



"""simple docstring"""
import torch
from torch import autograd
class 							lowerCamelCase    (     autograd.Function							):






					'''simple docstring'''





					@staticmethod
					def   lowerCAmelCase_							(			snake_case:				Dict		,	snake_case:				torch.tensor		,	snake_case:				float		,	snake_case:				bool		)  ->      Union[str, Any]:
											snake_case_					:Union[str, Any]		=     inputs.numel()
											snake_case_					:Tuple		=     int(0.0_0_5 * nb_elems		) + 1
											if sigmoid:
																	snake_case_					:List[str]		=     (torch.sigmoid(snake_case		) > threshold).type(inputs.type()		)
											else:
																	snake_case_					:Dict		=     (inputs > threshold).type(inputs.type()		)
											if mask.sum() < nb_min:
																	# We limit the pruning so that at least 0.5% (half a percent) of the weights are remaining
																	snake_case_					:Optional[int]		=     inputs.flatten().kthvalue(max(nb_elems - nb_min		,	1		)		).values
																	snake_case_					:List[str]		=     (inputs > k_threshold).type(inputs.type()		)
											return mask






					@staticmethod
					def   lowerCAmelCase_							(			snake_case:				Optional[int]		,	snake_case:				Union[str, Any]		)  ->      Any:
											return gradOutput, None, None

class 							lowerCamelCase    (     autograd.Function							):






					'''simple docstring'''





					@staticmethod
					def   lowerCAmelCase_							(			snake_case:				int		,	snake_case:				torch.tensor		,	snake_case:				float		)  ->      str:
											snake_case_					:Tuple		=     inputs.clone()
											snake_case_,			snake_case_					:Optional[Any]		=     inputs.flatten().sort(descending=snake_case		)
											snake_case_					:Dict		=     int(threshold * inputs.numel()		)

											# flat_out and mask access the same memory.
											snake_case_					:str		=     mask.flatten()
											snake_case_					:Tuple		=     0
											snake_case_					:Dict		=     1
											return mask






					@staticmethod
					def   lowerCAmelCase_							(			snake_case:				Optional[int]		,	snake_case:				Union[str, Any]		)  ->      int:
											return gradOutput, None

class 							lowerCamelCase    (     _lowerCAmelCase							):






					'''simple docstring'''





					@staticmethod
					def   lowerCAmelCase_							(			snake_case:				torch.tensor		,	snake_case:				float		)  ->      int:
											snake_case_					:Dict		=     inputs.clone()
											snake_case_,			snake_case_					:List[str]		=     inputs.abs().flatten().sort(descending=snake_case		)
											snake_case_					:str		=     int(threshold * inputs.numel()		)

											# flat_out and mask access the same memory.
											snake_case_					:Tuple		=     mask.flatten()
											snake_case_					:Tuple		=     0
											snake_case_					:Optional[Any]		=     1
											return mask






import requests

try:
							from django.contrib.auth import authenticate, login
							from django.shortcuts import redirect, render
except ImportError:
							UpperCamelCase__						=		UpperCamelCase__						=		UpperCamelCase__						=		UpperCamelCase__						=		print






def    snake_case   (				A     )				->				List[str]:




	'''simple docstring'''


	lowerCamelCase_				:						Optional[int]				  =				'secretKey'
	lowerCamelCase_				:						str				  =				'https://www.google.com/recaptcha/api/siteverify'

	# when method is not POST, direct user to login page
	if request.method != "POST":
		return render(A		,  'login.html'     )

	# from the frontend, get username, password, and client_key
	lowerCamelCase_				:						int				  =				request.POST.get('username'     )
	lowerCamelCase_				:						str				  =				request.POST.get('password'     )
	lowerCamelCase_				:						List[Any]				  =				request.POST.get('g-recaptcha-response'     )

	# post recaptcha response to Google's recaptcha api
	lowerCamelCase_				:						Union[str, Any]				  =				requests.post(A		,  data={'secret': secret_key, 'response': client_key}     )
	# if the recaptcha api verified our keys
	if response.json().get('success'		,  A     ):
		# authenticate the user
		lowerCamelCase_				:						int				  =				authenticate(A		,  username=A		,  password=A     )
		if user_in_database:
			login(A		,  A     )
			return redirect('/your-webpage'     )
	return render(A		,  'login.html'     )
