






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


a		:       int			     = logging.get_logger(__name__)

a		:       Optional[Any]			     = {
    "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     a    ( lowercase__   ):



      """simple docstring"""


      a  : Dict							       =	'yolos'
      def __init__(      self					:			int		,      __lowercase					:			Optional[Any]=768		,      __lowercase					:			List[str]=12		,      __lowercase					:			List[Any]=12		,      __lowercase					:			Optional[Any]=3072		,      __lowercase					:			Any="gelu"		,      __lowercase					:			List[Any]=0.0		,      __lowercase					:			Tuple=0.0		,      __lowercase					:			List[str]=0.02		,      __lowercase					:			Any=1e-1_2		,      __lowercase					:			Optional[Any]=[512, 864]		,      __lowercase					:			str=16		,      __lowercase					:			Optional[Any]=3		,      __lowercase					:			int=True		,      __lowercase					:			Optional[Any]=100		,      __lowercase					:			str=True		,      __lowercase					:			str=False		,      __lowercase					:			Dict=1		,      __lowercase					:			List[str]=5		,      __lowercase					:			Dict=2		,      __lowercase					:			Optional[Any]=5		,      __lowercase					:			int=2		,      __lowercase					:			List[Any]=0.1		,      **__lowercase					:			Optional[int]		,      )							->      Union[str, Any]:
        super().__init__(**__lowercase					)

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


class     a    ( lowercase__   ):



      """simple docstring"""


      a  : Tuple							       =	version.parse('1.11'   )
      @property
      def 	UpperCAmelCase      (      self					:			Optional[int]					)							->      Mapping[str, Mapping[int, str]]:
        return OrderedDict(
            [
                ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
            ]					)
      @property
      def 	UpperCAmelCase      (      self					:			Optional[Any]					)							->      float:
        return 1e-4




      @property
      def 	UpperCAmelCase      (      self					:			str					)							->      int:
        return 12










from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

a		:       Dict			     = typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
a		:       Any			     = typing.Union[np.floataa, int, float]  # noqa: UP007






def 				lowerCamelCase__      (    __lowerCamelCase			:     Vector  ,		__lowerCamelCase			:     Vector		):
  return np.sqrt(np.sum((np.asarray(__lowerCamelCase		) - np.asarray(__lowerCamelCase		)) ** 2		)		)






def 				lowerCamelCase__      (    __lowerCamelCase			:     Vector  ,		__lowerCamelCase			:     Vector		):
  return sum((va - va) ** 2 for va, va in zip(__lowerCamelCase  ,		__lowerCamelCase		)		) ** (1 / 2)


if __name__ == "__main__":






       def 				lowerCamelCase__      (    ):
         from timeit import timeit

         print("""Without Numpy"""		)
         print(
             timeit(
                 """euclidean_distance_no_np([1, 2, 3], [4, 5, 6])"""  ,		number=10000  ,		globals=globals()  ,		)		)
         print("""With Numpy"""		)
         print(
             timeit(
                 """euclidean_distance([1, 2, 3], [4, 5, 6])"""  ,		number=10000  ,		globals=globals()  ,		)		)







       benchmark()


