



"""simple docstring"""





from typing import TYPE_CHECKING

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


lowerCamelCase      =   {
    """configuration_convnext""": ["""CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ConvNextConfig""", """ConvNextOnnxConfig"""]
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase      =   ["""ConvNextFeatureExtractor"""]
  lowerCamelCase      =   ["""ConvNextImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase      =   [
      """CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """ConvNextForImageClassification""",
      """ConvNextModel""",
      """ConvNextPreTrainedModel""",
      """ConvNextBackbone""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase      =   [
      """TFConvNextForImageClassification""",
      """TFConvNextModel""",
      """TFConvNextPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_convnext import ConvNextFeatureExtractor
    from .image_processing_convnext import ConvNextImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_convnext import (
        CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
        ConvNextBackbone,
        ConvNextForImageClassification,
        ConvNextModel,
        ConvNextPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
  import sys

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









"""simple docstring"""





lowerCamelCase      =		{
    "joule": 1.0,
    "kilojoule": 1_000,
    "megajoule": 1_000_000,
    "gigajoule": 1_000_000_000,
    "wattsecond": 1.0,
    "watthour": 3_600,
    "kilowatthour": 3_600_000,
    "newtonmeter": 1.0,
    "calorie_nutr": 4_186.8,
    "kilocalorie_nutr": 4_186_800.00,
    "electronvolt": 1.6_0_2_1_7_6_6_3_4e-1_9,
    "britishthermalunit_it": 1_055.05_585,
    "footpound": 1.355_818,
}
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
            UpperCAmelCase_    				=							(
                f"""Incorrect 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"""
                f"""Valid values are: {', '.join(lowerCAmelCase__   )}"""
            )
            raise ValueError(lowerCAmelCase__   )
      return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
  import doctest

  doctest.testmod()




