






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


__lowerCamelCase :      Optional[int]										=				False



class 							SCREAMING_SNAKE_CASE__						(    unittest.TestCase						):





					"""simple docstring"""






					pass



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





					"""simple docstring"""






					def 	_lowercase					( self					:  Optional[int]	):
						snake_case__			:				Union[str, Any]       =  VersatileDiffusionImageVariationPipeline.from_pretrained("shi-labs/versatile-diffusion"	)
						pipe.to(__A	)
						pipe.set_progress_bar_config(disable=__A	)

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

						snake_case__			:				Optional[int]       =  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)
						snake_case__			:				Any       =  np.array([0.0_4_4_1, 0.0_4_6_9, 0.0_5_0_7, 0.0_5_7_5, 0.0_6_3_2, 0.0_6_5_0, 0.0_8_6_5, 0.0_9_0_9, 0.0_9_4_5]	)

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











# limitations under the License.

# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from .pipelines import DiffusionPipeline, ImagePipelineOutput  # noqa: F401
from .utils import deprecate


deprecate(
    """pipelines_utils""",
    """0.22.0""",
    """Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.""",
    standard_warn=False,
    stacklevel=3,
)



