
def 				a__ (				snake_case				):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE	:     Dict =						len(snake_case				)
  for i in range(length - 1				):
    __SCREAMING_SNAKE_CASE	:     Union[str, Any] =						i
    for k in range(i + 1    ,       snake_case				):
      if collection[k] < collection[least]:
        __SCREAMING_SNAKE_CASE	:     Optional[int] =						k
    if least != i:
      __SCREAMING_SNAKE_CASE	:     Optional[Any] =						(collection[i], collection[least])
  return collection


if __name__ == "__main__":
   lowercase_      							=       input("""Enter numbers separated by a comma:\n""").strip()
   lowercase_      							=       [int(item) for item in user_input.split(""",""")]
   print(selection_sort(unsorted))

from typing import TYPE_CHECKING

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


__lowerCamelCase					:	Dict       =  {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase					:	Any       =  [
		    '''VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ViTMAEForPreTraining''',
		    '''ViTMAELayer''',
		    '''ViTMAEModel''',
		    '''ViTMAEPreTrainedModel''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase					:	Optional[Any]       =  [
		    '''TFViTMAEForPreTraining''',
		    '''TFViTMAEModel''',
		    '''TFViTMAEPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vit_mae import (
				    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViTMAEForPreTraining,
				    ViTMAELayer,
				    ViTMAEModel,
				    ViTMAEPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
		import sys

		__lowerCamelCase					:	Any       =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
