




"""simple docstring"""

import unittest

import torch

from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism

from .test_modeling_common import ModelTesterMixin, UNetTesterMixin


enable_full_determinism()





class 							lowercase_			(	SCREAMING_SNAKE_CASE__     ,      SCREAMING_SNAKE_CASE__     ,      unittest.TestCase				):



 '''simple docstring'''
 UpperCAmelCase       :	int     =      VQModel
 UpperCAmelCase       :	List[Any]     =      '''sample'''

 @property
 def      lowerCAmelCase_				(					self			:			Dict       ,				_UpperCAmelCase			:			List[Any]=(32, 32)						):
       _A     =  4
       _A     =  3

       _A     =  floats_tensor((batch_size, num_channels) + sizes						).to(_UpperCAmelCase						)

       return {"sample": image}

 @property
 def      lowerCAmelCase_				(					self			:			str						):
       return (3, 32, 32)

 @property
 def      lowerCAmelCase_				(					self			:			Dict						):
       return (3, 32, 32)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       _A     =  {
           'block_out_channels': [32, 64],
           'in_channels': 3,
           'out_channels': 3,
           'down_block_types': ['DownEncoderBlock2D', 'DownEncoderBlock2D'],
           'up_block_types': ['UpDecoderBlock2D', 'UpDecoderBlock2D'],
           'latent_channels': 3,
       }
       _A     =  self.dummy_input
       return init_dict, inputs_dict

 def      lowerCAmelCase_				(					self			:			List[str]						):
       pass

 def      lowerCAmelCase_				(					self			:			List[Any]						):
       pass

 def      lowerCAmelCase_				(					self			:			Optional[Any]						):
       _A  ,       _A     =  VQModel.from_pretrained('fusing/vqgan-dummy'       ,				output_loading_info=_UpperCAmelCase						)
       self.assertIsNotNone(_UpperCAmelCase						)
       self.assertEqual(len(loading_info['missing_keys']						)       ,				0						)

       model.to(_UpperCAmelCase						)
       _A     =  model(**self.dummy_input						)

       assert image is not None, "Make sure output is not None"



 def      lowerCAmelCase_				(					self			:			Tuple						):
       _A     =  VQModel.from_pretrained('fusing/vqgan-dummy'						)
       model.to(_UpperCAmelCase						).eval()

       torch.manual_seed(0						)
       if torch.cuda.is_available():
             torch.cuda.manual_seed_all(0						)

       _A     =  torch.randn(1       ,				model.config.in_channels       ,				model.config.sample_size       ,				model.config.sample_size						)
       _A     =  image.to(_UpperCAmelCase						)
       with torch.no_grad():
             _A     =  model(_UpperCAmelCase						).sample

       _A     =  output[0, -1, -3:, -3:].flatten().cpu()
       # fmt: off
       _A     =  torch.tensor([-0.0153, -0.4044, -0.1880, -0.5161, -0.2418, -0.4072, -0.1612, -0.0633, -0.0143]						)
       # fmt: on
       self.assertTrue(torch.allclose(_UpperCAmelCase       ,				_UpperCAmelCase       ,				atol=1E-3						)						)







from __future__ import annotations

from collections.abc import MutableSequence



class       a_       :





	def __init__(							self      ,     SCREAMING_SNAKE_CASE      ,     SCREAMING_SNAKE_CASE      )  ->					None:




				"""simple docstring"""



				if len(SCREAMING_SNAKE_CASE      ) != degree + 1:
							raise ValueError(
							    'The number of coefficients should be equal to the degree + 1.'      )

				SCREAMING_SNAKE_CASE_								=						list(SCREAMING_SNAKE_CASE      )
				SCREAMING_SNAKE_CASE_								=						degree





	def __add__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					Polynomial:




				"""simple docstring"""



				if self.degree > polynomial_a.degree:
							SCREAMING_SNAKE_CASE_								=						self.coefficients[:]
							for i in range(polynomial_a.degree + 1      ):
										coefficients[i] += polynomial_a.coefficients[i]
							return Polynomial(self.degree      ,     SCREAMING_SNAKE_CASE      )
				else:
							SCREAMING_SNAKE_CASE_								=						polynomial_a.coefficients[:]
							for i in range(self.degree + 1      ):
										coefficients[i] += self.coefficients[i]
							return Polynomial(polynomial_a.degree      ,     SCREAMING_SNAKE_CASE      )





	def __sub__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					Polynomial:




				"""simple docstring"""



				return self + polynomial_a * Polynomial(0      ,     [-1]      )





	def __neg__(							self      )  ->					Polynomial:




				"""simple docstring"""



				return Polynomial(self.degree      ,     [-c for c in self.coefficients]      )





	def __mul__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					Polynomial:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						[0] * (self.degree + polynomial_a.degree + 1)
				for i in range(self.degree + 1      ):
							for j in range(polynomial_a.degree + 1      ):
										coefficients[i + j] += (
										    self.coefficients[i] * polynomial_a.coefficients[j]
										)

				return Polynomial(self.degree + polynomial_a.degree      ,     SCREAMING_SNAKE_CASE      )





	def 						A_(							self      ,     SCREAMING_SNAKE_CASE      )  ->					int | float:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						0
				for i in range(self.degree + 1      ):
							result += self.coefficients[i] * (substitution**i)
				return result





	def __str__(							self      )  ->					str:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						''
				for i in range(self.degree      ,     -1      ,     -1      ):
							if self.coefficients[i] == 0:
										continue
							elif self.coefficients[i] > 0:
										if polynomial:
													polynomial += " + "
							else:
										polynomial += " - "

							if i == 0:
										polynomial += str(abs(self.coefficients[i]      )      )
							elif i == 1:
										polynomial += str(abs(self.coefficients[i]      )      ) + "x"
							else:
										polynomial += str(abs(self.coefficients[i]      )      ) + "x^" + str(SCREAMING_SNAKE_CASE      )

				return polynomial





	def __repr__(							self      )  ->					str:




				"""simple docstring"""



				return self.__str__()





	def 						A_(							self      )  ->					Polynomial:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						[0] * self.degree
				for i in range(self.degree      ):
							SCREAMING_SNAKE_CASE_								=						self.coefficients[i + 1] * (i + 1)
				return Polynomial(self.degree - 1      ,     SCREAMING_SNAKE_CASE      )





	def 						A_(							self      ,     SCREAMING_SNAKE_CASE = 0      )  ->					Polynomial:




				"""simple docstring"""



				SCREAMING_SNAKE_CASE_								=						[0] * (self.degree + 2)
				SCREAMING_SNAKE_CASE_								=						constant
				for i in range(self.degree + 1      ):
							SCREAMING_SNAKE_CASE_								=						self.coefficients[i] / (i + 1)
				return Polynomial(self.degree + 1      ,     SCREAMING_SNAKE_CASE      )





	def __eq__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					bool:




				"""simple docstring"""



				if not isinstance(SCREAMING_SNAKE_CASE      ,     SCREAMING_SNAKE_CASE      ):
							return False

				if self.degree != polynomial_a.degree:
							return False

				for i in range(self.degree + 1      ):
							if self.coefficients[i] != polynomial_a.coefficients[i]:
										return False

				return True





	def __ne__(							self      ,     SCREAMING_SNAKE_CASE      )  ->					bool:




				"""simple docstring"""



				return not self.__eq__(SCREAMING_SNAKE_CASE      )
