




from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters



def        __a							(  ) ->					Dict:
							"""simple docstring"""




							lowerCamelCase_			:    List[str]   						=      {
							    "repo_name": ["test_repo1", "test_repo2", "test_repo3"],
							    "path": ["test_1.py", "test_2.py", "unit_test.py"],
							    "content": ["a " * 20, "a " * 30, "b " * 7],
							}
							lowerCamelCase_			:    Optional[Any]   						=      Dataset.from_dict(__UpperCAmelCase      )
							return dataset





class 					snake_case_   (     _UpperCamelCase	):



				'''simple docstring'''





				def    __SCREAMING_SNAKE_CASE     (      self							:   Optional[int]							)							->			int:
											lowerCamelCase_			:    Optional[Any]   						=      get_dataset()
											lowerCamelCase_			:    Dict   						=      make_duplicate_clusters(__magic_name__      ,							0.85							)
											self.assertEqual(len(duplicate_clusters[0]							)      ,							2							)





				def    __SCREAMING_SNAKE_CASE     (      self							:   Tuple							)							->			Optional[int]:
											lowerCamelCase_			:    int   						=      get_dataset()
											lowerCamelCase_			:    Optional[int]   						=      deduplicate_dataset(__magic_name__							)
											self.assertEqual(len(__magic_name__							)      ,							2							)
											print(__magic_name__							)
											self.assertEqual(duplicate_clusters[0][0]["copies"]      ,							2							)
											self.assertEqual(duplicate_clusters[0][0]["is_extreme"]      ,							__magic_name__							)








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

