





'''simple docstring'''



# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch

import math
from typing import Union

import torch

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin






class 							__lowercase    ( lowerCAmelCase__	, lowerCAmelCase__  ):







	'''simple docstring'''

	a      :			int     =    1


	@register_to_config
	def __init__(self       ,_lowerCamelCase=2000       ,_lowerCamelCase=0.1       ,_lowerCamelCase=20       ,_lowerCamelCase=1E-3	)							->							List[str]:







				'''simple docstring'''





				__lowercase			  =							None
				__lowercase			  =							None
				__lowercase			  =							None


	def   _UpperCAmelCase       (self       ,_lowerCamelCase       ,_lowerCamelCase = None	)							->							Dict:







				'''simple docstring'''





				__lowercase			  =							torch.linspace(1       ,self.config.sampling_eps       ,_lowerCamelCase       ,device=_lowerCamelCase	)


	def   _UpperCAmelCase       (self       ,_lowerCamelCase       ,_lowerCamelCase       ,_lowerCamelCase       ,_lowerCamelCase=None	)							->							List[Any]:







				'''simple docstring'''





				if self.timesteps is None:
							raise ValueError(
							    '''`self.timesteps` is not set, you need to run \'set_timesteps\' after creating the scheduler'''	)

				# TODO(Patrick) better comments + non-PyTorch
				# postprocess model score
				__lowercase			  =							(
				    -0.2_5 * t**2 * (self.config.beta_max - self.config.beta_min) - 0.5 * t * self.config.beta_min
				)
				__lowercase			  =							torch.sqrt(1.0 - torch.exp(2.0 * log_mean_coeff	)	)
				__lowercase			  =							std.flatten()
				while len(std.shape	) < len(score.shape	):
							__lowercase			  =							std.unsqueeze(-1	)
				__lowercase			  =							-score / std

				# compute
				__lowercase			  =							-1.0 / len(self.timesteps	)

				__lowercase			  =							self.config.beta_min + t * (self.config.beta_max - self.config.beta_min)
				__lowercase			  =							beta_t.flatten()
				while len(beta_t.shape	) < len(x.shape	):
							__lowercase			  =							beta_t.unsqueeze(-1	)
				__lowercase			  =							-0.5 * beta_t * x

				__lowercase			  =							torch.sqrt(_lowerCamelCase	)
				__lowercase			  =							drift - diffusion**2 * score
				__lowercase			  =							x + drift * dt

				# add noise
				__lowercase			  =							randn_tensor(x.shape       ,layout=x.layout       ,generator=_lowerCamelCase       ,device=x.device       ,dtype=x.dtype	)
				__lowercase			  =							x_mean + diffusion * math.sqrt(-dt	) * noise

				return x, x_mean


	def __len__(self	)							->							Optional[int]:







				'''simple docstring'''





				return self.config.num_train_timesteps












'''simple docstring'''



import os
import random
import sys

from . import cryptomath_module as cryptoMath  # noqa: N812
from . import rabin_miller as rabinMiller  # noqa: N812




def 				_lowerCAmelCase  (			):
			print('''Making key files...'''			)
			make_key_files('''rsa'''						,    1_0_2_4			)
			print('''Key files generation successful.'''			)




def 				_lowerCAmelCase  (			lowerCamelCase_     :					int			):
			print('''Generating prime p...'''			)
			__lowercase			  =							rabinMiller.generate_large_prime(lowerCamelCase_			)
			print('''Generating prime q...'''			)
			__lowercase			  =							rabinMiller.generate_large_prime(lowerCamelCase_			)
			__lowercase			  =							p * q

			print('''Generating e that is relatively prime to (p - 1) * (q - 1)...'''			)
			while True:
						__lowercase			  =							random.randrange(2 ** (key_size - 1)						,    2 ** (key_size)			)
						if cryptoMath.gcd(lowerCamelCase_						,    (p - 1) * (q - 1)			) == 1:
									break

			print('''Calculating d that is mod inverse of e...'''			)
			__lowercase			  =							cryptoMath.find_mod_inverse(lowerCamelCase_						,    (p - 1) * (q - 1)			)

			__lowercase			  =							(n, e)
			__lowercase			  =							(n, d)
			return (public_key, private_key)




def 				_lowerCAmelCase  (			lowerCamelCase_     :					str						,    lowerCamelCase_     :					int			):
			if os.path.exists(f"{name}_pubkey.txt"			) or os.path.exists(f"{name}_privkey.txt"			):
						print('''\nWARNING:'''			)
						print(
						    f"\"{name}_pubkey.txt\" or \"{name}_privkey.txt\" already exists. \n"
						    '''Use a different name or delete these files and re-run this program.'''			)
						sys.exit()

			__lowercase  ,						__lowercase			  =							generate_key(lowerCamelCase_			)
			print(f"\nWriting public key to file {name}_pubkey.txt..."			)
			with open(f"{name}_pubkey.txt"						,    '''w'''			) as out_file:
						out_file.write(f"{key_size},{public_key[0]},{public_key[1]}"			)

			print(f"Writing private key to file {name}_privkey.txt..."			)
			with open(f"{name}_privkey.txt"						,    '''w'''			) as out_file:
						out_file.write(f"{key_size},{private_key[0]},{private_key[1]}"			)


if __name__ == "__main__":
	main()





