     snake_case							:       List[Any]										=	Node(6)
     snake_case							:       Optional[int]										=	Node(5)
     snake_case							:       Union[str, Any]										=	Node(6)
     print(root_node.has_loop)  # False

     snake_case							:       Tuple										=	Node(1)
     print(root_node.has_loop)  # False





