



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__     =						False







class 		snake_case    (						unittest.TestCase	):



   '''simple docstring'''






   pass







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



   '''simple docstring'''






   def   UpperCamelCase_	(       self				:      List[str])					->					Optional[int]:

    """simple docstring"""







    _snake_case     :	Dict											=       VersatileDiffusionImageVariationPipeline.from_pretrained("""shi-labs/versatile-diffusion""")
    pipe.to(snake_case_)
    pipe.set_progress_bar_config(disable=snake_case_)

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

    _snake_case     :	Union[str, Any]											=       image[0, 253:256, 253:256, -1]

    assert image.shape == (1, 512, 512, 3)
    _snake_case     :	Any											=       np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945])

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


"""simple docstring"""
import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
SCREAMING_SNAKE_CASE_					     =	[
    '''kernels/rwkv/wkv_cuda.cu''',
    '''kernels/rwkv/wkv_op.cpp''',
    '''kernels/deformable_detr/ms_deform_attn.h''',
    '''kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh''',
    '''models/graphormer/algos_graphormer.pyx''',
]

def  lowercase     (_lowerCAmelCase						):
						# Test all the extensions added in the setup
						for file in FILES_TO_FIND:
												if not (transformers_path / file).exists():
																		return False
						return True


if __name__ == "__main__":
			SCREAMING_SNAKE_CASE_					     =	argparse.ArgumentParser()
			parser.add_argument('''--check_lib''', action='''store_true''', help='''Whether to check the build or the actual package.''')
			SCREAMING_SNAKE_CASE_					     =	parser.parse_args()
			if args.check_lib:
						SCREAMING_SNAKE_CASE_					     =	importlib.import_module('''transformers''')
						SCREAMING_SNAKE_CASE_					     =	Path(transformers_module.__file__).parent
			else:
						SCREAMING_SNAKE_CASE_					     =	Path.cwd() / '''build/lib/transformers'''
			if not test_custom_files_are_present(transformers_path):
						raise ValueError('''The built release does not contain the custom files. Fix this before going further!''')
