

'''simple docstring'''

import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest







class   UpperCamelCase__   (       lowercase__       ):


		"""simple docstring"""

		SCREAMING_SNAKE_CASE__  :     Optional[Any]       =							(VQDiffusionScheduler,)







		def 				A_	(			self   ,      **snake_case      ):


							'''simple docstring'''

							UpperCAmelCase		:							Any        =       {
							    "num_vec_classes": 4_0_9_7,
							    "num_train_timesteps": 1_0_0,
							}

							config.update(**snake_case      )
							return config







		def 				A_	(			self   ,      snake_case      ):


							'''simple docstring'''

							UpperCAmelCase		:							Union[str, Any]        =       4
							UpperCAmelCase		:							Union[str, Any]        =       8
							UpperCAmelCase		:							Tuple        =       8

							UpperCAmelCase		:							str        =       torch.randint(0   ,      snake_case   ,      (batch_size, height * width)      )

							return sample







		@property
		def 				A_	(			self      ):


							'''simple docstring'''

							assert False







		def 				A_	(			self   ,      snake_case      ):


							'''simple docstring'''

							def model(snake_case   ,      snake_case   ,      *snake_case      ):
												UpperCAmelCase		:							Dict        =       sample.shape
												UpperCAmelCase		:							str        =       torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)      )
												UpperCAmelCase		:							Optional[int]        =       F.log_softmax(logits.double()   ,      dim=1      ).float()
												return return_value

							return model







		def 				A_	(			self      ):


							'''simple docstring'''

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







		def 				A_	(			self      ):


							'''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=snake_case      )







		def 				A_	(			self      ):


							'''simple docstring'''

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







		def 				A_	(			self      ):


							'''simple docstring'''

							pass








'''simple docstring'''

a       :      str  	=			[[0, 1, 1], [0, 0, 1], [1, 0, 0]]







class   UpperCamelCase__   :


		"""simple docstring"""

		def __init__(			self   ,      snake_case      ):


							'''simple docstring'''

							UpperCAmelCase		:							Optional[int]        =       name
							UpperCAmelCase		:							Optional[Any]        =       []
							UpperCAmelCase		:							Tuple        =       []







		def 				A_	(			self   ,      snake_case      ):


							'''simple docstring'''

							self.inbound.append(snake_case      )







		def 				A_	(			self   ,      snake_case      ):


							'''simple docstring'''

							self.outbound.append(snake_case      )







		def __repr__(			self      ):


							'''simple docstring'''

							return f"<node={self.name} inbound={self.inbound} outbound={self.outbound}>"





def 				lowercase (					__magic_name__			,   __magic_name__=3			,   __magic_name__=0.8_5							):



					'''simple docstring'''







					UpperCAmelCase		:							str        =       {}
					for node in nodes:
										UpperCAmelCase		:							Tuple        =       1

					UpperCAmelCase		:							Optional[Any]        =       {}
					for node in nodes:
										UpperCAmelCase		:							List[str]        =       len(node.outbound							)

					for i in range(__magic_name__							):
										print(F"======= Iteration {i + 1} ======="							)
										for _, node in enumerate(__magic_name__							):
															UpperCAmelCase		:							Any        =       (1 - d) + d * sum(
															    ranks[ib] / outbounds[ib] for ib in node.inbound							)
										print(__magic_name__							)





def 				lowercase (					):



					'''simple docstring'''







					UpperCAmelCase		:							Dict        =       list(input("Enter Names of the Nodes: "							).split()							)

					UpperCAmelCase		:							Any        =       [Node(__magic_name__							) for name in names]

					for ri, row in enumerate(__magic_name__							):
										for ci, col in enumerate(__magic_name__							):
															if col == 1:
																				nodes[ci].add_inbound(names[ri]							)
																				nodes[ri].add_outbound(names[ci]							)

					print("======= Nodes ======="							)
					for node in nodes:
										print(__magic_name__							)

					page_rank(__magic_name__							)


if __name__ == "__main__":
				main()
