






from typing import TYPE_CHECKING

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


UpperCamelCase								=		{
    "configuration_efficientformer": [
        "EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientFormerConfig",
    ]
}

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

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

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase								=		[
							    "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

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






def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     list				)			->						float:
       SCREAMING_SNAKE_CASE_							:				Dict		=0
       while len(UpperCAmelCase_				) > 1:
              SCREAMING_SNAKE_CASE_							:				Tuple		=0
              # Consider two files with minimum cost to be merged
              for _ in range(2				):
                     SCREAMING_SNAKE_CASE_							:				int		=files.index(min(UpperCAmelCase_				)				)
                     temp += files[min_index]
                     files.pop(UpperCAmelCase_				)
              files.append(UpperCAmelCase_				)
              optimal_merge_cost += temp
       return optimal_merge_cost


if __name__ == "__main__":
 import doctest

 doctest.testmod()
