






"""simple docstring"""





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				:	List[Any]							,   a				:	List[Any]						):





            """simple docstring"""







            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      :    List[str]  			=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      :    Dict  			=baseaa.urlsafe_baadecode(a						).decode('''utf-8'''						)
                        __snake_case      :    List[Any]  			=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      :    List[Any]  			=config

            self.set_stage_and_offload()


      def _UpperCamelCase						(    self				:	str						):





            """simple docstring"""







            __snake_case      :    Any  			=self.get_value('''zero_optimization.stage'''							,   -1						)

            # offload
            __snake_case      :    Optional[int]  			=False
            if self.is_zeroa() or self.is_zeroa():
                  __snake_case      :    Any  			=set(['''cpu''', '''nvme''']						)
                  __snake_case      :    Union[str, Any]  			=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      :    Optional[int]  			=True


      def _UpperCamelCase						(    self				:	List[Any]							,   a				:	List[Any]						):





            """simple docstring"""







            __snake_case      :    List[str]  			=self.config

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

            return config, ds_key


      def _UpperCamelCase						(    self				:	Optional[Any]							,   a				:	Any							,   a				:	str=None						):





            """simple docstring"""







            __snake_case			,				__snake_case      :    Any  			=self.find_config_node(a						)
            if config is None:
                  return default
            return config.get(a							,   a						)


      def _UpperCamelCase						(    self				:	int							,   a				:	List[Any]							,   a				:	Dict=False						):





            """simple docstring"""







            __snake_case      :    Optional[Any]  			=self.config

            # find the config node of interest if it exists
            __snake_case      :    Optional[int]  			=ds_key_long.split('''.'''						)
            for node in nodes:
                  __snake_case      :    int  			=config
                  __snake_case      :    Dict  			=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 _UpperCamelCase						(    self				:	List[Any]							,   a				:	List[str]						):





            """simple docstring"""







            __snake_case      :    int  			=self.get_value(a						)
            return False if value is None else bool(a						)


      def _UpperCamelCase						(    self				:	str							,   a				:	int						):





            """simple docstring"""







            __snake_case      :    int  			=self.get_value(a						)
            return False if value is None else not bool(a						)


      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







            return self._stage == 2


      def _UpperCamelCase						(    self				:	Optional[int]						):





            """simple docstring"""







            return self._stage == 3







      def _UpperCamelCase						(    self				:	Union[str, Any]						):





            """simple docstring"""







            return self._offload



class      _lowercase :


      def __init__(    self				:	Optional[int]							,   a				:	Union[str, Any]						):





            """simple docstring"""







            __snake_case      :    Tuple  			=engine







      def _UpperCamelCase						(    self				:	Optional[int]							,   a				:	str							,   **a				:	Union[str, Any]						):





            """simple docstring"""







            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 (     lowerCAmelCase						):


      def __init__(    self				:	Optional[Any]							,   a				:	int						):





            """simple docstring"""







            super().__init__(a							,   device_placement=a							,   scaler=a						)
            __snake_case      :    Optional[Any]  			=hasattr(self.optimizer							,   '''overflow'''						)


      def _UpperCamelCase						(    self				:	Dict							,   a				:	List[Any]=None						):





            """simple docstring"""







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


      def _UpperCamelCase						(    self				:	int						):





            """simple docstring"""







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







      @property
      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







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



class      _lowercase (     lowerCAmelCase						):


      def __init__(    self				:	Tuple							,   a				:	int							,   a				:	str						):





            """simple docstring"""







            super().__init__(a							,   a						)







      def _UpperCamelCase						(    self				:	List[str]						):





            """simple docstring"""







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



class      _lowercase :


      def __init__(    self				:	Union[str, Any]							,   a				:	Union[str, Any]							,   a				:	Dict=0.0_0_1							,   a				:	List[Any]=0							,   **a				:	Dict						):





            """simple docstring"""







            __snake_case      :    Optional[Any]  			=params
            __snake_case      :    List[str]  			=lr
            __snake_case      :    List[Any]  			=weight_decay
            __snake_case      :    int  			=kwargs



class      _lowercase :


      def __init__(    self				:	Optional[int]							,   a				:	int							,   a				:	Union[str, Any]=None							,   a				:	List[str]=0							,   **a				:	List[Any]						):





            """simple docstring"""







            __snake_case      :    List[Any]  			=optimizer
            __snake_case      :    List[Any]  			=total_num_steps
            __snake_case      :    Optional[Any]  			=warmup_num_steps
            __snake_case      :    Union[str, Any]  			=kwargs










"""simple docstring"""





from __future__ import annotations



def     __lowercase					(    a :				int       ,		a :				int )					->					list[str]:
      if partitions <= 0:
            raise ValueError('''partitions must be a positive number!''' )
      if partitions > number_of_bytes:
            raise ValueError('''partitions can not > number_of_bytes!''' )
      __snake_case      :    List[str]  			=number_of_bytes // partitions
      __snake_case      :    str  			=[]
      for i in range(a ):
            __snake_case      :    Optional[Any]  			=i * bytes_per_partition + 1
            __snake_case      :    Any  			=(
                number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
            )
            allocation_list.append(f'''{start_bytes}-{end_bytes}''' )
      return allocation_list


if __name__ == "__main__":
    import doctest

    doctest.testmod()


