


"""simple docstring"""







import unittest

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


class 				SCREAMING_SNAKE_CASE__    (		unittest.TestCase    ):
       """simple docstring"""


       def 	lowercase__							(						self						):






         """simple docstring"""





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

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[Any]								=							Vector([0, 0, 0, 0, 0, 1]						)
         self.assertEqual(str(snake_case__						)		,					"(0,0,0,0,0,1)"						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[Any]								=							Vector([1, 2, 3, 4]						)
         self.assertEqual(len(snake_case__						)		,					4						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							Vector([1, 2]						)
         lowerCAmelCase					:					str								=							Vector([1, 2, 3, 4, 5]						)
         lowerCAmelCase					:					Any								=							Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]						)
         lowerCAmelCase					:					Tuple								=							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 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							Vector([1, 2, 3]						)
         lowerCAmelCase					:					str								=							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 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[int]								=							Vector([1, 2, 3]						)
         lowerCAmelCase					:					Tuple								=							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 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[Any]								=							Vector([1, 2, 3]						)
         lowerCAmelCase					:					Optional[int]								=							Vector([2, -1, 4]						)  # for test of dot product
         lowerCAmelCase					:					Any								=							Vector([1, -2, -1]						)
         self.assertEqual(str(x * 3.0						)		,					"(3.0,6.0,9.0)"						)
         self.assertEqual((a * b)		,					0						)

       def 	lowercase__							(						self						):






         """simple docstring"""





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

       def 	lowercase__							(						self						):






         """simple docstring"""





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

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[Any]								=							Vector([1, 2, 3]						)
         lowerCAmelCase					:					Union[str, Any]								=							Vector([1, 0, 1]						)
         self.assertEqual(str(axpy(2		,					snake_case__		,					snake_case__						)						)		,					"(3,4,7)"						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Tuple								=							Vector([1, 0, 0, 0, 0, 0]						)
         lowerCAmelCase					:					Union[str, Any]								=							x.copy()
         self.assertEqual(str(snake_case__						)		,					str(snake_case__						)						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[Any]								=							Vector([1, 0, 0]						)
         x.change_component(0		,					0						)
         x.change_component(1		,					1						)
         self.assertEqual(str(snake_case__						)		,					"(0,1,0)"						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Union[str, Any]								=							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(snake_case__						)						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Any								=							Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,					3		,					3						)
         lowerCAmelCase					:					str								=							[[-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(snake_case__		,					snake_case__						)						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,					3		,					3						)
         lowerCAmelCase					:					List[Any]								=							[[-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(snake_case__		,					snake_case__						)						)

       def 	lowercase__							(						self						):






         """simple docstring"""





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

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Dict								=							Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]		,					3		,					3						)
         lowerCAmelCase					:					int								=							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 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Any								=							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(snake_case__						)						)

       def 	lowercase__							(						self						):






         """simple docstring"""





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

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Any								=							Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,					3		,					3						)
         lowerCAmelCase					:					int								=							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 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Any								=							Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,					3		,					3						)
         lowerCAmelCase					:					Dict								=							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 	lowercase__							(						self						):






         """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 tempfile

import torch

from diffusers import (
    DEISMultistepScheduler,
    DPMSolverMultistepScheduler,
    DPMSolverSinglestepScheduler,
    UniPCMultistepScheduler,
)

from .test_schedulers import SchedulerCommonTest


class 				SCREAMING_SNAKE_CASE__    (		lowercase    ):
       """simple docstring"""


       a  :    Optional[int]       =(DEISMultistepScheduler,)
       a  :    str       =(("num_inference_steps", 25),)

       def 	lowercase__							(						self		,					**snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					Tuple								=							{
             "num_train_timesteps": 1_000,
             "beta_start": 0.0001,
             "beta_end": 0.02,
             "beta_schedule": "linear",
             "solver_order": 2,
         }

         config.update(**snake_case__						)
         return config

       def 	lowercase__							(						self		,					snake_case__=0		,					**snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							dict(self.forward_default_kwargs						)
         lowerCAmelCase					:					List[str]								=							kwargs.pop("num_inference_steps"		,					snake_case__						)
         lowerCAmelCase					:					List[str]								=							self.dummy_sample
         lowerCAmelCase					:					int								=							0.1 * sample
         lowerCAmelCase					:					Tuple								=							[residual + 0.2, residual + 0.15, residual + 0.10]

         for scheduler_class in self.scheduler_classes:
           lowerCAmelCase					:					Any								=							self.get_scheduler_config(**snake_case__						)
           lowerCAmelCase					:					List[str]								=							scheduler_class(**snake_case__						)
           scheduler.set_timesteps(snake_case__						)
           # copy over dummy past residuals
           lowerCAmelCase					:					str								=							dummy_past_residuals[: scheduler.config.solver_order]

           with tempfile.TemporaryDirectory() as tmpdirname:
             scheduler.save_config(snake_case__						)
             lowerCAmelCase					:					List[str]								=							scheduler_class.from_pretrained(snake_case__						)
             new_scheduler.set_timesteps(snake_case__						)
             # copy over dummy past residuals
             lowerCAmelCase					:					Optional[int]								=							dummy_past_residuals[: new_scheduler.config.solver_order]

