





from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
	if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_torch_and_transformers_objects import (
	    VersatileDiffusionDualGuidedPipeline,
	    VersatileDiffusionImageVariationPipeline,
	    VersatileDiffusionPipeline,
	    VersatileDiffusionTextToImagePipeline,
	)
else:
	from .modeling_text_unet import UNetFlatConditionModel
	from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
	from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
	from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
	from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline







import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
	import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin



@require_torch
class  __lowerCAmelCase	(      unittest.TestCase,					_a					):






			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							snake_case_						:   Dict           =  load_tool('''text-to-speech'''   )
							self.tool.setup()






			def       lowerCamelCase  (self   )					->       List[str]:


							'''simple docstring'''



							torch.manual_seed(0   )
							snake_case_						:   Optional[int]           =  self.tool('''hey'''   )
							snake_case_						:   Union[str, Any]           =  result.to_raw()
							self.assertTrue(
							    torch.allclose(
							        resulting_tensor[:3] ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]   ) ,							)   )






			def       lowerCamelCase  (self   )					->       Optional[Any]:


							'''simple docstring'''



							torch.manual_seed(0   )
							snake_case_						:   Any           =  self.tool('''hey'''   )
							snake_case_						:   str           =  result.to_raw()
							self.assertTrue(
							    torch.allclose(
							        resulting_tensor[:3] ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]   ) ,							)   )
