






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


UpperCamelCase        =				False

class        lowerCAmelCase_				(      unittest.TestCase	):







				"""simple docstring"""




				pass

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







				"""simple docstring"""




				def 				__a   ( self     :Optional[int]     ):
					UpperCamelCase__ :Optional[Any]						=      VersatileDiffusionImageVariationPipeline.from_pretrained("""shi-labs/versatile-diffusion"""     )
					pipe.to(lowerCamelCase__     )
					pipe.set_progress_bar_config(disable=lowerCamelCase__     )

					UpperCamelCase__ :str						=      load_image(
					    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg"""     )
					UpperCamelCase__ :List[Any]						=      torch.manual_seed(0     )
					UpperCamelCase__ :Any						=      pipe(
					    image=lowerCamelCase__  ,     generator=lowerCamelCase__  ,     guidance_scale=7.5  ,     num_inference_steps=50  ,     output_type="""numpy"""  ,     ).images

					UpperCamelCase__ :Optional[int]						=      image[0, 2_53:2_56, 2_53:2_56, -1]

					assert image.shape == (1, 5_12, 5_12, 3)
					UpperCamelCase__ :Any						=      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'''





# Lint as: python3
import itertools
import os
import re


UpperCAmelCase__  			=				re.compile(r'''([A-Z]+)([A-Z][a-z])''')
UpperCAmelCase__  			=				re.compile(r'''([a-z\d])([A-Z])''')

UpperCAmelCase__  			=				re.compile(r'''(?<!_)_(?!_)''')
UpperCAmelCase__  			=				re.compile(r'''(_{2,})''')

UpperCAmelCase__  			=				r'''^\w+(\.\w+)*$'''

UpperCAmelCase__  			=				r'''<>:/\|?*'''






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Union[str, Any] ):






			"""simple docstring"""




			__A=	_uppercase_uppercase_re.sub(r'\1_\2',_SCREAMING_SNAKE_CASE )
			__A=	_lowercase_uppercase_re.sub(r'\1_\2',_SCREAMING_SNAKE_CASE )
			return name.lower()






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: int ):






			"""simple docstring"""




			__A=	_single_underscore_re.split(_SCREAMING_SNAKE_CASE )
			__A=	[_multiple_underscores_re.split(_SCREAMING_SNAKE_CASE ) for n in name]
			return "".join(n.capitalize() for n in itertools.chain.from_iterable(_SCREAMING_SNAKE_CASE ) if n != '' )






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: str ):






			"""simple docstring"""




			if os.path.basename(_SCREAMING_SNAKE_CASE ) != name:
						raise ValueError(f"""Should be a dataset name, not a path: {name}""" )
			return camelcase_to_snakecase(_SCREAMING_SNAKE_CASE )






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Union[str, Any],_SCREAMING_SNAKE_CASE					: str ):






			"""simple docstring"""




			if os.path.basename(_SCREAMING_SNAKE_CASE ) != name:
						raise ValueError(f"""Should be a dataset name, not a path: {name}""" )
			if not re.match(_split_re,_SCREAMING_SNAKE_CASE ):
						raise ValueError(f"""Split name should match '{_split_re}'' but got '{split}'.""" )
			return f"""{filename_prefix_for_name(_SCREAMING_SNAKE_CASE )}-{split}"""






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Union[str, Any],_SCREAMING_SNAKE_CASE					: Optional[Any],_SCREAMING_SNAKE_CASE					: Optional[int],_SCREAMING_SNAKE_CASE					: Union[str, Any]=None ):






			"""simple docstring"""




			__A=	filename_prefix_for_split(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE )
			if filetype_suffix:
						prefix += f""".{filetype_suffix}"""
			__A=	os.path.join(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE )
			return f"""{filepath}*"""






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: int,_SCREAMING_SNAKE_CASE					: List[str],_SCREAMING_SNAKE_CASE					: int,_SCREAMING_SNAKE_CASE					: List[Any]=None,_SCREAMING_SNAKE_CASE					: List[str]=None ):






			"""simple docstring"""




			__A=	filename_prefix_for_split(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE )
			__A=	os.path.join(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE )

			if shard_lengths:
						__A=	len(_SCREAMING_SNAKE_CASE )
						__A=	[f"""{prefix}-{shard_id:05d}-of-{num_shards:05d}""" for shard_id in range(_SCREAMING_SNAKE_CASE )]
						if filetype_suffix:
									__A=	[filename + f""".{filetype_suffix}""" for filename in filenames]
						return filenames
			else:
						__A=	prefix
						if filetype_suffix:
									filename += f""".{filetype_suffix}"""
						return [filename]



