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					:   Union[str, Any]							=		False


class 						lowercase    (     unittest.TestCase     ):
							pass



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




							def 	__snake_case(						self   :					List[str]      )					->				Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       VersatileDiffusionImageVariationPipeline.from_pretrained("shi-labs/versatile-diffusion"      )
												pipe.to(_UpperCamelCase      )
												pipe.set_progress_bar_config(disable=_UpperCamelCase      )

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

												SCREAMING_SNAKE_CASE    			=       image[0, 253:256, 253:256, -1]

												assert image.shape == (1, 512, 512, 3)
												SCREAMING_SNAKE_CASE    			=       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





import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property


@unittest.skipUnless(os.path.exists(a     )				,       """Tatoeba directory does not exist."""     )
class 						lowercase    (     unittest.TestCase     ):




							@cached_property
							def 	__snake_case(						self   :					int      )					->				List[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       tempfile.mkdtemp()
												return TatoebaConverter(save_dir=_UpperCamelCase      )




							@slow
							def 	__snake_case(						self   :					Tuple      )					->				List[Any]:



												'''simple docstring'''

												self.resolver.convert_models(["heb-eng"]      )





							@slow
							def 	__snake_case(						self   :					Any      )					->				Optional[int]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       self.resolver.write_model_card("opus-mt-he-en"	,							dry_run=_UpperCamelCase      )
												assert mmeta["long_pair"] == "heb-eng"




