code: 
  
  
  '''simple docstring'''
  
  from collections import namedtuple
  
  lowerCamelCase							:     Optional[int]								=			namedtuple('from_to', 'from_ to')
  
  lowerCamelCase							:     int								=			{
      'millimeter': 'mm',
      'centimeter': 'cm',
      'meter': 'm',
      'kilometer': 'km',
      'inch': 'in',
      'inche': 'in',  # Trailing 's' has been stripped off
      'feet': 'ft',
      'foot': 'ft',
      'yard': 'yd',
      'mile': 'mi',
  }
  
  lowerCamelCase							:     int								=			{
      'mm': from_to(0.0_0_1, 1_000),
      'cm': from_to(0.0_1, 100),
      'm': from_to(1, 1),
      'km': from_to(1_000, 0.0_0_1),
      'in': from_to(0.0_2_5_4, 3_9.3_7_0_1),
      'ft': from_to(0.3_0_4_8, 3.2_8_0_8_4),
      'yd': from_to(0.9_1_4_4, 1.0_9_3_6_1),
      'mi': from_to(1_6_0_9.3_4, 0.0_0_0_6_2_1_3_7_1),
  }
  
  def _SCREAMING_SNAKE_CASE   (A						,				A						,				A ) -> float:
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
  
         lowercase__       =				from_type.lower().rstrip('''s''' )
         lowercase__       =				TYPE_CONVERSION.get(A						,				A )
         lowercase__       =				to_type.lower().rstrip('''s''' )
         lowercase__       =				TYPE_CONVERSION.get(A						,				A )
         if new_from not in METRIC_CONVERSION:
                lowercase__       =				(
                    f"Invalid 'from_type' value: {from_type!r}.\n"
                    f"Conversion abbreviations are: {', '.join(A )}"
                )
                raise ValueError(A )
         if new_to not in METRIC_CONVERSION:
                lowercase__       =				(
                    f"Invalid 'to_type' value: {to_type!r}.\n"
                    f"Conversion abbreviations are: {', '.join(A )}"
                )
                raise ValueError(A )
         return value * METRIC_CONVERSION[new_from].from_ * METRIC_CONVERSION[new_to].to
  
  
  if __name__ == "__main__":
   import doctest
  
   doctest.testmod()
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  import torch
  
  from accelerate import Accelerator, DistributedType
  class 						__lowerCAmelCase		:
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        def __enter__(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if self.enabled:
                      lowercase__       =				self.model.no_sync()
                      self.model_sync_obj.__enter__()
  
               return self
  
  
  
        def __exit__(self					:					List[str]     ,		UpperCamelCase					:					List[Any]     ,		UpperCamelCase					:					Optional[int]     ,		UpperCamelCase					:					Optional[int]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if self.enabled:
                      # Average all models on exit
                      self._sync_and_avg_model_params()
                      self.model_sync_obj.__exit__(UpperCamelCase     ,		UpperCamelCase     ,		UpperCamelCase				)
  
  
  
        def __init__(self					:					Dict     ,		UpperCamelCase					:					Accelerator     ,		UpperCamelCase					:					torch.nn.Module     ,		UpperCamelCase					:					int     ,		UpperCamelCase					:					bool = True				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               if accelerator.distributed_type not in [
                   DistributedType.NO,
                   DistributedType.MULTI_CPU,
                   DistributedType.MULTI_GPU,
               ]:
                      raise NotImplementedError('''LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)'''				)
               lowercase__       =				enabled and accelerator.distributed_type != DistributedType.NO
               lowercase__       =				0
               if self.enabled:
                      lowercase__       =				accelerator
                      lowercase__       =				model
                      lowercase__       =				local_sgd_steps
  
  
  
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               self.num_steps += 1
               if not self.enabled:
                      return
  
               if self.num_steps % self.local_sgd_steps == 0:
                      self._sync_and_avg_model_params()
  
  
  
  
  
  
        def    UpperCamelCase__	(self					:					Any				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               self.accelerator.wait_for_everyone()
               with self.accelerator.autocast():
                      for param in self.model.parameters():
                             lowercase__       =				self.accelerator.reduce(param.data     ,		reduction='''mean'''				)
  
  
  
  
  