


'''simple docstring'''



def       UpperCAmelCase__ (     UpperCAmelCase_   :    list							)					->		list:

     for insert_index, insert_value in enumerate(collection[1:]							):
          __lowerCamelCase       :     Union[str, Any]        =		insert_index
          while insert_index >= 0 and insert_value < collection[insert_index]:
               __lowerCamelCase       :     List[str]        =		collection[insert_index]
               insert_index -= 1
          if insert_index != temp_index:
               __lowerCamelCase       :     Optional[int]        =		insert_value
     return collection


if __name__ == "__main__":
      from doctest import testmod

      testmod()

      A__		: Any												=  input("""Enter numbers separated by a comma:\n""").strip()
      A__		: Dict												=  [int(item) for item in user_input.split(""",""")]
      print(f'''{insertion_sort(unsorted) = }''')










'''simple docstring'''



from typing import TYPE_CHECKING

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


A__		: str												=  {"""configuration_hubert""": ["""HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """HubertConfig"""]}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__		: List[str]												=  [
          """HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """HubertForCTC""",
          """HubertForSequenceClassification""",
          """HubertModel""",
          """HubertPreTrainedModel""",
      ]


try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__		: Optional[int]												=  [
          """TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TFHubertForCTC""",
          """TFHubertModel""",
          """TFHubertPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_hubert import (
                HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                HubertForCTC,
                HubertForSequenceClassification,
                HubertModel,
                HubertPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_hubert import (
                TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFHubertForCTC,
                TFHubertModel,
                TFHubertPreTrainedModel,
            )


else:
      import sys

      A__		: Optional[int]												=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






