
"""simple docstring"""




class 			snake_case  :

							def __init__(self     ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_    			=			0
									SCREAMING_SNAKE_CASE_    			=			0
									SCREAMING_SNAKE_CASE_    			=			{}

							def _lowercase       (self							,							SCREAMING_SNAKE_CASE_     ):

									"""simple docstring"""







									if vertex not in self.adjacency:
											SCREAMING_SNAKE_CASE_    			=			{}
											self.num_vertices += 1

							def _lowercase       (self							,							SCREAMING_SNAKE_CASE_							,							SCREAMING_SNAKE_CASE_							,							SCREAMING_SNAKE_CASE_     ):

									"""simple docstring"""







									self.add_vertex(SCREAMING_SNAKE_CASE_     )
									self.add_vertex(SCREAMING_SNAKE_CASE_     )

									if head == tail:
											return

									SCREAMING_SNAKE_CASE_    			=			weight
									SCREAMING_SNAKE_CASE_    			=			weight

							def _lowercase       (self     ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_    			=			self.get_edges()
									for edge in edges:
											SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_    			=			edge
											edges.remove((tail, head, weight)     )
									for i in range(len(SCREAMING_SNAKE_CASE_     )     ):
											SCREAMING_SNAKE_CASE_    			=			list(edges[i]     )

									edges.sort(key=lambda SCREAMING_SNAKE_CASE_     : e[2]     )
									for i in range(len(SCREAMING_SNAKE_CASE_     ) - 1     ):
											if edges[i][2] >= edges[i + 1][2]:
													SCREAMING_SNAKE_CASE_    			=			edges[i][2] + 1
									for edge in edges:
											SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_    			=			edge
											SCREAMING_SNAKE_CASE_    			=			weight
											SCREAMING_SNAKE_CASE_    			=			weight

							def __str__(self     ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_    			=			''''''
									for tail in self.adjacency:
											for head in self.adjacency[tail]:
													SCREAMING_SNAKE_CASE_    			=			self.adjacency[head][tail]
													string += f'{head} -> {tail} == {weight}\n'
									return string.rstrip('''\n'''     )

							def _lowercase       (self     ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_    			=			[]
									for tail in self.adjacency:
											for head in self.adjacency[tail]:
													output.append((tail, head, self.adjacency[head][tail])     )
									return output

							def _lowercase       (self     ):

									"""simple docstring"""







									return self.adjacency.keys()

							@staticmethod
							def _lowercase       (SCREAMING_SNAKE_CASE_=None							,							SCREAMING_SNAKE_CASE_=None     ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_    			=			Graph()
									if vertices is None:
											SCREAMING_SNAKE_CASE_    			=			[]
									if edges is None:
											SCREAMING_SNAKE_CASE_    			=			[]
									for vertex in vertices:
											g.add_vertex(SCREAMING_SNAKE_CASE_     )
									for edge in edges:
											g.add_edge(*SCREAMING_SNAKE_CASE_     )
									return g





							class 			snake_case  :

														def __init__(self     ):

																"""simple docstring"""







																SCREAMING_SNAKE_CASE_    			=			{}
																SCREAMING_SNAKE_CASE_    			=			{}

														def __len__(self     ):

																"""simple docstring"""







																return len(self.parent     )

														def _lowercase       (self							,							SCREAMING_SNAKE_CASE_     ):

																"""simple docstring"""







																if item in self.parent:
																		return self.find(SCREAMING_SNAKE_CASE_     )

																SCREAMING_SNAKE_CASE_    			=			item
																SCREAMING_SNAKE_CASE_    			=			0
																return item

														def _lowercase       (self							,							SCREAMING_SNAKE_CASE_     ):

																"""simple docstring"""







																if item not in self.parent:
																		return self.make_set(SCREAMING_SNAKE_CASE_     )
																if item != self.parent[item]:
																		SCREAMING_SNAKE_CASE_    			=			self.find(self.parent[item]     )
																return self.parent[item]







														def _lowercase       (self							,							SCREAMING_SNAKE_CASE_							,							SCREAMING_SNAKE_CASE_     ):

																"""simple docstring"""







																SCREAMING_SNAKE_CASE_    			=			self.find(SCREAMING_SNAKE_CASE_     )
																SCREAMING_SNAKE_CASE_    			=			self.find(SCREAMING_SNAKE_CASE_     )

																if roota == roota:
																		return roota

																if self.rank[roota] > self.rank[roota]:
																		SCREAMING_SNAKE_CASE_    			=			roota
																		return roota

																if self.rank[roota] < self.rank[roota]:
																		SCREAMING_SNAKE_CASE_    			=			roota
																		return roota

																if self.rank[roota] == self.rank[roota]:
																		self.rank[roota] += 1
																		SCREAMING_SNAKE_CASE_    			=			roota
																		return roota
																return None







