


'''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


lowerCamelCase__    	=     logging.get_logger(__name__)

lowerCamelCase__    	=     {
    'hustvl/yolos-small': 'https://huggingface.co/hustvl/yolos-small/resolve/main/config.json',
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}






class 	lowerCAmelCase__			(			__lowerCamelCase	):
			lowerCAmelCase :	Dict          =     '''yolos'''




			def __init__(		self  :     Dict	,  lowerCamelCase__  :     List[str]=7_68	,  lowerCamelCase__  :     Optional[Any]=12	,  lowerCamelCase__  :     Optional[int]=12	,  lowerCamelCase__  :     Any=30_72	,  lowerCamelCase__  :     List[Any]="gelu"	,  lowerCamelCase__  :     Optional[int]=0.0	,  lowerCamelCase__  :     List[Any]=0.0	,  lowerCamelCase__  :     Optional[int]=0.0_2	,  lowerCamelCase__  :     List[str]=1E-12	,  lowerCamelCase__  :     str=[5_12, 8_64]	,  lowerCamelCase__  :     List[Any]=16	,  lowerCamelCase__  :     int=3	,  lowerCamelCase__  :     List[Any]=True	,  lowerCamelCase__  :     List[str]=1_00	,  lowerCamelCase__  :     Optional[int]=True	,  lowerCamelCase__  :     Any=False	,  lowerCamelCase__  :     Any=1	,  lowerCamelCase__  :     Tuple=5	,  lowerCamelCase__  :     Tuple=2	,  lowerCamelCase__  :     Any=5	,  lowerCamelCase__  :     Optional[int]=2	,  lowerCamelCase__  :     Any=0.1	,  **lowerCamelCase__  :     Optional[Any]	,  )   ->Optional[Any]:



					'''simple docstring'''







					super().__init__(**a_ )

					_UpperCAmelCase		:       Optional[Any]								=      hidden_size
					_UpperCAmelCase		:       Optional[int]								=      num_hidden_layers
					_UpperCAmelCase		:       List[str]								=      num_attention_heads
					_UpperCAmelCase		:       Any								=      intermediate_size
					_UpperCAmelCase		:       int								=      hidden_act
					_UpperCAmelCase		:       Dict								=      hidden_dropout_prob
					_UpperCAmelCase		:       Tuple								=      attention_probs_dropout_prob
					_UpperCAmelCase		:       Dict								=      initializer_range
					_UpperCAmelCase		:       Optional[Any]								=      layer_norm_eps
					_UpperCAmelCase		:       Optional[Any]								=      image_size
					_UpperCAmelCase		:       Dict								=      patch_size
					_UpperCAmelCase		:       List[Any]								=      num_channels
					_UpperCAmelCase		:       Any								=      qkv_bias
					_UpperCAmelCase		:       str								=      num_detection_tokens
					_UpperCAmelCase		:       int								=      use_mid_position_embeddings
					_UpperCAmelCase		:       int								=      auxiliary_loss
					# Hungarian matcher
					_UpperCAmelCase		:       Optional[int]								=      class_cost
					_UpperCAmelCase		:       Optional[Any]								=      bbox_cost
					_UpperCAmelCase		:       Union[str, Any]								=      giou_cost
					# Loss coefficients
					_UpperCAmelCase		:       Optional[int]								=      bbox_loss_coefficient
					_UpperCAmelCase		:       Tuple								=      giou_loss_coefficient
					_UpperCAmelCase		:       Optional[int]								=      eos_coefficient






class 	lowerCAmelCase__			(			__lowerCamelCase	):
			lowerCAmelCase :	Dict          =     version.parse("1.11"	)




			@property
			def 							lowerCAmelCase__    (		self  :     str )   ->Union[str, Any]:



					'''simple docstring'''







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




			@property
			def 							lowerCAmelCase__    (		self  :     Union[str, Any] )   ->Any:



					'''simple docstring'''







					return 1E-4






			@property
			def 							lowerCAmelCase__    (		self  :     Tuple )   ->List[Any]:



					'''simple docstring'''







					return 12







'''simple docstring'''


from __future__ import annotations

import numpy as np






def  __lowerCAmelCase (__lowerCAmelCase   ):
		return np.maximum(0      , __lowerCAmelCase   )


if __name__ == "__main__":
						print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]



