






"""simple docstring"""
from __future__ import annotations



class      SCREAMING_SNAKE_CASE  :





	"""simple docstring"""




	def __init__(self     ,     lowerCAmelCase_							):
		A_		:						Dict	    =   order

		# a_{0} ... a_{k}
		A_		:						List[Any]	    =   [1.0] + [0.0] * order
		# b_{0} ... b_{k}
		A_		:						Optional[Any]	    =   [1.0] + [0.0] * order

		# x[n-1] ... x[n-k]
		A_		:						str	    =   [0.0] * self.order
		# y[n-1] ... y[n-k]
		A_		:						Optional[int]	    =   [0.0] * self.order





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_							):
		if len(lowerCAmelCase_							) < self.order:
			A_		:						List[Any]	    =   [1.0, *a_coeffs]

		if len(lowerCAmelCase_							) != self.order + 1:
			A_		:						Tuple	    =   (
			    f"""Expected a_coeffs to have {self.order + 1} elements """
			    f"""for {self.order}-order filter, got {len(lowerCAmelCase_							)}"""
			)
			raise ValueError(lowerCAmelCase_							)

		if len(lowerCAmelCase_							) != self.order + 1:
			A_		:						Union[str, Any]	    =   (
			    f"""Expected b_coeffs to have {self.order + 1} elements """
			    f"""for {self.order}-order filter, got {len(lowerCAmelCase_							)}"""
			)
			raise ValueError(lowerCAmelCase_							)

		A_		:						Optional[Any]	    =   a_coeffs
		A_		:						Optional[Any]	    =   b_coeffs





	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		A_		:						str	    =   0.0

		# Start at index 1 and do index 0 at the end.
		for i in range(1     ,     self.order + 1							):
			result += (
			    self.b_coeffs[i] * self.input_history[i - 1]
			    - self.a_coeffs[i] * self.output_history[i - 1]
			)

		A_		:						Union[str, Any]	    =   (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

		A_		:						str	    =   self.input_history[:-1]
		A_		:						Optional[int]	    =   self.output_history[:-1]

		A_		:						str	    =   sample
		A_		:						Optional[int]	    =   result

		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							)

