



from typing import TYPE_CHECKING

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


lowercase_	       =			{'''configuration_fnet''': ['''FNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FNetConfig''']}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			['''FNetTokenizer''']

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			['''FNetTokenizerFast''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    '''FNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''FNetForMaskedLM''',
				    '''FNetForMultipleChoice''',
				    '''FNetForNextSentencePrediction''',
				    '''FNetForPreTraining''',
				    '''FNetForQuestionAnswering''',
				    '''FNetForSequenceClassification''',
				    '''FNetForTokenClassification''',
				    '''FNetLayer''',
				    '''FNetModel''',
				    '''FNetPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_fnet import FNetTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_fnet_fast import FNetTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_fnet import (
								    FNET_PRETRAINED_MODEL_ARCHIVE_LIST,
								    FNetForMaskedLM,
								    FNetForMultipleChoice,
								    FNetForNextSentencePrediction,
								    FNetForPreTraining,
								    FNetForQuestionAnswering,
								    FNetForSequenceClassification,
								    FNetForTokenClassification,
								    FNetLayer,
								    FNetModel,
								    FNetPreTrainedModel,
								)


else:
				import sys

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









def 					__lowerCAmelCase		(  __lowerCamelCase	:    list	)  ->						list:
					if len(__lowerCamelCase	) <= 1:
										return lst

					__lowerCAmelCase	   =1

					while i < len(__lowerCamelCase	):
										if lst[i - 1] <= lst[i]:
															i += 1
										else:
															__lowerCAmelCase   ,	__lowerCAmelCase	   =lst[i], lst[i - 1]
															i -= 1
															if i == 0:
																				__lowerCAmelCase	   =1

					return lst


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




