




import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)







class     A(		unittest.TestCase  ):



 '''simple docstring'''


 def 							a__					(							self   :    List[str]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 2, 3]    )
       self.assertEqual(x.component(0    )		,				1    )
       self.assertEqual(x.component(2    )		,				3    )
       lowerCamelCase_							=       Vector()

 def 							a__					(							self   :    Optional[Any]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([0, 0, 0, 0, 0, 1]    )
       self.assertEqual(str(a_    )		,				'(0,0,0,0,0,1)'    )

 def 							a__					(							self   :    Optional[Any]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 2, 3, 4]    )
       self.assertEqual(len(a_    )		,				4    )

 def 							a__					(							self   :    int    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 2]    )
       lowerCamelCase_							=       Vector([1, 2, 3, 4, 5]    )
       lowerCamelCase_							=       Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]    )
       lowerCamelCase_							=       Vector([1, -1, 1, -1, 2, -3, 4, -5]    )
       self.assertAlmostEqual(x.euclidean_length()		,				2.236		,				3    )
       self.assertAlmostEqual(y.euclidean_length()		,				7.416		,				3    )
       self.assertEqual(z.euclidean_length()		,				0    )
       self.assertAlmostEqual(w.euclidean_length()		,				7.616		,				3    )

 def 							a__					(							self   :    Any    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 2, 3]    )
       lowerCamelCase_							=       Vector([1, 1, 1]    )
       self.assertEqual((x + y).component(0    )		,				2    )
       self.assertEqual((x + y).component(1    )		,				3    )
       self.assertEqual((x + y).component(2    )		,				4    )

 def 							a__					(							self   :    int    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 2, 3]    )
       lowerCamelCase_							=       Vector([1, 1, 1]    )
       self.assertEqual((x - y).component(0    )		,				0    )
       self.assertEqual((x - y).component(1    )		,				1    )
       self.assertEqual((x - y).component(2    )		,				2    )

 def 							a__					(							self   :    List[Any]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 2, 3]    )
       lowerCamelCase_							=       Vector([2, -1, 4]    )  # for test of dot product
       lowerCamelCase_							=       Vector([1, -2, -1]    )
       self.assertEqual(str(x * 3.0    )		,				'(3.0,6.0,9.0)'    )
       self.assertEqual((a * b)		,				0    )

 def 							a__					(							self   :    List[Any]    )  ->      None:

       """simple docstring"""






       self.assertEqual(str(zero_vector(10    )    ).count('0'    )		,				10    )

 def 							a__					(							self   :    List[Any]    )  ->      None:

       """simple docstring"""






       self.assertEqual(str(unit_basis_vector(3		,				1    )    )		,				'(0,1,0)'    )

 def 							a__					(							self   :    Dict    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 2, 3]    )
       lowerCamelCase_							=       Vector([1, 0, 1]    )
       self.assertEqual(str(axpy(2		,				a_		,				a_    )    )		,				'(3,4,7)'    )

 def 							a__					(							self   :    str    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 0, 0, 0, 0, 0]    )
       lowerCamelCase_							=       x.copy()
       self.assertEqual(str(a_    )		,				str(a_    )    )

 def 							a__					(							self   :    Any    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Vector([1, 0, 0]    )
       x.change_component(0		,				0    )
       x.change_component(1		,				1    )
       self.assertEqual(str(a_    )		,				'(0,1,0)'    )

 def 							a__					(							self   :    List[str]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       self.assertEqual('|1,2,3|\n|2,4,5|\n|6,7,8|\n'		,				str(a_    )    )

 def 							a__					(							self   :    List[str]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       lowerCamelCase_							=       [[-3, -14, -10], [-5, -10, -5], [-2, -1, 0]]
       for x in range(a.height()    ):
             for y in range(a.width()    ):
                   self.assertEqual(minors[x][y]		,				a.minor(a_		,				a_    )    )

 def 							a__					(							self   :    Tuple    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       lowerCamelCase_							=       [[-3, 14, -10], [5, -10, 5], [-2, 1, 0]]
       for x in range(a.height()    ):
             for y in range(a.width()    ):
                   self.assertEqual(cofactors[x][y]		,				a.cofactor(a_		,				a_    )    )

 def 							a__					(							self   :    Any    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       self.assertEqual(-5		,				a.determinant()    )

 def 							a__					(							self   :    int    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]		,				3		,				3    )
       lowerCamelCase_							=       Vector([1, 2, 3]    )
       self.assertEqual('(14,32,50)'		,				str(a * x    )    )
       self.assertEqual('|2,4,6|\n|8,10,12|\n|14,16,18|\n'		,				str(a * 2    )    )