           lowerCAmelCase						,  lowerCAmelCase					:					Union[str, Any]								=							sample, sample
           for t in range(snake_case__		,					time_step + scheduler.config.solver_order + 1						):
             lowerCAmelCase					:					Any								=							scheduler.step(snake_case__		,					snake_case__		,					snake_case__		,					**snake_case__						).prev_sample
             lowerCAmelCase					:					str								=							new_scheduler.step(snake_case__		,					snake_case__		,					snake_case__		,					**snake_case__						).prev_sample

             assert torch.sum(torch.abs(output - new_output						)						) < 1e-5, "Scheduler outputs are not identical"

       def 	lowercase__							(						self						):






         """simple docstring"""





         pass

       def 	lowercase__							(						self		,					snake_case__=0		,					**snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					Dict								=							dict(self.forward_default_kwargs						)
         lowerCAmelCase					:					List[str]								=							kwargs.pop("num_inference_steps"		,					snake_case__						)
         lowerCAmelCase					:					List[str]								=							self.dummy_sample
         lowerCAmelCase					:					Optional[int]								=							0.1 * sample
         lowerCAmelCase					:					List[Any]								=							[residual + 0.2, residual + 0.15, residual + 0.10]

         for scheduler_class in self.scheduler_classes:
           lowerCAmelCase					:					int								=							self.get_scheduler_config()
           lowerCAmelCase					:					Any								=							scheduler_class(**snake_case__						)
           scheduler.set_timesteps(snake_case__						)

           # copy over dummy past residuals (must be after setting timesteps)
           lowerCAmelCase					:					Union[str, Any]								=							dummy_past_residuals[: scheduler.config.solver_order]

           with tempfile.TemporaryDirectory() as tmpdirname:
             scheduler.save_config(snake_case__						)
             lowerCAmelCase					:					Any								=							scheduler_class.from_pretrained(snake_case__						)
             # copy over dummy past residuals
             new_scheduler.set_timesteps(snake_case__						)

             # copy over dummy past residual (must be after setting timesteps)
             lowerCAmelCase					:					Optional[int]								=							dummy_past_residuals[: new_scheduler.config.solver_order]

           lowerCAmelCase					:					Union[str, Any]								=							scheduler.step(snake_case__		,					snake_case__		,					snake_case__		,					**snake_case__						).prev_sample
           lowerCAmelCase					:					int								=							new_scheduler.step(snake_case__		,					snake_case__		,					snake_case__		,					**snake_case__						).prev_sample

           assert torch.sum(torch.abs(output - new_output						)						) < 1e-5, "Scheduler outputs are not identical"

       def 	lowercase__							(						self		,					snake_case__=None		,					**snake_case__						):






         """simple docstring"""





         if scheduler is None:
           lowerCAmelCase					:					List[str]								=							self.scheduler_classes[0]
           lowerCAmelCase					:					Optional[int]								=							self.get_scheduler_config(**snake_case__						)
           lowerCAmelCase					:					Any								=							scheduler_class(**snake_case__						)

         lowerCAmelCase					:					List[str]								=							self.scheduler_classes[0]
         lowerCAmelCase					:					Tuple								=							self.get_scheduler_config(**snake_case__						)
         lowerCAmelCase					:					List[str]								=							scheduler_class(**snake_case__						)

         lowerCAmelCase					:					int								=							10
         lowerCAmelCase					:					List[str]								=							self.dummy_model()
         lowerCAmelCase					:					List[Any]								=							self.dummy_sample_deter
         scheduler.set_timesteps(snake_case__						)

         for i, t in enumerate(scheduler.timesteps						):
           lowerCAmelCase					:					Any								=							model(snake_case__		,					snake_case__						)
           lowerCAmelCase					:					List[Any]								=							scheduler.step(snake_case__		,					snake_case__		,					snake_case__						).prev_sample

         return sample

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Dict								=							dict(self.forward_default_kwargs						)

         lowerCAmelCase					:					Optional[Any]								=							kwargs.pop("num_inference_steps"		,					snake_case__						)

         for scheduler_class in self.scheduler_classes:
           lowerCAmelCase					:					Dict								=							self.get_scheduler_config()
           lowerCAmelCase					:					List[Any]								=							scheduler_class(**snake_case__						)

           lowerCAmelCase					:					int								=							self.dummy_sample
           lowerCAmelCase					:					int								=							0.1 * sample

           if num_inference_steps is not None and hasattr(snake_case__		,					"set_timesteps"						):
             scheduler.set_timesteps(snake_case__						)
           elif num_inference_steps is not None and not hasattr(snake_case__		,					"set_timesteps"						):
             lowerCAmelCase					:					List[str]								=							num_inference_steps

