





"""simple docstring"""


from random import randint
from tempfile import TemporaryFile

import numpy as np




def 					lowercase__    (					lowercase_		,lowercase_		,lowercase_			)					->		Dict:




						"""simple docstring"""

						_UpperCamelCase      :	List[Any]						=       0
						if start < end:
												_UpperCamelCase      :	Optional[int]						=       randint(lowercase_		,lowercase_			)
												_UpperCamelCase      :	Union[str, Any]						=       a[end]
												_UpperCamelCase      :	Optional[Any]						=       a[pivot]
												_UpperCamelCase      :	Any						=       temp

												_UpperCamelCase      :	List[str]						=       _in_place_partition(lowercase_		,lowercase_		,lowercase_			)
												count += _in_place_quick_sort(lowercase_		,lowercase_		,p - 1			)
												count += _in_place_quick_sort(lowercase_		,p + 1		,lowercase_			)
						return count




def 					lowercase__    (					lowercase_		,lowercase_		,lowercase_			)					->		Dict:




						"""simple docstring"""

						_UpperCamelCase      :	Optional[int]						=       0
						_UpperCamelCase      :	List[Any]						=       randint(lowercase_		,lowercase_			)
						_UpperCamelCase      :	Optional[Any]						=       a[end]
						_UpperCamelCase      :	Any						=       a[pivot]
						_UpperCamelCase      :	Optional[int]						=       temp
						_UpperCamelCase      :	int						=       start - 1
						for index in range(lowercase_		,lowercase_			):
												count += 1
												if a[index] < a[end]:  # check if current val is less than pivot value
																		_UpperCamelCase      :	List[str]						=       new_pivot_index + 1
																		_UpperCamelCase      :	Union[str, Any]						=       a[new_pivot_index]
																		_UpperCamelCase      :	Tuple						=       a[index]
																		_UpperCamelCase      :	Union[str, Any]						=       temp

						_UpperCamelCase      :	List[str]						=       a[new_pivot_index + 1]
						_UpperCamelCase      :	str						=       a[end]
						_UpperCamelCase      :	Any						=       temp
						return new_pivot_index + 1, count


lowerCamelCase__				  =   TemporaryFile()
lowerCamelCase__				  =   100  # 1000 elements are to be sorted


lowerCamelCase__  ,    lowerCamelCase__				  =   0, 1  # mean and standard deviation
lowerCamelCase__				  =   np.random.normal(mu, sigma, p)
np.save(outfile, X)
print("The array is")
print(X)


outfile.seek(0)  # using the same array
lowerCamelCase__				  =   np.load(outfile)
lowerCamelCase__				  =   len(M) - 1
lowerCamelCase__				  =   _in_place_quick_sort(M, 0, r)

print(
    "No of Comparisons for 100 elements selected from a standard normal distribution"
    "is :"
)

print(z)







"""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      __SCREAMING_SNAKE_CASE    (						_UpperCamelCase   ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:Tuple	     =					"yolos"

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

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





class      __SCREAMING_SNAKE_CASE    (						_UpperCamelCase   ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:List[str]	     =					version.parse("1.11"   )

  @property
  def    __SCREAMING_SNAKE_CASE				(		self   :       str	)		->				Mapping[str, Mapping[int, str]]:
        return OrderedDict(
            [
                ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
            ]	)

  @property
  def    __SCREAMING_SNAKE_CASE				(		self   :       Optional[Any]	)		->				float:
        return 1e-4


  @property
  def    __SCREAMING_SNAKE_CASE				(		self   :       Dict	)		->				int:
        return 12
