


def 				lowerCamelCase__	(      a	:   list[int]				)    ->	list[int]:





			"""simple docstring"""
			a__ :List[str]						  =    len(a				)
			for i in range(a				):
						for j in range(i + 1	,  a				):
									if numbers[j] < numbers[i]:
												a__  ,  a__ :List[str]						  =    numbers[j], numbers[i]
			return numbers


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






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__			 =						{
    '''configuration_mgp_str''': ['''MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MgpstrConfig'''],
    '''processing_mgp_str''': ['''MgpstrProcessor'''],
    '''tokenization_mgp_str''': ['''MgpstrTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		snake_case__			 =						[
		    '''MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''MgpstrModel''',
		    '''MgpstrPreTrainedModel''',
		    '''MgpstrForSceneTextRecognition''',
		]

if TYPE_CHECKING:
		from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
		from .processing_mgp_str import MgpstrProcessor
		from .tokenization_mgp_str import MgpstrTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mgp_str import (
				    MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MgpstrForSceneTextRecognition,
				    MgpstrModel,
				    MgpstrPreTrainedModel,
				)
else:
		import sys

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


