

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

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






class 						__magic_name__					:






     def __init__(				self		,						_lowercase	)->     Dict:
         if isinstance(_lowercase		,						_lowercase	):
             # 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_			  =						deepcopy(_lowercase	)
         elif os.path.exists(_lowercase	):
             with io.open(_lowercase		,						"r"		,						encoding="utf-8"	) as f:
                 UpperCamelCase_			  =						json.load(_lowercase	)
         else:
             try:
                 UpperCamelCase_			  =						baseaa.urlsafe_baadecode(_lowercase	).decode("utf-8"	)
                 UpperCamelCase_			  =						json.loads(_lowercase	)
             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_			  =						config

         self.set_stage_and_offload()






     def 	UpperCAmelCase_				(				self	)->     Optional[Any]:
         # 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.
         UpperCamelCase_			  =						self.get_value("zero_optimization.stage"		,						-1	)

         # offload
         UpperCamelCase_			  =						False
         if self.is_zeroa() or self.is_zeroa():
             UpperCamelCase_			  =						set(["cpu", "nvme"]	)
             UpperCamelCase_			  =						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_			  =						True






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     int:
         UpperCamelCase_			  =						self.config

         # find the config node of interest if it exists
         UpperCamelCase_			  =						ds_key_long.split("."	)
         UpperCamelCase_			  =						nodes.pop()
         for node in nodes:
             UpperCamelCase_			  =						config.get(_lowercase	)
             if config is None:
                 return None, ds_key

         return config, ds_key






     def 	UpperCAmelCase_				(				self		,						_lowercase		,						_lowercase=None	)->     Any:
         UpperCamelCase_  ,       UpperCamelCase_			  =						self.find_config_node(_lowercase	)
         if config is None:
             return default
         return config.get(_lowercase		,						_lowercase	)






     def 	UpperCAmelCase_				(				self		,						_lowercase		,						_lowercase=False	)->     int:
         UpperCamelCase_			  =						self.config

         # find the config node of interest if it exists
         UpperCamelCase_			  =						ds_key_long.split("."	)
         for node in nodes:
             UpperCamelCase_			  =						config
             UpperCamelCase_			  =						config.get(_lowercase	)
             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(_lowercase	)






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     Any:
         UpperCamelCase_			  =						self.get_value(_lowercase	)
         return False if value is None else bool(_lowercase	)






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     Any:
         UpperCamelCase_			  =						self.get_value(_lowercase	)
         return False if value is None else not bool(_lowercase	)






     def 	UpperCAmelCase_				(				self	)->     Any:
         return self._stage == 2






     def 	UpperCAmelCase_				(				self	)->     Any:
         return self._stage == 3






     def 	UpperCAmelCase_				(				self	)->     Dict:
         return self._offload






class 						__magic_name__					:






     def __init__(				self		,						_lowercase	)->     List[Any]:
         UpperCamelCase_			  =						engine






     def 	UpperCAmelCase_				(				self		,						_lowercase		,						**_lowercase	)->     Union[str, Any]:
         # runs backpropagation and handles mixed precision
         self.engine.backward(_lowercase		,						**_lowercase	)

         # 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 						__magic_name__					(							snake_case				):






     def __init__(				self		,						_lowercase	)->     int:
         super().__init__(_lowercase		,						device_placement=_lowercase		,						scaler=_lowercase	)
         UpperCamelCase_			  =						hasattr(self.optimizer		,						"overflow"	)






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






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






     @property
     def 	UpperCAmelCase_				(				self	)->     Tuple:
         if self.__has_overflow__:
             return self.optimizer.overflow
         return False






class 						__magic_name__					(							snake_case				):






     def __init__(				self		,						_lowercase		,						_lowercase	)->     Tuple:
         super().__init__(_lowercase		,						_lowercase	)






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






class 						__magic_name__					:






     def __init__(				self		,						_lowercase		,						_lowercase=0.001		,						_lowercase=0		,						**_lowercase	)->     Optional[Any]:
         UpperCamelCase_			  =						params
         UpperCamelCase_			  =						lr
         UpperCamelCase_			  =						weight_decay
         UpperCamelCase_			  =						kwargs






class 						__magic_name__					:






     def __init__(				self		,						_lowercase		,						_lowercase=None		,						_lowercase=0		,						**_lowercase	)->     Dict:
         UpperCamelCase_			  =						optimizer
         UpperCamelCase_			  =						total_num_steps
         UpperCamelCase_			  =						warmup_num_steps
         UpperCamelCase_			  =						kwargs



def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)->						int:



    """simple docstring"""






    if exponent == 1:
        return base
    if exponent % 2 == 0:
        UpperCamelCase_			  =						_modexpt(SCREAMING_SNAKE_CASE_			,						exponent // 2			,						SCREAMING_SNAKE_CASE_			) % modulo_value
        return (x * x) % modulo_value
    else:
        return (base * _modexpt(SCREAMING_SNAKE_CASE_			,						exponent - 1			,						SCREAMING_SNAKE_CASE_			)) % modulo_value




def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_ = 1_7_7_7			,						SCREAMING_SNAKE_CASE_ = 1_8_5_5			,						SCREAMING_SNAKE_CASE_ = 8			)->						int:



    """simple docstring"""






    UpperCamelCase_			  =						base
    for _ in range(1			,						SCREAMING_SNAKE_CASE_			):
        UpperCamelCase_			  =						_modexpt(SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						1_0**digits			)

    return result


if __name__ == "__main__":
 print(F'''{solution() = }''')
