




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

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




class 		__lowercase						:




      """simple docstring"""





      def __init__( self							, A      )						->							int:

         if isinstance(_SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE      ):
            # 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 :							List[str]           =			deepcopy(_SCREAMING_SNAKE_CASE      )
         elif os.path.exists(_SCREAMING_SNAKE_CASE      ):
            with io.open(_SCREAMING_SNAKE_CASE							, """r"""							, encoding="""utf-8"""      ) as f:
               snake_case :							Any           =			json.load(_SCREAMING_SNAKE_CASE      )
         else:
            try:
               snake_case :							Optional[int]           =			baseaa.urlsafe_baadecode(_SCREAMING_SNAKE_CASE      ).decode("""utf-8"""      )
               snake_case :							int           =			json.loads(_SCREAMING_SNAKE_CASE      )
            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       UpperCAmelCase ( self      )						->							Optional[int]:
         snake_case :							Optional[int]           =			self.get_value("""zero_optimization.stage"""							, -1      )

         # offload
         snake_case :							List[Any]           =			False
         if self.is_zeroa() or self.is_zeroa():
            snake_case :							Optional[Any]           =			set(["""cpu""", """nvme"""]      )
            snake_case :							Dict           =			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 :							Dict           =			True

      def       UpperCAmelCase ( self							, A      )						->							List[Any]:
         snake_case :							Optional[Any]           =			self.config

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

         return config, ds_key

      def       UpperCAmelCase ( self							, A							, A=None      )						->							Dict:
         snake_case      ,   snake_case :							Optional[int]           =			self.find_config_node(_SCREAMING_SNAKE_CASE      )
         if config is None:
            return default
         return config.get(_SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE      )

      def       UpperCAmelCase ( self							, A							, A=False      )						->							List[str]:
         snake_case :							str           =			self.config

         # find the config node of interest if it exists
         snake_case :							Tuple           =			ds_key_long.split("""."""      )
         for node in nodes:
            snake_case :							Dict           =			config
            snake_case :							List[Any]           =			config.get(_SCREAMING_SNAKE_CASE      )
            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(_SCREAMING_SNAKE_CASE      )

      def       UpperCAmelCase ( self							, A      )						->							Optional[Any]:
         snake_case :							Optional[Any]           =			self.get_value(_SCREAMING_SNAKE_CASE      )
         return False if value is None else bool(_SCREAMING_SNAKE_CASE      )

      def       UpperCAmelCase ( self							, A      )						->							Optional[int]:
         snake_case :							Optional[int]           =			self.get_value(_SCREAMING_SNAKE_CASE      )
         return False if value is None else not bool(_SCREAMING_SNAKE_CASE      )

      def       UpperCAmelCase ( self      )						->							Optional[Any]:
         return self._stage == 2

      def       UpperCAmelCase ( self      )						->							Optional[int]:
         return self._stage == 3

      def       UpperCAmelCase ( self      )						->							str:
         return self._offload




class 		__lowercase						:




      """simple docstring"""





      def __init__( self							, A      )						->							Union[str, Any]:
         snake_case :							List[str]           =			engine

      def       UpperCAmelCase ( self							, A							, **A      )						->							Dict:
         self.engine.backward(_SCREAMING_SNAKE_CASE							, **_SCREAMING_SNAKE_CASE      )

         # 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_				):




      """simple docstring"""





      def __init__( self							, A      )						->							Dict:
         super().__init__(_SCREAMING_SNAKE_CASE							, device_placement=_SCREAMING_SNAKE_CASE							, scaler=_SCREAMING_SNAKE_CASE      )
         snake_case :							List[Any]           =			hasattr(self.optimizer							, """overflow"""      )

      def       UpperCAmelCase ( self							, A=None      )						->							Optional[int]:
         pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed

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

      @property
      def       UpperCAmelCase ( self      )						->							int:

         if self.__has_overflow__:
            return self.optimizer.overflow
         return False




class 		__lowercase						(a_				):




      """simple docstring"""





      def __init__( self							, A							, A      )						->							List[Any]:
         super().__init__(_SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE      )

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




class 		__lowercase						:




      """simple docstring"""





      def __init__( self							, A							, A=0.0_01							, A=0							, **A      )						->							Union[str, Any]:
         snake_case :							Any           =			params
         snake_case :							Optional[int]           =			lr
         snake_case :							str           =			weight_decay
         snake_case :							Optional[int]           =			kwargs




class 		__lowercase						:




      """simple docstring"""





      def __init__( self							, A							, A=None							, A=0							, **A      )						->							Dict:
         snake_case :							Optional[int]           =			optimizer
         snake_case :							Optional[Any]           =			total_num_steps
         snake_case :							Union[str, Any]           =			warmup_num_steps
         snake_case :							int           =			kwargs








'''simple docstring'''



def       snake_case   (	snake_case      : list			) ->  list:


    """simple docstring"""


    if any(not isinstance(snake_case					,		snake_case			) or x < 0 for x in sequence			):
        raise TypeError('Sequence must be list of non-negative integers'			)
    for _ in range(len(snake_case			)			):
        for i, (rod_upper, rod_lower) in enumerate(zip(snake_case					,		sequence[1:]			)			):
            if rod_upper > rod_lower:
                sequence[i] -= rod_upper - rod_lower
                sequence[i + 1] += rod_upper - rod_lower
    return sequence


if __name__ == "__main__":
     assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
     assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]





