





'''simple docstring'''

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

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

class       UpperCAmelCase :




		def __init__(self      :	List[Any]							,			A__      :	int				)					-> Dict:
						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
										lowercase         = deepcopy(A__				)
						elif os.path.exists(A__				):
										with io.open(A__							,			"r"							,			encoding="utf-8"				) as f:
														lowercase         = json.load(A__				)
						else:
										try:
														lowercase         = baseaa.urlsafe_baadecode(A__				).decode("utf-8"				)
														lowercase         = 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}'				)

						lowercase         = config

						self.set_stage_and_offload()




		def 				UpperCAmelCase__   (self      :	Dict				)					-> Optional[int]:
						# 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.
						lowercase         = self.get_value("zero_optimization.stage"							,			-1				)

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




		def 				UpperCAmelCase__   (self      :	List[str]							,			A__      :	Union[str, Any]				)					-> Tuple:
						lowercase         = self.config

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

						return config, ds_key




		def 				UpperCAmelCase__   (self      :	Optional[Any]							,			A__      :	List[str]							,			A__      :	List[str]=None				)					-> Optional[Any]:
						lowercase   ,							lowercase         = self.find_config_node(A__				)
						if config is None:
										return default
						return config.get(A__							,			A__				)




		def 				UpperCAmelCase__   (self      :	Any							,			A__      :	Union[str, Any]							,			A__      :	List[str]=False				)					-> Optional[Any]:
						lowercase         = self.config

						# find the config node of interest if it exists
						lowercase         = ds_key_long.split("."				)
						for node in nodes:
										lowercase         = config
										lowercase         = 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]				)					-> Any:
						lowercase         = self.get_value(A__				)
						return False if value is None else bool(A__				)




		def 				UpperCAmelCase__   (self      :	List[Any]							,			A__      :	int				)					-> int:
						lowercase         = self.get_value(A__				)
						return False if value is None else not bool(A__				)




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




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





		def 				UpperCAmelCase__   (self      :	List[str]				)					-> Optional[Any]:
						return self._offload




class       UpperCAmelCase :




		def __init__(self      :	Optional[int]							,			A__      :	List[str]				)					-> str:
						lowercase         = engine





		def 				UpperCAmelCase__   (self      :	List[Any]							,			A__      :	Optional[Any]							,			**A__      :	int				)					-> str:
						# 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       UpperCAmelCase (						_lowercase  ):




		def __init__(self      :	Tuple							,			A__      :	Dict				)					-> List[str]:
						super().__init__(A__							,			device_placement=A__							,			scaler=A__				)
						lowercase         = hasattr(self.optimizer							,			"overflow"				)




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




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





		@property
		def 				UpperCAmelCase__   (self      :	Optional[Any]				)					-> Tuple:
						if self.__has_overflow__:
										return self.optimizer.overflow
						return False




class       UpperCAmelCase (						_lowercase  ):




		def __init__(self      :	int							,			A__      :	Tuple							,			A__      :	List[str]				)					-> List[Any]:
						super().__init__(A__							,			A__				)





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




class       UpperCAmelCase :




		def __init__(self      :	int							,			A__      :	List[str]							,			A__      :	Dict=0.0_0_1							,			A__      :	Tuple=0							,			**A__      :	Dict				)					-> Optional[Any]:
						lowercase         = params
						lowercase         = lr
						lowercase         = weight_decay
						lowercase         = kwargs




class       UpperCAmelCase :




		def __init__(self      :	Union[str, Any]							,			A__      :	int							,			A__      :	Union[str, Any]=None							,			A__      :	Any=0							,			**A__      :	List[str]				)					-> int:
						lowercase         = optimizer
						lowercase         = total_num_steps
						lowercase         = warmup_num_steps
						lowercase         = kwargs











'''simple docstring'''

import functools







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				if not isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) or not all(isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) for day in days							):
								raise ValueError("The parameter days should be a list of integers"							)

				if len(lowerCAmelCase_							) != 3 or not all(isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) for cost in costs							):
								raise ValueError("The parameter costs should be a list of three integers"							)

				if len(lowerCAmelCase_							) == 0:
								return 0

				if min(lowerCAmelCase_							) <= 0:
								raise ValueError("All days elements should be greater than 0"							)

				if max(lowerCAmelCase_							) >= 366:
								raise ValueError("All days elements should be less than 366"							)

				lowercase         = set(lowerCAmelCase_							)

				@functools.cache
				def dynamic_programming(lowerCAmelCase_							) -> int:
								if index > 365:
												return 0

								if index not in days_set:
												return dynamic_programming(index + 1							)

								return min(
								    costs[0] + dynamic_programming(index + 1							)		,							costs[1] + dynamic_programming(index + 7							)		,							costs[2] + dynamic_programming(index + 30							)		,							)

				return dynamic_programming(1							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()




