
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  =	logging.get_logger(__name__)

_A  =	{
    "microsoft/beit-base-patch16-224-pt22k": (
        "https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}





class       _lowerCAmelCase   (      __lowercase			):
				_lowercase     						="beit"




				def __init__(   self							,							_UpperCamelCase=8_192							,							_UpperCamelCase=768							,							_UpperCamelCase=12							,							_UpperCamelCase=12							,							_UpperCamelCase=3_072							,							_UpperCamelCase="gelu"							,							_UpperCamelCase=0.0							,							_UpperCamelCase=0.0							,							_UpperCamelCase=0.02							,							_UpperCamelCase=1e-1_2							,							_UpperCamelCase=224							,							_UpperCamelCase=16							,							_UpperCamelCase=3							,							_UpperCamelCase=False							,							_UpperCamelCase=False							,							_UpperCamelCase=False							,							_UpperCamelCase=False							,							_UpperCamelCase=0.1							,							_UpperCamelCase=0.1							,							_UpperCamelCase=True							,							_UpperCamelCase=[3, 5, 7, 11]							,							_UpperCamelCase=[1, 2, 3, 6]							,							_UpperCamelCase=True							,							_UpperCamelCase=0.4							,							_UpperCamelCase=256							,							_UpperCamelCase=1							,							_UpperCamelCase=False							,							_UpperCamelCase=255							,							**_UpperCamelCase							,							)							-> Tuple:
							super().__init__(**_a	)

							lowerCAmelCase_         =      vocab_size
							lowerCAmelCase_         =      hidden_size
							lowerCAmelCase_         =      num_hidden_layers
							lowerCAmelCase_         =      num_attention_heads
							lowerCAmelCase_         =      intermediate_size
							lowerCAmelCase_         =      hidden_act
							lowerCAmelCase_         =      hidden_dropout_prob
							lowerCAmelCase_         =      attention_probs_dropout_prob
							lowerCAmelCase_         =      initializer_range
							lowerCAmelCase_         =      layer_norm_eps

							lowerCAmelCase_         =      image_size
							lowerCAmelCase_         =      patch_size
							lowerCAmelCase_         =      num_channels
							lowerCAmelCase_         =      use_mask_token
							lowerCAmelCase_         =      use_absolute_position_embeddings
							lowerCAmelCase_         =      use_relative_position_bias
							lowerCAmelCase_         =      use_shared_relative_position_bias
							lowerCAmelCase_         =      layer_scale_init_value
							lowerCAmelCase_         =      drop_path_rate
							lowerCAmelCase_         =      use_mean_pooling
							# decode head attributes (semantic segmentation)
							lowerCAmelCase_         =      out_indices
							lowerCAmelCase_         =      pool_scales
							# auxiliary head attributes (semantic segmentation)
							lowerCAmelCase_         =      use_auxiliary_head
							lowerCAmelCase_         =      auxiliary_loss_weight
							lowerCAmelCase_         =      auxiliary_channels
							lowerCAmelCase_         =      auxiliary_num_convs
							lowerCAmelCase_         =      auxiliary_concat_input
							lowerCAmelCase_         =      semantic_loss_ignore_index





class       _lowerCAmelCase   (      __lowercase			):
				_lowercase     						=version.parse('''1.11'''			)




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




				@property
				def 	__a		(   self	)							-> float:
							return 1e-4






from random import randint
from tempfile import TemporaryFile

import numpy as np



def   __UpperCAmelCase					(      __a :     Optional[Any]						,__a :     int						,__a :     Any      )     ->	int:

					"""simple docstring"""

					_a      :       int   =						0
					if start < end:
										_a      :       Tuple   =						randint(__a						,__a      )
										_a      :       Tuple   =						a[end]
										_a      :       List[str]   =						a[pivot]
										_a      :       Any   =						temp

										_a ,   _a      :       Optional[int]   =						_in_place_partition(__a						,__a						,__a      )
										count += _in_place_quick_sort(__a						,__a						,p - 1      )
										count += _in_place_quick_sort(__a						,p + 1						,__a      )
					return count



def   __UpperCAmelCase					(      __a :     List[Any]						,__a :     Tuple						,__a :     Dict      )     ->	Dict:

					"""simple docstring"""

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

					_a      :       Union[str, Any]   =						a[new_pivot_index + 1]
					_a      :       Tuple   =						a[end]
					_a      :       Any   =						temp
					return new_pivot_index + 1, count


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


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


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

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







print(z)