							@staticmethod
							def _lowercase       (SCREAMING_SNAKE_CASE_     ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_    			=			graph.num_vertices

									SCREAMING_SNAKE_CASE_    			=			Graph.UnionFind()
									SCREAMING_SNAKE_CASE_    			=			[]
									while num_components > 1:
											SCREAMING_SNAKE_CASE_    			=			{}
											for vertex in graph.get_vertices():
													SCREAMING_SNAKE_CASE_    			=			-1

											SCREAMING_SNAKE_CASE_    			=			graph.get_edges()
											for edge in edges:
													SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_    			=			edge
													edges.remove((tail, head, weight)     )
											for edge in edges:
													SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_    			=			edge
													SCREAMING_SNAKE_CASE_    			=			union_find.find(SCREAMING_SNAKE_CASE_     )
													SCREAMING_SNAKE_CASE_    			=			union_find.find(SCREAMING_SNAKE_CASE_     )
													if seta != seta:
															if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																	SCREAMING_SNAKE_CASE_    			=			[head, tail, weight]

															if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
																	SCREAMING_SNAKE_CASE_    			=			[head, tail, weight]
											for vertex in cheap_edge:
													if cheap_edge[vertex] != -1:
															SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_			,SCREAMING_SNAKE_CASE_    			=			cheap_edge[vertex]
															if union_find.find(SCREAMING_SNAKE_CASE_     ) != union_find.find(SCREAMING_SNAKE_CASE_     ):
																	union_find.union(SCREAMING_SNAKE_CASE_							,							SCREAMING_SNAKE_CASE_     )
																	mst_edges.append(cheap_edge[vertex]     )
																	SCREAMING_SNAKE_CASE_    			=			num_components - 1
									SCREAMING_SNAKE_CASE_    			=			Graph.build(edges=SCREAMING_SNAKE_CASE_     )
									return mst

"""simple docstring"""




import os

import torch

from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version


if is_torch_version('>=', FSDP_PYTORCH_VERSION):
						import torch.distributed.checkpoint as dist_cp
						from torch.distributed.checkpoint.default_planner import DefaultLoadPlanner, DefaultSavePlanner
						from torch.distributed.checkpoint.optimizer import load_sharded_optimizer_state_dict
						from torch.distributed.fsdp.fully_sharded_data_parallel import FullyShardedDataParallel as FSDP
						from torch.distributed.fsdp.fully_sharded_data_parallel import StateDictType


lowerCAmelCase__				=					get_logger(__name__)



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a=0     ):
		os.makedirs(__a,				exist_ok=__a     )
		with FSDP.state_dict_type(
		    __a,				fsdp_plugin.state_dict_type,				fsdp_plugin.state_dict_config,				fsdp_plugin.optim_state_dict_config     ):
				SCREAMING_SNAKE_CASE_    			=			model.state_dict()
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			F'{MODEL_NAME}.bin' if model_index == 0 else F'{MODEL_NAME}_{model_index}.bin'
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						if accelerator.process_index == 0:
								logger.info(F'Saving model to {output_model_file}'     )
								torch.save(__a,				__a     )
								logger.info(F'Model saved to {output_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			(
						    F'{MODEL_NAME}_rank{accelerator.process_index}.bin'
						    if model_index == 0
						    else F'{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'
						)
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Saving model to {output_model_file}'     )
						torch.save(__a,				__a     )
						logger.info(F'Model saved to {output_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				F'{MODEL_NAME}_{model_index}'     )
						os.makedirs(__a,				exist_ok=__a     )
						logger.info(F'Saving model to {ckpt_dir}'     )
						SCREAMING_SNAKE_CASE_    			=			{'''model''': state_dict}

