



'''simple docstring'''





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 		_lowercase	(					self :      Dict  )   ->   List[str]:
    __lowerCamelCase			:			Optional[Any]       			=					VersatileDiffusionImageVariationPipeline.from_pretrained('shi-labs/versatile-diffusion'  )
    pipe.to(_a  )
    pipe.set_progress_bar_config(disable=_a  )

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

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

    assert image.shape == (1, 512, 512, 3)
    __lowerCamelCase			:			Dict       			=					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'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_UpperCamelCase											=		{
    'configuration_bridgetower': [
        'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BridgeTowerConfig',
        'BridgeTowerTextConfig',
        'BridgeTowerVisionConfig',
    ],
    'processing_bridgetower': ['BridgeTowerProcessor'],
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=		['BridgeTowerImageProcessor']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=		[
       'BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'BridgeTowerForContrastiveLearning',
       'BridgeTowerForImageAndTextRetrieval',
       'BridgeTowerForMaskedLM',
       'BridgeTowerModel',
       'BridgeTowerPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_bridgetower import (
       BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
       BridgeTowerConfig,
       BridgeTowerTextConfig,
       BridgeTowerVisionConfig,
   )
   from .processing_bridgetower import BridgeTowerProcessor

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_bridgetower import BridgeTowerImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_bridgetower import (
          BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
          BridgeTowerForContrastiveLearning,
          BridgeTowerForImageAndTextRetrieval,
          BridgeTowerForMaskedLM,
          BridgeTowerModel,
          BridgeTowerPreTrainedModel,
      )


else:
   import sys

   _UpperCamelCase											=		_LazyModule(__name__, globals()['__file__'], _import_structure)






