from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def    A			(					):
						SCREAMING_SNAKE_CASE							:					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],
						}
						SCREAMING_SNAKE_CASE							:					Union[str, Any]           =							Dataset.from_dict(__a		)
						return dataset





class       lowercase__		(     __lowerCamelCase):


						def  __A ( self			:       Optional[Any]		):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:					str           =							get_dataset()
												SCREAMING_SNAKE_CASE							:					Union[str, Any]           =							make_duplicate_clusters(SCREAMING_SNAKE_CASE_					,	0.85		)
												self.assertEqual(len(duplicate_clusters[0]		)					,	2		)



						def  __A ( self			:       List[str]		):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:					Optional[int]           =							get_dataset()
												SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE							:					int           =							deduplicate_dataset(SCREAMING_SNAKE_CASE_		)
												self.assertEqual(len(SCREAMING_SNAKE_CASE_		)					,	2		)
												print(SCREAMING_SNAKE_CASE_		)
												self.assertEqual(duplicate_clusters[0][0]['''copies''']					,	2		)
												self.assertEqual(duplicate_clusters[0][0]['''is_extreme''']					,	SCREAMING_SNAKE_CASE_		)
from typing import TYPE_CHECKING

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


__UpperCamelCase	: Tuple    		=  {
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase	: Optional[Any]    		=  ['MaskFormerFeatureExtractor']
					__UpperCamelCase	: List[Any]    		=  ['MaskFormerImageProcessor']


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase	: Optional[int]    		=  [
					    'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MaskFormerForInstanceSegmentation',
					    'MaskFormerModel',
					    'MaskFormerPreTrainedModel',
					]
					__UpperCamelCase	: Union[str, Any]    		=  [
					    'MaskFormerSwinBackbone',
					    'MaskFormerSwinModel',
					    'MaskFormerSwinPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
					from .configuration_maskformer_swin import MaskFormerSwinConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_maskformer import MaskFormerFeatureExtractor
										from .image_processing_maskformer import MaskFormerImageProcessor
					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_maskformer import (
										    MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MaskFormerForInstanceSegmentation,
										    MaskFormerModel,
										    MaskFormerPreTrainedModel,
										)
										from .modeling_maskformer_swin import (
										    MaskFormerSwinBackbone,
										    MaskFormerSwinModel,
										    MaskFormerSwinPreTrainedModel,
										)


else:
					import sys

					__UpperCamelCase	: List[str]    		=  _LazyModule(__name__, globals()['__file__'], _import_structure)





