code: 
  
  
  
  
  
  
  """simple docstring"""
  snake_case   :   dict[str, float]    		=		{
      "kilogram": 1,
      "gram": pow(1_0, 3),
      "milligram": pow(1_0, 6),
      "metric-ton": pow(1_0, -3),
      "long-ton": 0.00_09_84_20_73,
      "short-ton": 0.00_11_02_31_22,
      "pound": 2.20_46_24_42_02,
      "stone": 0.15_74_73_17_28,
      "ounce": 35.2_73_99_07_23,
      "carrat": 5_0_0_0,
      "atomic-mass-unit": 6.0_22_13_66_52E26,
  }
  
  snake_case   :   dict[str, float]    		=		{
      "kilogram": 1,
      "gram": pow(1_0, -3),
      "milligram": pow(1_0, -6),
      "metric-ton": pow(1_0, 3),
      "long-ton": 10_16.0_46_08,
      "short-ton": 9_07.1_84,
      "pound": 0.45_35_92,
      "stone": 6.3_50_29,
      "ounce": 0.0_28_34_95,
      "carrat": 0.00_02,
      "atomic-mass-unit": 1.6_60_54_01_99E-27,
  }
  
  
  def        A	(							__snake_case:   str   ,    __snake_case:   str   ,    __snake_case:   float     )						->		float:
  
         """simple docstring"""
  
  
  
  
  
         if to_type not in KILOGRAM_CHART or from_type not in WEIGHT_TYPE_CHART:
                __magic_name__										=						(
                    F"""Invalid 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"""
                    F"""Supported values are: {", ".join(__snake_case     )}"""
                )
                raise ValueError(__snake_case     )
         return value * KILOGRAM_CHART[to_type] * WEIGHT_TYPE_CHART[from_type]
  
  
  if __name__ == "__main__":
   import doctest
  
   doctest.testmod()
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  snake_case   :   Optional[int]    		=		{
      """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
      """tokenization_splinter""": ["""SplinterTokenizer"""],
  }
  
  try:
   if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   snake_case   :   Dict    		=		["""SplinterTokenizerFast"""]
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   snake_case   :   Dict    		=		[
       """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """SplinterForQuestionAnswering""",
       """SplinterForPreTraining""",
       """SplinterLayer""",
       """SplinterModel""",
       """SplinterPreTrainedModel""",
   ]
  
  
  if TYPE_CHECKING:
   from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
   from .tokenization_splinter import SplinterTokenizer
  
   try:
    if not is_tokenizers_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .tokenization_splinter_fast import SplinterTokenizerFast
  
   try:
    if not is_torch_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_splinter import (
        SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
        SplinterForPreTraining,
        SplinterForQuestionAnswering,
        SplinterLayer,
        SplinterModel,
        SplinterPreTrainedModel,
    )
  
  
  else:
   import sys
  
   snake_case   :   List[str]    		=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)