





"""simple docstring"""




import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest




class 					_a		( snake_case_							):
				UpperCamelCase								=       (VQDiffusionScheduler,)






				def 							snake_case      (					self						:       List[Any],					**lowerCAmelCase__						:       List[str]				)      -> Union[str, Any]:




										'''simple docstring'''



										_UpperCamelCase     :   Optional[Any]      =       {
										    '''num_vec_classes''': 4_0_9_7,
										    '''num_train_timesteps''': 1_0_0,
										}

										config.update(**SCREAMING_SNAKE_CASE_				)
										return config






				def 							snake_case      (					self						:       Tuple,					lowerCAmelCase__						:       Optional[Any]				)      -> List[Any]:




										'''simple docstring'''



										_UpperCamelCase     :   Optional[Any]      =       4
										_UpperCamelCase     :   Optional[int]      =       8
										_UpperCamelCase     :   Optional[Any]      =       8

										_UpperCamelCase     :   Dict      =       torch.randint(0,					SCREAMING_SNAKE_CASE_,					(batch_size, height * width)				)

										return sample






				@property
				def 							snake_case      (					self						:       int				)      -> Union[str, Any]:




										'''simple docstring'''



										assert False






				def 							snake_case      (					self						:       Any,					lowerCAmelCase__						:       Optional[int]				)      -> List[str]:




										'''simple docstring'''



										def model(lowerCAmelCase__						:       List[Any],					lowerCAmelCase__						:       str,					*lowerCAmelCase__						:       Tuple				):
																_UpperCamelCase     :   Optional[Any]      =       sample.shape
																_UpperCamelCase     :   Any      =       torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)				)
																_UpperCamelCase     :   List[Any]      =       F.log_softmax(logits.double(),					dim=1				).float()
																return return_value

										return model






				def 							snake_case      (					self						:       List[Any]				)      -> Union[str, Any]:




										'''simple docstring'''



										for timesteps in [2, 5, 1_0_0, 1_0_0_0]:
																self.check_over_configs(num_train_timesteps=SCREAMING_SNAKE_CASE_				)






				def 							snake_case      (					self						:       List[str]				)      -> int:




										'''simple docstring'''



										for num_vec_classes in [5, 1_0_0, 1_0_0_0, 4_0_0_0]:
																self.check_over_configs(num_vec_classes=SCREAMING_SNAKE_CASE_				)






				def 							snake_case      (					self						:       Dict				)      -> Any:




										'''simple docstring'''



										for t in [0, 5_0, 9_9]:
																self.check_over_forward(time_step=SCREAMING_SNAKE_CASE_				)






				def 							snake_case      (					self						:       List[str]				)      -> List[Any]:




										'''simple docstring'''



										pass









"""simple docstring"""





from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
_lowercase						   =     TypeVar("""T""", bound="""Enum""")

@unique
class    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      =80
				_lowerCAmelCase						      =70
				_lowerCAmelCase						      =60
				_lowerCAmelCase						      =50
				_lowerCAmelCase						      =40
				_lowerCAmelCase						      =30
				_lowerCAmelCase						      =20
				_lowerCAmelCase						      =10







@unique
class    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      =24
				_lowerCAmelCase						      =21
				_lowerCAmelCase						      =18
				_lowerCAmelCase						      =15
				_lowerCAmelCase						      =12
				_lowerCAmelCase						      =9
				_lowerCAmelCase						      =6
				_lowerCAmelCase						      =3
				_lowerCAmelCase						      =2
				_lowerCAmelCase						      =1
				_lowerCAmelCase						      =-1
				_lowerCAmelCase						      =-2
				_lowerCAmelCase						      =-3
				_lowerCAmelCase						      =-6
				_lowerCAmelCase						      =-9
				_lowerCAmelCase						      =-12
				_lowerCAmelCase						      =-15
				_lowerCAmelCase						      =-18
				_lowerCAmelCase						      =-21
				_lowerCAmelCase						      =-24

				@classmethod
				def    _lowerCamelCase       ( cls :  type[T]   ):
										return {unit.name: unit.value for unit in cls if unit.value > 0}





				@classmethod
				def    _lowerCamelCase       ( cls :  type[T]   ):
										return {unit.name: unit.value for unit in cls if unit.value < 0}







def 		lowerCAmelCase				(			lowerCamelCase		):
						'''simple docstring'''


						snake_case__							:       List[Any]				      =       SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
						for name_prefix, value_prefix in prefixes.items():
												snake_case__							:       Optional[int]				      =       value / (10**value_prefix)
												if numerical_part > 1:
																		return f'''{numerical_part!s} {name_prefix}'''
						return str(lowerCamelCase		)

def 		lowerCAmelCase				(			lowerCamelCase		):
						'''simple docstring'''


						for prefix in BinaryUnit:
												snake_case__							:       int				      =       value / (2**prefix.value)
												if numerical_part > 1:
																		return f'''{numerical_part!s} {prefix.name}'''
						return str(lowerCamelCase		)


if __name__ == "__main__":
							import doctest

							doctest.testmod()


