




from __future__ import annotations

from collections.abc import MutableSequence
class 						_A					:






  def __init__(  self		:	List[str]      ,						_A		:	str      ,						_A		:	Union[str, Any]      )		->    Optional[Any]:






       """simple docstring"""







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

       lowercase					:   List[Any]								= list(lowerCAmelCase_      )
       lowercase					:   Any								= degree






  def __add__(  self		:	Optional[int]      ,						_A		:	Dict      )		->    Any:






       """simple docstring"""







       if self.degree > polynomial_a.degree:
            lowercase					:   Any								= self.coefficients[:]
            for i in range(polynomial_a.degree + 1      ):
                 coefficients[i] += polynomial_a.coefficients[i]
            return Polynomial(self.degree      ,						lowerCAmelCase_      )
       else:
            lowercase					:   int								= polynomial_a.coefficients[:]
            for i in range(self.degree + 1      ):
                 coefficients[i] += self.coefficients[i]
            return Polynomial(polynomial_a.degree      ,						lowerCAmelCase_      )






  def __sub__(  self		:	Tuple      ,						_A		:	int      )		->    int:






       """simple docstring"""







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






  def __neg__(  self		:	Dict      )		->    List[str]:






       """simple docstring"""







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






  def __mul__(  self		:	Tuple      ,						_A		:	Union[str, Any]      )		->    List[Any]:






       """simple docstring"""







       lowercase					:   Optional[Any]								= [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      ,						lowerCAmelCase_      )






  def 					__a			(  self		:	Union[str, Any]      ,						_A		:	int      )		->    List[Any]:






       """simple docstring"""







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






  def __str__(  self		:	Any      )		->    str:






       """simple docstring"""







       lowercase					:   Any								= ''''''
       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(lowerCAmelCase_      )

       return polynomial






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






       """simple docstring"""







       return self.__str__()






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






       """simple docstring"""







       lowercase					:   Optional[Any]								= [0] * self.degree
       for i in range(self.degree      ):
            lowercase					:   Optional[Any]								= self.coefficients[i + 1] * (i + 1)
       return Polynomial(self.degree - 1      ,						lowerCAmelCase_      )






  def 					__a			(  self		:	str      ,						_A		:	List[str] = 0      )		->    str:






       """simple docstring"""







       lowercase					:   Optional[Any]								= [0] * (self.degree + 2)
       lowercase					:   Optional[int]								= constant
       for i in range(self.degree + 1      ):
            lowercase					:   Tuple								= self.coefficients[i] / (i + 1)
       return Polynomial(self.degree + 1      ,						lowerCAmelCase_      )






  def __eq__(  self		:	Any      ,						_A		:	Dict      )		->    List[str]:






       """simple docstring"""







       if not isinstance(lowerCAmelCase_      ,						lowerCAmelCase_      ):
            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		:	Union[str, Any]      ,						_A		:	Union[str, Any]      )		->    List[str]:






       """simple docstring"""







       return not self.__eq__(lowerCAmelCase_      )

'''simple docstring'''







import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device


lowercase    :							Optional[Any]      =					False


class 						__UpperCAmelCase      (					unittest.TestCase						):
							pass


@nightly
@require_torch_gpu
class 						__UpperCAmelCase      (					unittest.TestCase						):


							def  lowerCamelCase				(       self  ):





								"""simple docstring"""






								super().tearDown()
								gc.collect()
								torch.cuda.empty_cache()


							def  lowerCamelCase				(       self  ):





								"""simple docstring"""






								_snake_case   						=		VersatileDiffusionTextToImagePipeline.from_pretrained('shi-labs/versatile-diffusion'  )
								# remove text_unet
								pipe.remove_unused_weights()
								pipe.to(lowerCAmelCase_  )
								pipe.set_progress_bar_config(disable=lowerCAmelCase_  )

								_snake_case   						=		'A painting of a squirrel eating a burger '
								_snake_case   						=		torch.manual_seed(0  )
								_snake_case   						=		pipe(
								    prompt=lowerCAmelCase_    ,   generator=lowerCAmelCase_    ,   guidance_scale=7.5    ,   num_inference_steps=2    ,   output_type='numpy'  ).images

								with tempfile.TemporaryDirectory() as tmpdirname:
									pipe.save_pretrained(lowerCAmelCase_  )
									_snake_case   						=		VersatileDiffusionTextToImagePipeline.from_pretrained(lowerCAmelCase_  )
								pipe.to(lowerCAmelCase_  )
								pipe.set_progress_bar_config(disable=lowerCAmelCase_  )

								_snake_case   						=		generator.manual_seed(0  )
								_snake_case   						=		pipe(
								    prompt=lowerCAmelCase_    ,   generator=lowerCAmelCase_    ,   guidance_scale=7.5    ,   num_inference_steps=2    ,   output_type='numpy'  ).images

								assert np.abs(image - new_image  ).sum() < 1E-5, "Models don't have the same forward pass"




							def  lowerCamelCase				(       self  ):





								"""simple docstring"""






								_snake_case   						=		VersatileDiffusionTextToImagePipeline.from_pretrained(
								    'shi-labs/versatile-diffusion'    ,   torch_dtype=torch.floataa  )
								pipe.to(lowerCAmelCase_  )
								pipe.set_progress_bar_config(disable=lowerCAmelCase_  )

								_snake_case   						=		'A painting of a squirrel eating a burger '
								_snake_case   						=		torch.manual_seed(0  )
								_snake_case   						=		pipe(
								    prompt=lowerCAmelCase_    ,   generator=lowerCAmelCase_    ,   guidance_scale=7.5    ,   num_inference_steps=50    ,   output_type='numpy'  ).images

								_snake_case   						=		image[0, 2_53:2_56, 2_53:2_56, -1]

								assert image.shape == (1, 5_12, 5_12, 3)
								_snake_case   						=		np.array([0.3367, 0.3169, 0.2656, 0.3870, 0.4790, 0.3796, 0.4009, 0.4878, 0.4778]  )

								assert np.abs(image_slice.flatten() - expected_slice  ).max() < 1E-2

