





'''simple docstring'''






def 							_lowerCamelCase(  UpperCamelCase__    : Tuple		)		->  Tuple:
    A       :       str							=						len(UpperCamelCase__		)
    for i in range(length - 1		):
        A       :       List[str]							=						i
        for k in range(i + 1    ,       UpperCamelCase__		):
            if collection[k] < collection[least]:
                A       :       Tuple							=						k
        if least != i:
            A       :       Optional[Any]							=						(collection[i], collection[least])
    return collection


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(selection_sort(unsorted))







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case_     =	{
    """configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
    """tokenization_biogpt""": ["""BioGptTokenizer"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case_     =	[
         """BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """BioGptForCausalLM""",
         """BioGptForTokenClassification""",
         """BioGptForSequenceClassification""",
         """BioGptModel""",
         """BioGptPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
     from .tokenization_biogpt import BioGptTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_biogpt import (
              BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
              BioGptForCausalLM,
              BioGptForSequenceClassification,
              BioGptForTokenClassification,
              BioGptModel,
              BioGptPreTrainedModel,
          )


else:
     import sys

     snake_case_     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
