






"""simple docstring"""
import torch

from diffusers import DiffusionPipeline



class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE						):





	"""simple docstring"""




	def __init__(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_							):
		super().__init__()

		self.register_modules(unet=lowerCAmelCase_     ,     scheduler=lowerCAmelCase_							)





	def __call__(self							):
		A_		:						str	    =   torch.randn(
		    (1, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)     ,     )
		A_		:						List[Any]	    =   1

		A_		:						str	    =   self.unet(lowerCAmelCase_     ,     lowerCAmelCase_							).sample
		A_		:						List[Any]	    =   self.scheduler.step(lowerCAmelCase_     ,     lowerCAmelCase_     ,     lowerCAmelCase_							).prev_sample

		A_		:						Optional[Any]	    =   scheduler_output - scheduler_output + torch.ones_like(lowerCAmelCase_							)

		return result









"""simple docstring"""
import unittest

import torch
from torch import nn

from diffusers.models.activations import get_activation



class      SCREAMING_SNAKE_CASE  (				unittest.TestCase						):





	"""simple docstring"""




	def    lowerCamelCase(self							):
		A_		:						Optional[int]	    =   get_activation("""swish"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.SiLU							)

		self.assertEqual(act(torch.tensor(-100     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)





	def    lowerCamelCase(self							):
		A_		:						Dict	    =   get_activation("""silu"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.SiLU							)

		self.assertEqual(act(torch.tensor(-100     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)





	def    lowerCamelCase(self							):
		A_		:						Optional[Any]	    =   get_activation("""mish"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.Mish							)

		self.assertEqual(act(torch.tensor(-200     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)





	def    lowerCamelCase(self							):
		A_		:						int	    =   get_activation("""gelu"""							)

		self.assertIsInstance(lowerCAmelCase_     ,     nn.GELU							)

		self.assertEqual(act(torch.tensor(-100     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertNotEqual(act(torch.tensor(-1     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(0     ,     dtype=torch.floataa							)							).item()     ,     0							)
		self.assertEqual(act(torch.tensor(20     ,     dtype=torch.floataa							)							).item()     ,     20							)

