


from random import randint
from tempfile import TemporaryFile

import numpy as np
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case						)     ->			Dict:







 """simple docstring"""


 _lowercase							      =0
 if start < end:
  _lowercase							      =randint(__snake_case     ,						__snake_case						)
  _lowercase							      =a[end]
  _lowercase							      =a[pivot]
  _lowercase							      =temp

  _lowercase      ,    _lowercase							      =_in_place_partition(__snake_case     ,						__snake_case     ,						__snake_case						)
  count += _in_place_quick_sort(__snake_case     ,						__snake_case     ,						p - 1						)
  count += _in_place_quick_sort(__snake_case     ,						p + 1     ,						__snake_case						)
 return count
def 				UpperCAmelCase_					(							__snake_case     ,						__snake_case     ,						__snake_case						)     ->			Union[str, Any]:







 """simple docstring"""


 _lowercase							      =0
 _lowercase							      =randint(__snake_case     ,						__snake_case						)
 _lowercase							      =a[end]
 _lowercase							      =a[pivot]
 _lowercase							      =temp
 _lowercase							      =start - 1
 for index in range(__snake_case     ,						__snake_case						):
  count += 1
  if a[index] < a[end]:  # check if current val is less than pivot value
   _lowercase							      =new_pivot_index + 1
   _lowercase							      =a[new_pivot_index]
   _lowercase							      =a[index]
   _lowercase							      =temp

 _lowercase							      =a[new_pivot_index + 1]
 _lowercase							      =a[end]
 _lowercase							      =temp
 return new_pivot_index + 1, count


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


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


outfile.seek(0)  # using the same array
UpperCAmelCase__   	=							np.load(outfile)
UpperCAmelCase__   	=							len(M) - 1
UpperCAmelCase__   	=							_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 ...configuration_utils import PretrainedConfig
from ...utils import logging


__a          =		logging.get_logger(__name__)

__a          =		{
    "vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		"glpn"




    def __init__(    self					:     Optional[Any] ,     snake_case_					:     List[str]=3 ,     snake_case_					:     Dict=4 ,     snake_case_					:     List[Any]=[2, 2, 2, 2] ,     snake_case_					:     int=[8, 4, 2, 1] ,     snake_case_					:     List[str]=[32, 64, 160, 256] ,     snake_case_					:     Tuple=[7, 3, 3, 3] ,     snake_case_					:     List[Any]=[4, 2, 2, 2] ,     snake_case_					:     Tuple=[1, 2, 5, 8] ,     snake_case_					:     List[str]=[4, 4, 4, 4] ,     snake_case_					:     Optional[int]="gelu" ,     snake_case_					:     Dict=0.0 ,     snake_case_					:     Union[str, Any]=0.0 ,     snake_case_					:     List[Any]=0.02 ,     snake_case_					:     Tuple=0.1 ,     snake_case_					:     Any=1E-6 ,     snake_case_					:     Dict=64 ,     snake_case_					:     Tuple=10 ,     snake_case_					:     List[Any]=-1 ,     **snake_case_					:     Optional[Any] ,     ):
          super().__init__(**snake_case_						)

          snake_case__  :    Optional[Any]    						=      num_channels
          snake_case__  :    Dict    						=      num_encoder_blocks
          snake_case__  :    Tuple    						=      depths
          snake_case__  :    Union[str, Any]    						=      sr_ratios
          snake_case__  :    Tuple    						=      hidden_sizes
          snake_case__  :    Optional[Any]    						=      patch_sizes
          snake_case__  :    int    						=      strides
          snake_case__  :    List[Any]    						=      mlp_ratios
          snake_case__  :    Optional[int]    						=      num_attention_heads
          snake_case__  :    Dict    						=      hidden_act
          snake_case__  :    int    						=      hidden_dropout_prob
          snake_case__  :    Optional[Any]    						=      attention_probs_dropout_prob
          snake_case__  :    str    						=      initializer_range
          snake_case__  :    List[str]    						=      drop_path_rate
          snake_case__  :    int    						=      layer_norm_eps
          snake_case__  :    Tuple    						=      decoder_hidden_size
          snake_case__  :    List[Any]    						=      max_depth
          snake_case__  :    Dict    						=      head_in_index
