


"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


A	:  Union[str, Any]            =     {
    "configuration_efficientformer": [
        "EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientFormerConfig",
    ]
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:  Optional[int]            =     ["EfficientFormerImageProcessor"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:  List[str]            =     [
	    "EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "EfficientFormerForImageClassification",
	    "EfficientFormerForImageClassificationWithTeacher",
	    "EfficientFormerModel",
	    "EfficientFormerPreTrainedModel",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:  Tuple            =     [
	    "TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFEfficientFormerForImageClassification",
	    "TFEfficientFormerForImageClassificationWithTeacher",
	    "TFEfficientFormerModel",
	    "TFEfficientFormerPreTrainedModel",
	]

if TYPE_CHECKING:
	from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .image_processing_efficientformer import EfficientFormerImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_efficientformer import (
		    EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    EfficientFormerForImageClassification,
		    EfficientFormerForImageClassificationWithTeacher,
		    EfficientFormerModel,
		    EfficientFormerPreTrainedModel,
		)
	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_efficientformer import (
		    TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFEfficientFormerForImageClassification,
		    TFEfficientFormerForImageClassificationWithTeacher,
		    TFEfficientFormerModel,
		    TFEfficientFormerPreTrainedModel,
		)

else:
	import sys

	A	:  str            =     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








"""simple docstring"""


import baseaa


def _lowerCamelCase      (						_UpperCamelCase ):

			'''simple docstring'''




			return baseaa.baaencode(string.encode("utf-8" ) )


def _lowerCamelCase      (						_UpperCamelCase ):

			'''simple docstring'''




			return baseaa.baadecode(_UpperCamelCase ).decode("utf-8" )


if __name__ == "__main__":
	A	:  List[str]            =     "Hello World!"
	A	:  Any            =     baseaa_encode(test)
	print(encoded)

	A	:  List[Any]            =     baseaa_decode(encoded)
	print(decoded)




