




"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCamelCase  :			Union[str, Any]        =       {'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ReformerConfig']}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			int        =       ['ReformerTokenizer']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			Dict        =       ['ReformerTokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase  :			Union[str, Any]        =       [
		    'REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ReformerAttention',
		    'ReformerForMaskedLM',
		    'ReformerForQuestionAnswering',
		    'ReformerForSequenceClassification',
		    'ReformerLayer',
		    'ReformerModel',
		    'ReformerModelWithLMHead',
		    'ReformerPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_reformer import ReformerTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_reformer_fast import ReformerTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_reformer import (
				    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ReformerAttention,
				    ReformerForMaskedLM,
				    ReformerForQuestionAnswering,
				    ReformerForSequenceClassification,
				    ReformerLayer,
				    ReformerModel,
				    ReformerModelWithLMHead,
				    ReformerPreTrainedModel,
				)

else:
		import sys

		_lowerCamelCase  :			str        =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











"""simple docstring"""

def 		lowercase_      (		_UpperCAmelCase	):




	"""simple docstring"""






	A_  :				int	   =		len(_UpperCAmelCase	)
	for i in range(length - 1	):
		A_  :				str	   =		i
		for k in range(i + 1  ,      _UpperCAmelCase	):
			if collection[k] < collection[least]:
				A_  :				Tuple	   =		k
		if least != i:
			A_   , A_  :				Optional[int]	   =		(collection[i], collection[least])
	return collection


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





