'''simple docstring'''





from collections import namedtuple

SCREAMING_SNAKE_CASE_:					Tuple  =namedtuple('from_to', 'from_ to')

SCREAMING_SNAKE_CASE_:					Union[str, Any]  ={
    'cubicmeter': from_to(1, 1),
    'litre': from_to(0.001, 10_00),
    'kilolitre': from_to(1, 1),
    'gallon': from_to(0.00454, 264.172),
    'cubicyard': from_to(0.76455, 1.30795),
    'cubicfoot': from_to(0.028, 35.3147),
    'cup': from_to(0.000236588, 4226.75),
}





def      lowerCAmelCase_    ( snake_case_	:			float ,   snake_case_	:			str ,   snake_case_	:			str      )   ->				float:


     '''simple docstring'''




     if from_type not in METRIC_CONVERSION:
          raise ValueError(
              f"""Invalid 'from_type' value: {from_type!r}  Supported values are:\n"""
              + ", ".join(snake_case_      )      )
     if to_type not in METRIC_CONVERSION:
          raise ValueError(
              f"""Invalid 'to_type' value: {to_type!r}.  Supported values are:\n"""
              + ", ".join(snake_case_      )      )
     return value * METRIC_CONVERSION[from_type].from_ * METRIC_CONVERSION[to_type].to


if __name__ == "__main__":
    import doctest

    doctest.testmod()





'''simple docstring'''





from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_:					int  ={
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					List[str]  =['MaskFormerFeatureExtractor']
    SCREAMING_SNAKE_CASE_:					Union[str, Any]  =['MaskFormerImageProcessor']


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					Dict  =[
        'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
        'MaskFormerForInstanceSegmentation',
        'MaskFormerModel',
        'MaskFormerPreTrainedModel',
    ]
    SCREAMING_SNAKE_CASE_:					List[str]  =[
        'MaskFormerSwinBackbone',
        'MaskFormerSwinModel',
        'MaskFormerSwinPreTrainedModel',
    ]

if TYPE_CHECKING:
    from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
    from .configuration_maskformer_swin import MaskFormerSwinConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_maskformer import MaskFormerFeatureExtractor
        from .image_processing_maskformer import MaskFormerImageProcessor
    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_maskformer import (
            MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            MaskFormerForInstanceSegmentation,
            MaskFormerModel,
            MaskFormerPreTrainedModel,
        )
        from .modeling_maskformer_swin import (
            MaskFormerSwinBackbone,
            MaskFormerSwinModel,
            MaskFormerSwinPreTrainedModel,
        )


else:
    import sys

    SCREAMING_SNAKE_CASE_:					Dict  =_LazyModule(__name__, globals()['__file__'], _import_structure)




