
def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ = " "		):
      UpperCamelCase__    :   Dict					=				[]

      UpperCamelCase__    :   Optional[int]					=				0
      for index, char in enumerate(UpperCamelCase__		):
            if char == separator:
                  split_words.append(string[last_index:index]		)
                  UpperCamelCase__    :   List[str]					=				index + 1
            elif index + 1 == len(UpperCamelCase__		):
                  split_words.append(string[last_index : index + 1]		)
      return split_words


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

    testmod()




from typing import TYPE_CHECKING

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


lowerCamelCase      ={"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SwinForImageClassification",
        "SwinForMaskedImageModeling",
        "SwinModel",
        "SwinPreTrainedModel",
        "SwinBackbone",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFSwinForImageClassification",
        "TFSwinForMaskedImageModeling",
        "TFSwinModel",
        "TFSwinPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_swin import (
            SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
            SwinBackbone,
            SwinForImageClassification,
            SwinForMaskedImageModeling,
            SwinModel,
            SwinPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_swin import (
            TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFSwinForImageClassification,
            TFSwinForMaskedImageModeling,
            TFSwinModel,
            TFSwinPreTrainedModel,
        )

else:
    import sys

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


