

"""simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy

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

class       lowerCamelCase	:


  '''simple docstring'''







  def __init__(self							,       _lowerCamelCase	):


        """simple docstring"""

        if isinstance(_lowerCamelCase							,       _lowerCamelCase	):
              # 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
              UpperCAmelCase__			:							Any							=    deepcopy(_lowerCamelCase	)
        elif os.path.exists(_lowerCamelCase	):
              with io.open(_lowerCamelCase							,       """r"""							,       encoding="""utf-8"""	) as f:
                    UpperCAmelCase__			:							Optional[Any]							=    json.load(_lowerCamelCase	)
        else:
              try:
                    UpperCAmelCase__			:							int							=    baseaa.urlsafe_baadecode(_lowerCamelCase	).decode("""utf-8"""	)
                    UpperCAmelCase__			:							Any							=    json.loads(_lowerCamelCase	)
              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}"""	)

        UpperCAmelCase__			:							Dict							=    config

        self.set_stage_and_offload()



  def  _a      (self	):


        """simple docstring"""

        UpperCAmelCase__			:							List[Any]							=    self.get_value("""zero_optimization.stage"""							,       -1	)

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



  def  _a      (self							,       _lowerCamelCase	):


        """simple docstring"""

        UpperCAmelCase__			:							int							=    self.config

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

        return config, ds_key



  def  _a      (self							,       _lowerCamelCase							,       _lowerCamelCase=None	):


        """simple docstring"""

        UpperCAmelCase__					,		UpperCAmelCase__			:							Optional[Any]							=    self.find_config_node(_lowerCamelCase	)
        if config is None:
              return default
        return config.get(_lowerCamelCase							,       _lowerCamelCase	)



  def  _a      (self							,       _lowerCamelCase							,       _lowerCamelCase=False	):


        """simple docstring"""

        UpperCAmelCase__			:							Any							=    self.config

        # find the config node of interest if it exists
        UpperCAmelCase__			:							Any							=    ds_key_long.split("""."""	)
        for node in nodes:
              UpperCAmelCase__			:							Optional[Any]							=    config
              UpperCAmelCase__			:							int							=    config.get(_lowerCamelCase	)
              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(_lowerCamelCase	)



  def  _a      (self							,       _lowerCamelCase	):


        """simple docstring"""

        UpperCAmelCase__			:							List[str]							=    self.get_value(_lowerCamelCase	)
        return False if value is None else bool(_lowerCamelCase	)



  def  _a      (self							,       _lowerCamelCase	):


        """simple docstring"""

        UpperCAmelCase__			:							Tuple							=    self.get_value(_lowerCamelCase	)
        return False if value is None else not bool(_lowerCamelCase	)



  def  _a      (self	):


        """simple docstring"""

        return self._stage == 2



  def  _a      (self	):


        """simple docstring"""

        return self._stage == 3




  def  _a      (self	):


        """simple docstring"""

        return self._offload




class       lowerCamelCase	:


  '''simple docstring'''







  def __init__(self							,       _lowerCamelCase	):


        """simple docstring"""

        UpperCAmelCase__			:							int							=    engine




  def  _a      (self							,       _lowerCamelCase							,       **_lowerCamelCase	):


        """simple docstring"""

        self.engine.backward(_lowerCamelCase							,       **_lowerCamelCase	)

        # 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       lowerCamelCase	(       lowerCAmelCase__   ):


  '''simple docstring'''







  def __init__(self							,       _lowerCamelCase	):


        """simple docstring"""

        super().__init__(_lowerCamelCase							,       device_placement=_lowerCamelCase							,       scaler=_lowerCamelCase	)
        UpperCAmelCase__			:							Any							=    hasattr(self.optimizer							,       """overflow"""	)



  def  _a      (self							,       _lowerCamelCase=None	):


        """simple docstring"""

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



  def  _a      (self	):


        """simple docstring"""

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




  @property
  def  _a      (self	):


        """simple docstring"""

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




class       lowerCamelCase	(       lowerCAmelCase__   ):


  '''simple docstring'''







  def __init__(self							,       _lowerCamelCase							,       _lowerCamelCase	):


        """simple docstring"""

        super().__init__(_lowerCamelCase							,       _lowerCamelCase	)




  def  _a      (self	):


        """simple docstring"""

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




class       lowerCamelCase	:


  '''simple docstring'''







  def __init__(self							,       _lowerCamelCase							,       _lowerCamelCase=0.001							,       _lowerCamelCase=0							,       **_lowerCamelCase	):


        """simple docstring"""

        UpperCAmelCase__			:							Any							=    params
        UpperCAmelCase__			:							Tuple							=    lr
        UpperCAmelCase__			:							str							=    weight_decay
        UpperCAmelCase__			:							List[str]							=    kwargs




class       lowerCamelCase	:


  '''simple docstring'''







  def __init__(self							,       _lowerCamelCase							,       _lowerCamelCase=None							,       _lowerCamelCase=0							,       **_lowerCamelCase	):


        """simple docstring"""

        UpperCAmelCase__			:							str							=    optimizer
        UpperCAmelCase__			:							Any							=    total_num_steps
        UpperCAmelCase__			:							Any							=    warmup_num_steps
        UpperCAmelCase__			:							Optional[int]							=    kwargs




"""simple docstring"""
def 					a__						(						)	-> Union[str, Any]:
      UpperCAmelCase__			:							Dict							=    []
      UpperCAmelCase__			:							Tuple							=    1

      while len(lowerCAmelCase    ) < 1E6:
            constant.append(str(lowerCAmelCase    )    )
            i += 1

      UpperCAmelCase__			:							Any							=    """""".join(lowerCAmelCase    )

      return (
          int(constant[0]    )
          * int(constant[9]    )
          * int(constant[99]    )
          * int(constant[9_99]    )
          * int(constant[99_99]    )
          * int(constant[9_99_99]    )
          * int(constant[99_99_99]    )
      )


if __name__ == "__main__":
    print(solution())

