





"""simple docstring"""





from typing import TYPE_CHECKING

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


_lowerCamelCase  					=     {
    "configuration_segformer": ["SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SegformerConfig", "SegformerOnnxConfig"]
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase  					=     ["SegformerFeatureExtractor"]
    _lowerCamelCase  					=     ["SegformerImageProcessor"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase  					=     [
        "SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SegformerDecodeHead",
        "SegformerForImageClassification",
        "SegformerForSemanticSegmentation",
        "SegformerLayer",
        "SegformerModel",
        "SegformerPreTrainedModel",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase  					=     [
        "TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFSegformerDecodeHead",
        "TFSegformerForImageClassification",
        "TFSegformerForSemanticSegmentation",
        "TFSegformerModel",
        "TFSegformerPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig, SegformerOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_segformer import SegformerFeatureExtractor
        from .image_processing_segformer import SegformerImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_segformer import (
            SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            SegformerDecodeHead,
            SegformerForImageClassification,
            SegformerForSemanticSegmentation,
            SegformerLayer,
            SegformerModel,
            SegformerPreTrainedModel,
        )
    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_segformer import (
            TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFSegformerDecodeHead,
            TFSegformerForImageClassification,
            TFSegformerForSemanticSegmentation,
            TFSegformerModel,
            TFSegformerPreTrainedModel,
        )

else:
    import sys

    _lowerCamelCase  					=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








"""simple docstring"""





def 		lowerCAmelCase_     (  lowercase_       :							int = 30		):

 '''simple docstring'''






 __SCREAMING_SNAKE_CASE			:      str 							=	exponent + 2
 __SCREAMING_SNAKE_CASE			:      Optional[Any] 							=	(1 + 5**0.5) / 2
 __SCREAMING_SNAKE_CASE			:      Optional[int] 							=	(phi**fibonacci_index - (phi - 1) ** fibonacci_index) / 5**0.5

 return int(lowercase_		)


if __name__ == "__main__":
    print(f'{solution() = }')

