



import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


A__  :  Union[str, Any]								=					False



class 				__snake_case						(     unittest.TestCase						):
							pass





@slow
@require_torch_gpu
class 				__snake_case						(     unittest.TestCase						):




							def    UpperCAmelCase__			(       self     :       Union[str, Any]):
									lowerCAmelCase_			:     List[Any]									= VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion''')
									pipe.to(A_)
									pipe.set_progress_bar_config(disable=A_)

									lowerCAmelCase_			:     Optional[Any]									= load_image(
									    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg''')
									lowerCAmelCase_			:     Union[str, Any]									= torch.manual_seed(0)
									lowerCAmelCase_			:     Optional[int]									= pipe(
									    image=A_				,				generator=A_				,				guidance_scale=7.5				,				num_inference_steps=5_0				,				output_type='''numpy'''				,				).images

									lowerCAmelCase_			:     Union[str, Any]									= image[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

									assert image.shape == (1, 5_1_2, 5_1_2, 3)
									lowerCAmelCase_			:     str									= np.array([0.0441, 0.0469, 0.0507, 0.0575, 0.0632, 0.0650, 0.0865, 0.0909, 0.0945])

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










'''simple docstring'''

import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union

import transformers
from transformers.testing_utils import require_tf, require_torch, slow


__lowerCAmelCase									=   logging.getLogger()

@unittest.skip('Temporarily disable the doc tests.'   )
@require_torch
@require_tf
@slow
class 	__magic_name__						(    unittest.TestCase   ):







							def 							__lowercase			(							self					:       str	,_UpperCAmelCase					:       Path	,_UpperCAmelCase					:       Union[str, None] = None	,_UpperCAmelCase					:       Union[List[str], None] = None	,_UpperCAmelCase					:       Union[str, List[str], None] = None	,_UpperCAmelCase					:       bool = True	,):
									_a     :      Dict        =							[file for file in os.listdir(_UpperCAmelCase		) if os.path.isfile(os.path.join(_UpperCAmelCase	,_UpperCAmelCase		)		)]

									if identifier is not None:
											_a     :      str        =							[file for file in files if identifier in file]

									if n_identifier is not None:
											if isinstance(_UpperCAmelCase	,_UpperCAmelCase		):
													for n_ in n_identifier:
															_a     :      int        =							[file for file in files if n_ not in file]
											else:
													_a     :      Optional[Any]        =							[file for file in files if n_identifier not in file]

									_a     :      Dict        =							ignore_files or []
									ignore_files.append('__init__.py'		)
									_a     :      List[str]        =							[file for file in files if file not in ignore_files]

									for file in files:
											# Open all files
											print('Testing'	,_UpperCAmelCase		)

											if only_modules:
													_a     :      Any        =							file.split('.'		)[0]
													try:
															_a     :      Optional[int]        =							getattr(_UpperCAmelCase	,_UpperCAmelCase		)
															_a     :      Dict        =							doctest.DocTestSuite(_UpperCAmelCase		)
															_a     :      Optional[int]        =							unittest.TextTestRunner().run(_UpperCAmelCase		)
															self.assertIs(len(result.failures		)	,0		)
													except AttributeError:
															logger.info(F"""{module_identifier} is not a module."""		)
											else:
													_a     :      str        =							doctest.testfile(str('..' / directory / file		)	,optionflags=doctest.ELLIPSIS		)
													self.assertIs(result.failed	,0		)







							def 							__lowercase			(							self					:       Union[str, Any]		):
									_a     :      Optional[Any]        =							Path('src/transformers'		)
									_a     :      Optional[Any]        =							'modeling'
									_a     :      Union[str, Any]        =							[
									    'modeling_ctrl.py',
									    'modeling_tf_ctrl.py',
									]
									self.analyze_directory(_UpperCAmelCase	,identifier=_UpperCAmelCase	,ignore_files=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       int		):
									_a     :      str        =							Path('src/transformers'		)
									_a     :      List[str]        =							'tokenization'
									self.analyze_directory(_UpperCAmelCase	,identifier=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       int		):
									_a     :      Any        =							Path('src/transformers'		)
									_a     :      str        =							'configuration'
									self.analyze_directory(_UpperCAmelCase	,identifier=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       Dict		):
									_a     :      Tuple        =							Path('src/transformers'		)
									_a     :      Optional[int]        =							['configuration', 'modeling', 'tokenization']
									self.analyze_directory(_UpperCAmelCase	,n_identifier=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       Optional[Any]		):
									_a     :      Union[str, Any]        =							Path('docs/source'		)
									_a     :      List[str]        =							['favicon.ico']
									self.analyze_directory(_UpperCAmelCase	,ignore_files=_UpperCAmelCase	,only_modules=_UpperCAmelCase		)




