




from collections import deque




def 						SCREAMING_SNAKE_CASE__ (   lowercase					)  ->       List[Any]:
    snake_case				:    int           =	len(lowercase					)
    snake_case				:    int           =	deque()
    snake_case				:    Union[str, Any]           =	[False for _ in range(lowercase					)]
    snake_case				:    Any           =	[-1 for _ in range(lowercase					)]
    snake_case				:    int           =	index_of[:]

    def strong_connect(lowercase						,lowercase						,lowercase					):
        snake_case				:    int           =	index  # the number when this node is seen
        snake_case				:    str           =	index  # lowest rank node reachable from here
        index += 1
        stack.append(lowercase					)
        snake_case				:    Tuple           =	True

        for w in g[v]:
            if index_of[w] == -1:
                snake_case				:    Tuple           =	strong_connect(lowercase						,lowercase						,lowercase					)
                snake_case				:    str           =	(
                    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
                )
            elif on_stack[w]:
                snake_case				:    List[str]           =	(
                    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
                )

        if lowlink_of[v] == index_of[v]:
            snake_case				:    Tuple           =	[]
            snake_case				:    str           =	stack.pop()
            snake_case				:    Optional[int]           =	False
            component.append(lowercase					)
            while w != v:
                snake_case				:    Union[str, Any]           =	stack.pop()
                snake_case				:    str           =	False
                component.append(lowercase					)
            components.append(lowercase					)
        return index

    snake_case				:    str           =	[]
    for v in range(lowercase					):
        if index_of[v] == -1:
            strong_connect(lowercase						,0						,lowercase					)

    return components




def 						SCREAMING_SNAKE_CASE__ (   lowercase						,lowercase					)  ->       List[str]:
    snake_case				:    Tuple           =	[[] for _ in range(lowercase					)]
    for u, v in edges:
        g[u].append(lowercase					)
    return g


if __name__ == "__main__":
       # Test
       lowerCamelCase	:	Dict				=   7
       lowerCamelCase	:	Dict				=   [0, 0, 1, 2, 3, 3, 4, 4, 6]
       lowerCamelCase	:	int				=   [1, 3, 2, 0, 1, 4, 5, 6, 5]
       lowerCamelCase	:	Union[str, Any]				=   [(u, v) for u, v in zip(source, target)]
       lowerCamelCase	:	List[str]				=   create_graph(n_vertices, edges)

       assert [[5], [6], [4], [3, 2, 1, 0]] == tarjan(g)











from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase	:	Optional[int]				=   logging.get_logger(__name__)

lowerCamelCase	:	Tuple				=   {
    'snap-research/efficientformer-l1-300': (
        'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json'
    ),
}




class 						__lowercase		(UpperCamelCase__							):




      """simple docstring"""





      _snake_case												=						"""efficientformer"""

      def __init__(				self    ,				A = [3, 2, 6, 4]    ,				A = [4_8, 9_6, 2_2_4, 4_4_8]    ,				A = [True, True, True, True]    ,				A = 4_4_8    ,				A = 3_2    ,				A = 4    ,				A = 7    ,				A = 5    ,				A = 8    ,				A = 4    ,				A = 0.0    ,				A = 1_6    ,				A = 3    ,				A = 3    ,				A = 3    ,				A = 2    ,				A = 1    ,				A = 0.0    ,				A = 1    ,				A = True    ,				A = True    ,				A = 1e-5    ,				A = "gelu"    ,				A = 0.02    ,				A = 1e-1_2    ,				A = 2_2_4    ,				A = 1e-0_5    ,				**A    ,				)		->    None:
         super().__init__(**A     )

         snake_case				:    Dict           =	hidden_act
         snake_case				:    int           =	hidden_dropout_prob
         snake_case				:    Any           =	hidden_sizes
         snake_case				:    Optional[Any]           =	num_hidden_layers
         snake_case				:    List[Any]           =	num_attention_heads
         snake_case				:    List[Any]           =	initializer_range
         snake_case				:    str           =	layer_norm_eps
         snake_case				:    Dict           =	patch_size
         snake_case				:    Optional[int]           =	num_channels
         snake_case				:    int           =	depths
         snake_case				:    Optional[int]           =	mlp_expansion_ratio
         snake_case				:    Any           =	downsamples
         snake_case				:    Dict           =	dim
         snake_case				:    Optional[int]           =	key_dim
         snake_case				:    Union[str, Any]           =	attention_ratio
         snake_case				:    Any           =	resolution
         snake_case				:    Dict           =	pool_size
         snake_case				:    Any           =	downsample_patch_size
         snake_case				:    Tuple           =	downsample_stride
         snake_case				:    Any           =	downsample_pad
         snake_case				:    Union[str, Any]           =	drop_path_rate
         snake_case				:    List[str]           =	num_metaad_blocks
         snake_case				:    Union[str, Any]           =	distillation
         snake_case				:    List[str]           =	use_layer_scale
         snake_case				:    int           =	layer_scale_init_value
         snake_case				:    Union[str, Any]           =	image_size
         snake_case				:    Dict           =	batch_norm_eps





