


"""simple docstring"""

from typing import TYPE_CHECKING

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


UpperCAmelCase__					={
    '''configuration_electra''': ['''ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ElectraConfig''', '''ElectraOnnxConfig'''],
    '''tokenization_electra''': ['''ElectraTokenizer'''],
}

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

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase__					=[
           '''ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''ElectraForCausalLM''',
           '''ElectraForMaskedLM''',
           '''ElectraForMultipleChoice''',
           '''ElectraForPreTraining''',
           '''ElectraForQuestionAnswering''',
           '''ElectraForSequenceClassification''',
           '''ElectraForTokenClassification''',
           '''ElectraModel''',
           '''ElectraPreTrainedModel''',
           '''load_tf_weights_in_electra''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase__					=[
           '''TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''TFElectraForMaskedLM''',
           '''TFElectraForMultipleChoice''',
           '''TFElectraForPreTraining''',
           '''TFElectraForQuestionAnswering''',
           '''TFElectraForSequenceClassification''',
           '''TFElectraForTokenClassification''',
           '''TFElectraModel''',
           '''TFElectraPreTrainedModel''',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase__					=[
           '''FlaxElectraForCausalLM''',
           '''FlaxElectraForMaskedLM''',
           '''FlaxElectraForMultipleChoice''',
           '''FlaxElectraForPreTraining''',
           '''FlaxElectraForQuestionAnswering''',
           '''FlaxElectraForSequenceClassification''',
           '''FlaxElectraForTokenClassification''',
           '''FlaxElectraModel''',
           '''FlaxElectraPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraOnnxConfig
       from .tokenization_electra import ElectraTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_electra_fast import ElectraTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_electra import (
                  ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ElectraForCausalLM,
                  ElectraForMaskedLM,
                  ElectraForMultipleChoice,
                  ElectraForPreTraining,
                  ElectraForQuestionAnswering,
                  ElectraForSequenceClassification,
                  ElectraForTokenClassification,
                  ElectraModel,
                  ElectraPreTrainedModel,
                  load_tf_weights_in_electra,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_electra import (
                  TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFElectraForMaskedLM,
                  TFElectraForMultipleChoice,
                  TFElectraForPreTraining,
                  TFElectraForQuestionAnswering,
                  TFElectraForSequenceClassification,
                  TFElectraForTokenClassification,
                  TFElectraModel,
                  TFElectraPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_electra import (
                  FlaxElectraForCausalLM,
                  FlaxElectraForMaskedLM,
                  FlaxElectraForMultipleChoice,
                  FlaxElectraForPreTraining,
                  FlaxElectraForQuestionAnswering,
                  FlaxElectraForSequenceClassification,
                  FlaxElectraForTokenClassification,
                  FlaxElectraModel,
                  FlaxElectraPreTrainedModel,
              )

else:
       import sys

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




def 			lowerCAmelCase__					(     a__:						Optional[int]			)    ->						Optional[int]:


							'''simple docstring'''





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


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