






import baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler







class  _lowercase   :
      def __init__(     self				,			a   ):
       if isinstance(a				,			a   ):
        # Don't modify user's data should they want to reuse it (e.g. in tests), because once we
        # modified it, it will not be accepted here again, since `auto` values would have been overridden
        snake_case__  :    Optional[Any]							       =deepcopy(a   )
       elif os.path.exists(a   ):
        with io.open(a				,			"""r"""				,			encoding="""utf-8"""   ) as f:
         snake_case__  :    Tuple							       =json.load(a   )
       else:
        try:
         snake_case__  :    int							       =baseaa.urlsafe_baadecode(a   ).decode("""utf-8"""   )
         snake_case__  :    str							       =json.loads(a   )
        except (UnicodeDecodeError, AttributeError, ValueError):
         raise ValueError(
             F"Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}"   )

       snake_case__  :    Union[str, Any]							       =config

       self.set_stage_and_offload()
      def 						lowercase__					(     self   ):
       # zero stage - this is done as early as possible, before model is created, to allow
       # ``is_deepspeed_zero3_enabled`` query and getting to the early deepspeed config object
       # during ``zero.Init()`` which needs to know the dtype, and some other hparams.
       snake_case__  :    Tuple							       =self.get_value("""zero_optimization.stage"""				,			-1   )

       # offload
       snake_case__  :    Optional[int]							       =False
       if self.is_zeroa() or self.is_zeroa():
        snake_case__  :    Union[str, Any]							       =set(["""cpu""", """nvme"""]   )
        snake_case__  :    int							       =set(
            [
                self.get_value("""zero_optimization.offload_optimizer.device"""   ),
                self.get_value("""zero_optimization.offload_param.device"""   ),
            ]   )
        if len(offload_devices & offload_devices_valid   ) > 0:
         snake_case__  :    Tuple							       =True
      def 						lowercase__					(     self				,			a   ):
       snake_case__  :    List[Any]							       =self.config

       # find the config node of interest if it exists
       snake_case__  :    Optional[Any]							       =ds_key_long.split("""."""   )
       snake_case__  :    Optional[Any]							       =nodes.pop()
       for node in nodes:
        snake_case__  :    Dict							       =config.get(a   )
        if config is None:
         return None, ds_key

       return config, ds_key
      def 						lowercase__					(     self				,			a				,			a=None   ):
       snake_case__  :    Tuple							       =self.find_config_node(a   )
       if config is None:
        return default
       return config.get(a				,			a   )
      def 						lowercase__					(     self				,			a				,			a=False   ):
       snake_case__  :    Tuple							       =self.config

       # find the config node of interest if it exists
       snake_case__  :    List[Any]							       =ds_key_long.split("""."""   )
       for node in nodes:
        snake_case__  :    List[str]							       =config
        snake_case__  :    Tuple							       =config.get(a   )
        if config is None:
         if must_exist:
          raise ValueError(F"Can't find {ds_key_long} entry in the config: {self.config}"   )
         else:
          return

        # if found remove it
       if parent_config is not None:
        parent_config.pop(a   )
      def 						lowercase__					(     self				,			a   ):
       snake_case__  :    int							       =self.get_value(a   )
       return False if value is None else bool(a   )
      def 						lowercase__					(     self				,			a   ):
       snake_case__  :    Union[str, Any]							       =self.get_value(a   )
       return False if value is None else not bool(a   )
      def 						lowercase__					(     self   ):
       return self._stage == 2
      def 						lowercase__					(     self   ):
       return self._stage == 3



      def 						lowercase__					(     self   ):
       return self._offload







class  _lowercase   :
      def __init__(     self				,			a   ):
       snake_case__  :    Optional[Any]							       =engine



      def 						lowercase__					(     self				,			a				,			**a   ):
       # runs backpropagation and handles mixed precision
       self.engine.backward(a				,			**a   )

       # Deepspeed's `engine.step` performs the following operations:
       # - gradient accumulation check
       # - gradient clipping
       # - optimizer step
       # - zero grad
       # - checking overflow
       # - lr_scheduler step (only if engine.lr_scheduler is not None)
       self.engine.step()
       # and this plugin overrides the above calls with no-ops when Accelerate runs under
       # Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
       # training loop that works transparently under many training regimes.







class  _lowercase   (   _A						):
      def __init__(     self				,			a   ):
       super().__init__(a				,			device_placement=a				,			scaler=a   )
       snake_case__  :    str							       =hasattr(self.optimizer				,			"""overflow"""   )
      def 						lowercase__					(     self				,			a=None   ):
       pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed
      def 						lowercase__					(     self   ):
       pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed



      @property
      def 						lowercase__					(     self   ):
       if self.__has_overflow__:
        return self.optimizer.overflow
       return False







class  _lowercase   (   _A						):
      def __init__(     self				,			a				,			a   ):
       super().__init__(a				,			a   )



      def 						lowercase__					(     self   ):
       pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed







class  _lowercase   :
      def __init__(     self				,			a				,			a=0.001				,			a=0				,			**a   ):
       snake_case__  :    Tuple							       =params
       snake_case__  :    int							       =lr
       snake_case__  :    List[str]							       =weight_decay
       snake_case__  :    List[str]							       =kwargs







class  _lowercase   :
      def __init__(     self				,			a				,			a=None				,			a=0				,			**a   ):
       snake_case__  :    Tuple							       =optimizer
       snake_case__  :    int							       =total_num_steps
       snake_case__  :    str							       =warmup_num_steps
       snake_case__  :    Dict							       =kwargs













def 			A__							(      _a  :					Optional[Any]		,  _a  :					Tuple		,  _a  :					List[str]=False	):





 '''simple docstring'''







 if isinstance(_a		,  _a	) and isinstance(_a		,  _a	):
  snake_case__  :    int							       =len(set_a.intersection(_a	)	)

  if alternative_union:
   snake_case__  :    int							       =len(_a	) + len(_a	)
  else:
   snake_case__  :    Tuple							       =len(set_a.union(_a	)	)

  return intersection / union

 if isinstance(_a		,  (list, tuple)	) and isinstance(_a		,  (list, tuple)	):
  snake_case__  :    Optional[int]							       =[element for element in set_a if element in set_b]

  if alternative_union:
   snake_case__  :    Optional[Any]							       =len(_a	) + len(_a	)
   return len(_a	) / union
  else:
   snake_case__  :    Dict							       =set_a + [element for element in set_b if element not in set_a]
   return len(_a	) / len(_a	)

  return len(_a	) / len(_a	)
 return None


if __name__ == "__main__":
       __lowerCamelCase	:		List[Any]										=   {"""a""", """b""", """c""", """d""", """e"""}
       __lowerCamelCase	:		Optional[int]										=   {"""c""", """d""", """e""", """f""", """h""", """i"""}
       print(jaccard_similarity(set_a, set_b))