 def 							a__					(							self   :    str    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       a.change_component(0		,				2		,				5    )
       self.assertEqual('|1,2,5|\n|2,4,5|\n|6,7,8|\n'		,				str(a_    )    )

 def 							a__					(							self   :    Optional[Any]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       self.assertEqual(7		,				a.component(2		,				1    )		,				0.01    )

 def 							a__					(							self   :    Optional[Any]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       lowerCamelCase_							=       Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]		,				3		,				3    )
       self.assertEqual('|2,4,10|\n|4,8,10|\n|12,14,18|\n'		,				str(a + b    )    )

 def 							a__					(							self   :    Optional[int]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,				3		,				3    )
       lowerCamelCase_							=       Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]		,				3		,				3    )
       self.assertEqual('|0,0,-4|\n|0,0,0|\n|0,0,-2|\n'		,				str(a - b    )    )





 def 							a__					(							self   :    Tuple    )  ->      None:

       """simple docstring"""






       self.assertEqual(
           '|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n'		,				str(square_zero_matrix(5    )    )		,				)


if __name__ == "__main__":
 unittest.main()










"""simple docstring"""






import unittest

import torch

from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow


__UpperCAmelCase						=			False



class 					__UpperCAmelCase							(						unittest.TestCase  ):
				def       UpperCAmelCase      (		self    :			Tuple	, a_    :			Optional[Any]=32    )	->	Union[str, Any]:



							'''simple docstring'''



							set_seed(0    )
							a__  :	Any		 =			UNetaDModel(sample_size=a_	, in_channels=3	, out_channels=3    )
							a__  :	Union[str, Any]		 =			torch.optim.SGD(model.parameters()	, lr=0.0001    )
							return model, optimizer






				@slow
				def       UpperCAmelCase      (		self    :			Union[str, Any]    )	->	Any:



							'''simple docstring'''



							a__  :	Optional[Any]		 =			"cpu"  # ensure full determinism without setting the CUBLAS_WORKSPACE_CONFIG env variable
							a__  :	Dict		 =			DDPMScheduler(
							    num_train_timesteps=10_00	, beta_start=0.0001	, beta_end=0.02	, beta_schedule="linear"	, clip_sample=a_	, )
							a__  :	Optional[Any]		 =			DDIMScheduler(
							    num_train_timesteps=10_00	, beta_start=0.0001	, beta_end=0.02	, beta_schedule="linear"	, clip_sample=a_	, )

							assert ddpm_scheduler.config.num_train_timesteps == ddim_scheduler.config.num_train_timesteps

							# shared batches for DDPM and DDIM
							set_seed(0    )
							a__  :	List[str]		 =			[torch.randn((4, 3, 32, 32)    ).clip(-1	, 1    ).to(a_    ) for _ in range(4    )]
							a__  :	List[str]		 =			[torch.randn((4, 3, 32, 32)    ).to(a_    ) for _ in range(4    )]
							a__  :	Optional[Any]		 =			[torch.randint(0	, 10_00	, (4,)    ).long().to(a_    ) for _ in range(4    )]

							# train with a DDPM scheduler
							a__ ,	a__  :	Union[str, Any]		 =			self.get_model_optimizer(resolution=32    )
							model.train().to(a_    )
							for i in range(4    ):
										optimizer.zero_grad()
										a__  :	Optional[int]		 =			ddpm_scheduler.add_noise(clean_images[i]	, noise[i]	, timesteps[i]    )
										a__  :	List[str]		 =			model(a_	, timesteps[i]    ).sample
										a__  :	Optional[int]		 =			torch.nn.functional.mse_loss(a_	, noise[i]    )
										loss.backward()
										optimizer.step()
							del model, optimizer

							# recreate the model and optimizer, and retry with DDIM
							a__ ,	a__  :	Optional[Any]		 =			self.get_model_optimizer(resolution=32    )
							model.train().to(a_    )
							for i in range(4    ):
										optimizer.zero_grad()
										a__  :	List[str]		 =			ddim_scheduler.add_noise(clean_images[i]	, noise[i]	, timesteps[i]    )
										a__  :	Optional[int]		 =			model(a_	, timesteps[i]    ).sample
										a__  :	Union[str, Any]		 =			torch.nn.functional.mse_loss(a_	, noise[i]    )
										loss.backward()
										optimizer.step()
							del model, optimizer

							self.assertTrue(torch.allclose(a_	, a_	, atol=1E-5    )    )
							self.assertTrue(torch.allclose(a_	, a_	, atol=1E-5    )    )