


'''simple docstring'''

lowerCamelCase							:     Optional[Any]								=			{
    '0000': '0',
    '0001': '1',
    '0010': '2',
    '0011': '3',
    '0100': '4',
    '0101': '5',
    '0110': '6',
    '0111': '7',
    '1000': '8',
    '1001': '9',
    '1010': 'a',
    '1011': 'b',
    '1100': 'c',
    '1101': 'd',
    '1110': 'e',
    '1111': 'f',
}

def _SCREAMING_SNAKE_CASE   (A ) -> str:






       """simple docstring"""







       lowercase__       =				str(A ).strip()

       # Exceptions
       if not binary_str:
              raise ValueError('''Empty string was passed to the function''' )
       lowercase__       =				binary_str[0] == '''-'''
       lowercase__       =				binary_str[1:] if is_negative else binary_str
       if not all(char in '''01''' for char in binary_str ):
              raise ValueError('''Non-binary value was passed to the function''' )

       lowercase__       =				(
           '''0''' * (4 * (divmod(len(A )						,				4 )[0] + 1) - len(A )) + binary_str
       )

       lowercase__       =				[]
       for x in range(0						,				len(A )						,				4 ):
              hexadecimal.append(BITS_TO_HEX[binary_str[x : x + 4]] )
       lowercase__       =				'''0x''' + ''''''.join(A )

       return "-" + hexadecimal_str if is_negative else hexadecimal_str


if __name__ == "__main__":
 from doctest import testmod

 testmod()








'''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'''				)