           # copy over dummy past residuals (must be done after set_timesteps)
           lowerCAmelCase					:					int								=							[residual + 0.2, residual + 0.15, residual + 0.10]
           lowerCAmelCase					:					Tuple								=							dummy_past_residuals[: scheduler.config.solver_order]

           lowerCAmelCase					:					int								=							scheduler.timesteps[5]
           lowerCAmelCase					:					str								=							scheduler.timesteps[6]

           lowerCAmelCase					:					str								=							scheduler.step(snake_case__		,					snake_case__		,					snake_case__		,					**snake_case__						).prev_sample
           lowerCAmelCase					:					Union[str, Any]								=							scheduler.step(snake_case__		,					snake_case__		,					snake_case__		,					**snake_case__						).prev_sample

           self.assertEqual(output_a.shape		,					sample.shape						)
           self.assertEqual(output_a.shape		,					output_a.shape						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					int								=							DEISMultistepScheduler(**self.get_scheduler_config()						)
         lowerCAmelCase					:					Dict								=							self.full_loop(scheduler=snake_case__						)
         lowerCAmelCase					:					Optional[Any]								=							torch.mean(torch.abs(snake_case__						)						)

         assert abs(result_mean.item() - 0.23916						) < 1e-3

         lowerCAmelCase					:					List[str]								=							DPMSolverSinglestepScheduler.from_config(scheduler.config						)
         lowerCAmelCase					:					Any								=							DPMSolverMultistepScheduler.from_config(scheduler.config						)
         lowerCAmelCase					:					str								=							UniPCMultistepScheduler.from_config(scheduler.config						)
         lowerCAmelCase					:					Union[str, Any]								=							DEISMultistepScheduler.from_config(scheduler.config						)

         lowerCAmelCase					:					Union[str, Any]								=							self.full_loop(scheduler=snake_case__						)
         lowerCAmelCase					:					str								=							torch.mean(torch.abs(snake_case__						)						)

         assert abs(result_mean.item() - 0.23916						) < 1e-3

       def 	lowercase__							(						self						):






         """simple docstring"""





         for timesteps in [25, 50, 100, 999, 1_000]:
           self.check_over_configs(num_train_timesteps=snake_case__						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         self.check_over_configs(thresholding=snake_case__						)
         for order in [1, 2, 3]:
           for solver_type in ["logrho"]:
             for threshold in [0.5, 1.0, 2.0]:
               for prediction_type in ["epsilon", "sample"]:
                 self.check_over_configs(
                     thresholding=snake_case__		,					prediction_type=snake_case__		,					sample_max_value=snake_case__		,					algorithm_type="deis"		,					solver_order=snake_case__		,					solver_type=snake_case__		,					)

       def 	lowercase__							(						self						):






         """simple docstring"""





         for prediction_type in ["epsilon", "v_prediction"]:
           self.check_over_configs(prediction_type=snake_case__						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         for algorithm_type in ["deis"]:
           for solver_type in ["logrho"]:
             for order in [1, 2, 3]:
               for prediction_type in ["epsilon", "sample"]:
                 self.check_over_configs(
                     solver_order=snake_case__		,					solver_type=snake_case__		,					prediction_type=snake_case__		,					algorithm_type=snake_case__		,					)
                 lowerCAmelCase					:					Any								=							self.full_loop(
                     solver_order=snake_case__		,					solver_type=snake_case__		,					prediction_type=snake_case__		,					algorithm_type=snake_case__		,					)
                 assert not torch.isnan(snake_case__						).any(), "Samples have nan numbers"

       def 	lowercase__							(						self						):






         """simple docstring"""





         self.check_over_configs(lower_order_final=snake_case__						)
         self.check_over_configs(lower_order_final=snake_case__						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         for num_inference_steps in [1, 2, 3, 5, 10, 50, 100, 999, 1_000]:
           self.check_over_forward(num_inference_steps=snake_case__		,					time_step=0						)

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							self.full_loop()
         lowerCAmelCase					:					Dict								=							torch.mean(torch.abs(snake_case__						)						)

         assert abs(result_mean.item() - 0.23916						) < 1e-3

       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[Any]								=							self.full_loop(prediction_type="v_prediction"						)
         lowerCAmelCase					:					List[Any]								=							torch.mean(torch.abs(snake_case__						)						)

         assert abs(result_mean.item() - 0.091						) < 1e-3







       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Dict								=							self.scheduler_classes[0]
         lowerCAmelCase					:					str								=							self.get_scheduler_config(thresholding=snake_case__		,					dynamic_thresholding_ratio=0						)
         lowerCAmelCase					:					Optional[Any]								=							scheduler_class(**snake_case__						)

         lowerCAmelCase					:					Optional[Any]								=							10
         lowerCAmelCase					:					Tuple								=							self.dummy_model()
         lowerCAmelCase					:					List[str]								=							self.dummy_sample_deter.half()
         scheduler.set_timesteps(snake_case__						)

         for i, t in enumerate(scheduler.timesteps						):
           lowerCAmelCase					:					Union[str, Any]								=							model(snake_case__		,					snake_case__						)
           lowerCAmelCase					:					Tuple								=							scheduler.step(snake_case__		,					snake_case__		,					snake_case__						).prev_sample

         assert sample.dtype == torch.floataa





