






"""simple docstring"""



import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


A_     =				50_0000

A_     ,						A_     =				os.path.split(__file__)
A_     =				os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))




@get_duration
def   _lowerCAmelCase		(				UpperCAmelCase__							:       datasets.Dataset   )		->Optional[int]:
						A__    :	Tuple			=	dataset.select(range(0,    len(UpperCAmelCase__   ),    2   )   )




@get_duration
def   _lowerCAmelCase		(				UpperCAmelCase__							:       datasets.Dataset   )		->str:
						A__    :	Any			=	dataset.sort("""numbers"""   )




@get_duration
def   _lowerCAmelCase		(				UpperCAmelCase__							:       datasets.Dataset   )		->List[Any]:
						A__    :	Optional[int]			=	dataset.shuffle()




@get_duration
def   _lowerCAmelCase		(				UpperCAmelCase__							:       datasets.Dataset   )		->Dict:
						A__    :	int			=	dataset.train_test_split(0.1   )




@get_duration
def   _lowerCAmelCase		(				UpperCAmelCase__							:       datasets.Dataset,    UpperCAmelCase__							:       Any=1_0   )		->List[Any]:
						for shard_id in range(UpperCAmelCase__   ):
												A__    :	List[Any]			=	dataset.shard(UpperCAmelCase__,    UpperCAmelCase__   )




def   _lowerCAmelCase		(				)		->Union[str, Any]:
						A__    :	Optional[Any]			=	{"""num examples""": SPEED_TEST_N_EXAMPLES}
						A__    :	Union[str, Any]			=	(select, sort, shuffle, train_test_split, shard)
						with tempfile.TemporaryDirectory() as tmp_dir:
												print("""generating dataset"""   )
												A__    :	Tuple			=	datasets.Features({"""text""": datasets.Value("""string"""   ), """numbers""": datasets.Value("""float32"""   )}   )
												A__    :	str			=	generate_example_dataset(
												    os.path.join(UpperCAmelCase__,    """dataset.arrow"""   ),    UpperCAmelCase__,    num_examples=UpperCAmelCase__   )
												print("""Functions"""   )
												for func in functions:
																		print(func.__name__   )
																		A__    :	Dict			=	func(UpperCAmelCase__   )

						with open(UpperCAmelCase__,    """wb"""   ) as f:
												f.write(json.dumps(UpperCAmelCase__   ).encode("""utf-8"""   )   )


if __name__ == "__main__":  # useful to run the profiler
						benchmark_indices_mapping()














"""simple docstring"""



from typing import TYPE_CHECKING

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


A_     =				{
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_     =				['''DeformableDetrFeatureExtractor''']
						A_     =				['''DeformableDetrImageProcessor''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_     =				[
						    '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''DeformableDetrForObjectDetection''',
						    '''DeformableDetrModel''',
						    '''DeformableDetrPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
												from .image_processing_deformable_detr import DeformableDetrImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_deformable_detr import (
												    DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DeformableDetrForObjectDetection,
												    DeformableDetrModel,
												    DeformableDetrPreTrainedModel,
												)

else:
						import sys

						A_     =				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






