




"""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					:	Optional[Any]    ,   lowercase__					:	int						):
						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
								__lowercase				:		str												=				deepcopy(lowercase__						)
						elif os.path.exists(lowercase__						):
								with io.open(lowercase__    ,   "r"    ,   encoding="utf-8"						) as f:
										__lowercase				:		Optional[Any]												=				json.load(lowercase__						)
						else:
								try:
										__lowercase				:		Dict												=				baseaa.urlsafe_baadecode(lowercase__						).decode("utf-8"						)
										__lowercase				:		Optional[int]												=				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}'						)

						__lowercase				:		List[str]												=				config

						self.set_stage_and_offload()



				def       snake_case    (     self					:	Tuple						):
						# 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				:		List[Any]												=				self.get_value("zero_optimization.stage"    ,   -1						)

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



				def       snake_case    (     self					:	Dict    ,   lowercase__					:	Union[str, Any]						):
						__lowercase				:		Tuple												=				self.config

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

						return config, ds_key



				def       snake_case    (     self					:	str    ,   lowercase__					:	Dict    ,   lowercase__					:	Any=None						):
						__lowercase				:		Dict												=				self.find_config_node(lowercase__						)
						if config is None:
								return default
						return config.get(lowercase__    ,   lowercase__						)



				def       snake_case    (     self					:	List[str]    ,   lowercase__					:	Union[str, Any]    ,   lowercase__					:	str=False						):
						__lowercase				:		Optional[Any]												=				self.config

						# find the config node of interest if it exists
						__lowercase				:		List[Any]												=				ds_key_long.split("."						)
						for node in nodes:
								__lowercase				:		Any												=				config
								__lowercase				:		List[Any]												=				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       snake_case    (     self					:	Optional[int]    ,   lowercase__					:	Dict						):
						__lowercase				:		List[Any]												=				self.get_value(lowercase__						)
						return False if value is None else bool(lowercase__						)



				def       snake_case    (     self					:	List[str]    ,   lowercase__					:	Tuple						):
						__lowercase				:		str												=				self.get_value(lowercase__						)
						return False if value is None else not bool(lowercase__						)



				def       snake_case    (     self					:	List[str]						):
						return self._stage == 2



				def       snake_case    (     self					:	Dict						):
						return self._stage == 3



				def       snake_case    (     self					:	int						):
						return self._offload





class       lowerCAmelCase__       :


				"""simple docstring"""





				def __init__(     self					:	Any    ,   lowercase__					:	Optional[Any]						):
						__lowercase				:		List[Any]												=				engine



				def       snake_case    (     self					:	Optional[Any]    ,   lowercase__					:	str    ,   **lowercase__					:	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       lowerCAmelCase__       (			lowerCAmelCase_    ):


				"""simple docstring"""





				def __init__(     self					:	Union[str, Any]    ,   lowercase__					:	List[Any]						):
						super().__init__(lowercase__    ,   device_placement=lowercase__    ,   scaler=lowercase__						)
						__lowercase				:		List[Any]												=				hasattr(self.optimizer    ,   "overflow"						)



				def       snake_case    (     self					:	int    ,   lowercase__					:	List[str]=None						):
						pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed



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



				@property
				def       snake_case    (     self					:	int						):
						if self.__has_overflow__:
								return self.optimizer.overflow
						return False





class       lowerCAmelCase__       (			lowerCAmelCase_    ):


				"""simple docstring"""





				def __init__(     self					:	List[Any]    ,   lowercase__					:	List[str]    ,   lowercase__					:	Optional[Any]						):
						super().__init__(lowercase__    ,   lowercase__						)



				def       snake_case    (     self					:	str						):
						pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed





class       lowerCAmelCase__       :


				"""simple docstring"""





				def __init__(     self					:	Dict    ,   lowercase__					:	Dict    ,   lowercase__					:	List[str]=0.0_0_1    ,   lowercase__					:	Tuple=0    ,   **lowercase__					:	List[str]						):
						__lowercase				:		Union[str, Any]												=				params
						__lowercase				:		str												=				lr
						__lowercase				:		Any												=				weight_decay
						__lowercase				:		Dict												=				kwargs





class       lowerCAmelCase__       :


				"""simple docstring"""





				def __init__(     self					:	Union[str, Any]    ,   lowercase__					:	int    ,   lowercase__					:	Dict=None    ,   lowercase__					:	Optional[int]=0    ,   **lowercase__					:	Optional[Any]						):
						__lowercase				:		List[Any]												=				optimizer
						__lowercase				:		Union[str, Any]												=				total_num_steps
						__lowercase				:		List[Any]												=				warmup_num_steps
						__lowercase				:		List[Any]												=				kwargs







"""simple docstring"""







from collections import deque

def 						snake_case__       (					_lowerCamelCase				)			->Dict:






		"""simple docstring"""


		__lowercase				:		Any												=				len(_lowerCamelCase				)
		__lowercase				:		str												=				deque()
		__lowercase				:		Tuple												=				[False for _ in range(_lowerCamelCase				)]
		__lowercase				:		Optional[int]												=				[-1 for _ in range(_lowerCamelCase				)]
		__lowercase				:		Dict												=				index_of[:]

		def strong_connect(_lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase				):
				__lowercase				:		List[str]												=				index  # the number when this node is seen
				__lowercase				:		List[str]												=				index  # lowest rank node reachable from here
				index += 1
				stack.append(_lowerCamelCase				)
				__lowercase				:		List[Any]												=				True

				for w in g[v]:
						if index_of[w] == -1:
								__lowercase				:		Optional[int]												=				strong_connect(_lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase				)
								__lowercase				:		List[Any]												=				(
								    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
								)
						elif on_stack[w]:
								__lowercase				:		List[Any]												=				(
								    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
								)

				if lowlink_of[v] == index_of[v]:
						__lowercase				:		Any												=				[]
						__lowercase				:		List[Any]												=				stack.pop()
						__lowercase				:		Any												=				False
						component.append(_lowerCamelCase				)
						while w != v:
								__lowercase				:		List[str]												=				stack.pop()
								__lowercase				:		Dict												=				False
								component.append(_lowerCamelCase				)
						components.append(_lowerCamelCase				)
				return index

		__lowercase				:		Tuple												=				[]
		for v in range(_lowerCamelCase				):
				if index_of[v] == -1:
						strong_connect(_lowerCamelCase,  0,  _lowerCamelCase				)

		return components

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase				)			->Tuple:






		"""simple docstring"""


		__lowercase				:		int												=				[[] for _ in range(_lowerCamelCase				)]
		for u, v in edges:
				g[u].append(_lowerCamelCase				)
		return g


if __name__ == "__main__":
						# Test
						__A   :  int					=      7
						__A   :  int					=      [0, 0, 1, 2, 3, 3, 4, 4, 6]
						__A   :  List[Any]					=      [1, 3, 2, 0, 1, 4, 5, 6, 5]
						__A   :  List[str]					=      [(u, v) for u, v in zip(source, target)]
						__A   :  List[str]					=      create_graph(n_vertices, edges)

						assert [[5], [6], [4], [3, 2, 1, 0]] == tarjan(g)
