




"""simple docstring"""

import unittest

import numpy as np
import torch

from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()





class 							lowercase_			(	unittest.TestCase				):



 '''simple docstring'''

 @property
 def      lowerCAmelCase_				(					self			:			Tuple						):
       torch.manual_seed(0						)
       _A     =  UNetaDModel(
           block_out_channels=(32, 64)       ,				layers_per_block=2       ,				sample_size=32       ,				in_channels=3       ,				out_channels=3       ,				down_block_types=('DownBlock2D', 'AttnDownBlock2D')       ,				up_block_types=('AttnUpBlock2D', 'UpBlock2D')       ,				)
       return model



 def      lowerCAmelCase_				(					self			:			List[Any]						):
       _A     =  self.dummy_uncond_unet
       _A     =  ScoreSdeVeScheduler()

       _A     =  ScoreSdeVePipeline(unet=_UpperCAmelCase       ,				scheduler=_UpperCAmelCase						)
       sde_ve.to(_UpperCAmelCase						)
       sde_ve.set_progress_bar_config(disable=_UpperCAmelCase						)

       _A     =  torch.manual_seed(0						)
       _A     =  sde_ve(num_inference_steps=2       ,				output_type='numpy'       ,				generator=_UpperCAmelCase						).images

       _A     =  torch.manual_seed(0						)
       _A     =  sde_ve(num_inference_steps=2       ,				output_type='numpy'       ,				generator=_UpperCAmelCase       ,				return_dict=_UpperCAmelCase						)[
           0
       ]

       _A     =  image[0, -3:, -3:, -1]
       _A     =  image_from_tuple[0, -3:, -3:, -1]

       assert image.shape == (1, 32, 32, 3)
       _A     =  np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]						)

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





@slow
@require_torch
class 							lowercase_			(	unittest.TestCase				):



 '''simple docstring'''

 def      lowerCAmelCase_				(					self			:			Optional[Any]						):
       _A     =  'google/ncsnpp-church-256'
       _A     =  UNetaDModel.from_pretrained(_UpperCAmelCase						)

       _A     =  ScoreSdeVeScheduler.from_pretrained(_UpperCAmelCase						)

       _A     =  ScoreSdeVePipeline(unet=_UpperCAmelCase       ,				scheduler=_UpperCAmelCase						)
       sde_ve.to(_UpperCAmelCase						)
       sde_ve.set_progress_bar_config(disable=_UpperCAmelCase						)

       _A     =  torch.manual_seed(0						)
       _A     =  sde_ve(num_inference_steps=10       ,				output_type='numpy'       ,				generator=_UpperCAmelCase						).images

       _A     =  image[0, -3:, -3:, -1]

       assert image.shape == (1, 256, 256, 3)

       _A     =  np.array([0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0]						)

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







"""simple docstring"""

import argparse


a							      =     '''docs/source/_static/js/custom.js'''






def 		_snake_case	(   _snake_case				:   Dict				)       ->   Any:






      '''simple docstring'''


      with open(_snake_case							,    encoding='utf-8'							,    newline='\n'				) as f:
            _A     =  f.readlines()
      _A     =  0

      # First let's put the right version
      while not lines[index].startswith('const stableVersion ='				):
            index += 1
      _A     =  F'''const stableVersion = "v{version}"\n'''

      # Then update the dictionary
      while not lines[index].startswith('const versionMapping = {'				):
            index += 1

      # We go until the end
      while not lines[index].startswith('}'				):
            index += 1
      # We add the new version at the end
      lines[index - 1] += F'''    "v{version}": "v{version}",\n'''

      with open(_snake_case							,    'w'							,    encoding='utf-8'							,    newline='\n'				) as f:
            f.writelines(_snake_case				)


if __name__ == "__main__":
       a							      =     argparse.ArgumentParser()
       parser.add_argument('''--version''', help='''Release version.''')
       a							      =     parser.parse_args()
       update_custom_js(args.version)