						dist_cp.save_state_dict(
						    state_dict=__a,				storage_writer=dist_cp.FileSystemWriter(__a     ),				planner=DefaultSavePlanner(),				)
						logger.info(F'Model saved to {ckpt_dir}'     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a=0     ):
		accelerator.wait_for_everyone()
		with FSDP.state_dict_type(
		    __a,				fsdp_plugin.state_dict_type,				fsdp_plugin.state_dict_config,				fsdp_plugin.optim_state_dict_config     ):
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						if type(__a     ) != FSDP and accelerator.process_index != 0:
								if not fsdp_plugin.sync_module_states:
										raise ValueError(
										    '''Set the `sync_module_states` flag to `True` so that model states are synced across processes when '''
										    '''initializing FSDP object'''     )
								return
						SCREAMING_SNAKE_CASE_    			=			F'{MODEL_NAME}.bin' if model_index == 0 else F'{MODEL_NAME}_{model_index}.bin'
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Loading model from {input_model_file}'     )
						SCREAMING_SNAKE_CASE_    			=			torch.load(__a     )
						logger.info(F'Model loaded from {input_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			(
						    F'{MODEL_NAME}_rank{accelerator.process_index}.bin'
						    if model_index == 0
						    else F'{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'
						)
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Loading model from {input_model_file}'     )
						SCREAMING_SNAKE_CASE_    			=			torch.load(__a     )
						logger.info(F'Model loaded from {input_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			(
						    os.path.join(__a,				F'{MODEL_NAME}_{model_index}'     )
						    if F'{MODEL_NAME}' not in input_dir
						    else input_dir
						)
						logger.info(F'Loading model from {ckpt_dir}'     )
						SCREAMING_SNAKE_CASE_    			=			{'''model''': model.state_dict()}
						dist_cp.load_state_dict(
						    state_dict=__a,				storage_reader=dist_cp.FileSystemReader(__a     ),				planner=DefaultLoadPlanner(),				)
						SCREAMING_SNAKE_CASE_    			=			state_dict['''model''']
						logger.info(F'Model loaded from {ckpt_dir}'     )
				model.load_state_dict(__a     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a,				__a=0     ):
		os.makedirs(__a,				exist_ok=__a     )
		with FSDP.state_dict_type(
		    __a,				fsdp_plugin.state_dict_type,				fsdp_plugin.state_dict_config,				fsdp_plugin.optim_state_dict_config     ):
				SCREAMING_SNAKE_CASE_    			=			FSDP.optim_state_dict(__a,				__a     )
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						if accelerator.process_index == 0:
								SCREAMING_SNAKE_CASE_    			=			(
								    F'{OPTIMIZER_NAME}.bin' if optimizer_index == 0 else F'{OPTIMIZER_NAME}_{optimizer_index}.bin'
								)
								SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
								logger.info(F'Saving Optimizer state to {output_optimizer_file}'     )
								torch.save(__a,				__a     )
								logger.info(F'Optimizer state saved in {output_optimizer_file}'     )
				else:
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				F'{OPTIMIZER_NAME}_{optimizer_index}'     )
						os.makedirs(__a,				exist_ok=__a     )
						logger.info(F'Saving Optimizer state to {ckpt_dir}'     )
						dist_cp.save_state_dict(
						    state_dict={'''optimizer''': optim_state},				storage_writer=dist_cp.FileSystemWriter(__a     ),				planner=DefaultSavePlanner(),				)
						logger.info(F'Optimizer state saved in {ckpt_dir}'     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a,				__a=0     ):
		accelerator.wait_for_everyone()
		with FSDP.state_dict_type(
		    __a,				fsdp_plugin.state_dict_type,				fsdp_plugin.state_dict_config,				fsdp_plugin.optim_state_dict_config     ):
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			None
						# below check should work but currently it isn't working (mostly opytorch issue),
						# in the meantime disabling it at the cost of excess memory usage
						# if accelerator.process_index == 0 or not fsdp_plugin.optim_state_dict_config.rank0_only:
						SCREAMING_SNAKE_CASE_    			=			(
						    F'{OPTIMIZER_NAME}.bin' if optimizer_index == 0 else F'{OPTIMIZER_NAME}_{optimizer_index}.bin'
						)
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Loading Optimizer state from {input_optimizer_file}'     )
						SCREAMING_SNAKE_CASE_    			=			torch.load(__a     )
						logger.info(F'Optimizer state loaded from {input_optimizer_file}'     )
				else:
						SCREAMING_SNAKE_CASE_    			=			(
						    os.path.join(__a,				F'{OPTIMIZER_NAME}_{optimizer_index}'     )
						    if F'{OPTIMIZER_NAME}' not in input_dir
						    else input_dir
						)
						logger.info(F'Loading Optimizer from {ckpt_dir}'     )
						SCREAMING_SNAKE_CASE_    			=			load_sharded_optimizer_state_dict(
						    model_state_dict=model.state_dict(),				optimizer_key='''optimizer''',				storage_reader=dist_cp.FileSystemReader(__a     ),				)
						SCREAMING_SNAKE_CASE_    			=			optim_state['''optimizer''']
						logger.info(F'Optimizer loaded from {ckpt_dir}'     )
				SCREAMING_SNAKE_CASE_    			=			FSDP.optim_state_dict_to_load(__a,				__a,				__a     )
				optimizer.load_state_dict(__a     )