




'''simple docstring'''





from random import randint
from tempfile import TemporaryFile

import numpy as np


def 					UpperCamelCase_(     snake_case							:	str							,    snake_case							:	str							,    snake_case							:	Union[str, Any]					):

       '''simple docstring'''






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

              snake_case_ ,				snake_case_      =				_in_place_partition(lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__					)
              count += _in_place_quick_sort(lowerCamelCase__							,    lowerCamelCase__							,    p - 1					)
              count += _in_place_quick_sort(lowerCamelCase__							,    p + 1							,    lowerCamelCase__					)
       return count


def 					UpperCamelCase_(     snake_case							:	int							,    snake_case							:	str							,    snake_case							:	int					):

       '''simple docstring'''






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

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


_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			TemporaryFile()
_SCREAMING_SNAKE_CASE							:       str						=			100  # 1000 elements are to be sorted


_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE							:       List[Any]						=			0, 1  # mean and standard deviation
_SCREAMING_SNAKE_CASE							:       Optional[int]						=			np.random.normal(mu, sigma, p)
np.save(outfile, X)
print("The array is")
print(X)


outfile.seek(0)  # using the same array
_SCREAMING_SNAKE_CASE							:       List[str]						=			np.load(outfile)
_SCREAMING_SNAKE_CASE							:       List[str]						=			len(M) - 1
_SCREAMING_SNAKE_CASE							:       Any						=			_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


_SCREAMING_SNAKE_CASE							:       Any						=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:       int						=			{
    "alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}




class 			_snake_case		(     lowercase_							):
			lowerCAmelCase_					:				Union[str, Any]							=   "mgp-str"




			def __init__( self    ,							a__=[32, 128]    ,							a__=4    ,							a__=3    ,							a__=27    ,							a__=38    ,							a__=50_257    ,							a__=30_522    ,							a__=768    ,							a__=12    ,							a__=12    ,							a__=4.0    ,							a__=True    ,							a__=False    ,							a__=1e-5    ,							a__=0.0    ,							a__=0.0    ,							a__=0.0    ,							a__=False    ,							a__=0.0_2    ,							**a__    ,							)    ->    Union[str, Any]:

										'''simple docstring'''




										super().__init__(**a__							)

										snake_case_      =				image_size
										snake_case_      =				patch_size
										snake_case_      =				num_channels
										snake_case_      =				max_token_length
										snake_case_      =				num_character_labels
										snake_case_      =				num_bpe_labels
										snake_case_      =				num_wordpiece_labels
										snake_case_      =				hidden_size
										snake_case_      =				num_hidden_layers
										snake_case_      =				num_attention_heads
										snake_case_      =				mlp_ratio
										snake_case_      =				distilled
										snake_case_      =				layer_norm_eps
										snake_case_      =				drop_rate
										snake_case_      =				qkv_bias
										snake_case_      =				attn_drop_rate
										snake_case_      =				drop_path_rate
										snake_case_      =				output_aa_attentions
										snake_case_      =				initializer_range




