'''simple docstring'''




def 				snake_case__							(			_A:					Dict      ,   _A:					Union[str, Any]      ,   _A:					Dict      ,   _A:					List[str]      ,   _A:					Optional[int]      ,   _A:					Dict )    ->	List[str]:

		'''simple docstring'''


		if index == r:
				for j in range(_A ):
						print(data[j]      ,   end=""" """ )
				print(""" """ )
				return
		#  When no more elements are there to put in data[]
		if i >= n:
				return
		# current is included, put next at next location
		lowerCAmelCase   					=  arr[i]
		combination_util(_A      ,   _A      ,   _A      ,   index + 1      ,   _A      ,   i + 1 )
		# current is excluded, replace it with
		# next (Note that i+1 is passed, but
		# index is not changed)
		combination_util(_A      ,   _A      ,   _A      ,   _A      ,   _A      ,   i + 1 )
		# The main function that prints all combinations
		# of size r in arr[] of size n. This function
		# mainly uses combinationUtil()






def 				snake_case__							(			_A:					List[str]      ,   _A:					Optional[int]      ,   _A:					Tuple )    ->	Tuple:

		'''simple docstring'''


		lowerCAmelCase   					=  [0] * r
		# Print all combination using temporary array 'data[]'
		combination_util(_A      ,   _A      ,   _A      ,   0      ,   _A      ,   0 )


if __name__ == "__main__":
						# Driver code to check the function above
						__lowercase          =  [1_0, 2_0, 3_0, 4_0, 5_0]
						print_combination(arr, len(arr), 3)
						# This code is contributed by Ambuj sahu





'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__lowercase          =  {
    '''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetConfig''', '''ResNetOnnxConfig''']
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''ResNetForImageClassification''',
						    '''ResNetModel''',
						    '''ResNetPreTrainedModel''',
						    '''ResNetBackbone''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFResNetForImageClassification''',
						    '''TFResNetModel''',
						    '''TFResNetPreTrainedModel''',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase          =  [
						    '''FlaxResNetForImageClassification''',
						    '''FlaxResNetModel''',
						    '''FlaxResNetPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_resnet import (
												    RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ResNetBackbone,
												    ResNetForImageClassification,
												    ResNetModel,
												    ResNetPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_resnet import (
												    TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFResNetForImageClassification,
												    TFResNetModel,
												    TFResNetPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
						import sys

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




