






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


SCREAMING_SNAKE_CASE__   :      List[Any]				=		get_logger(__name__)

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				os.makedirs(snake_case,	exist_ok=snake_case			)
				with FSDP.state_dict_type(
				    snake_case,	fsdp_plugin.state_dict_type,	fsdp_plugin.state_dict_config,	fsdp_plugin.optim_state_dict_config			):
								__magic_name__		:Tuple   =   model.state_dict()
								if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
												__magic_name__		:List[Any]   =   f'''{MODEL_NAME}.bin''' if model_index == 0 else f'''{MODEL_NAME}_{model_index}.bin'''
												__magic_name__		:int   =   os.path.join(snake_case,	snake_case			)
												if accelerator.process_index == 0:
																logger.info(f'''Saving model to {output_model_file}'''			)
																torch.save(snake_case,	snake_case			)
																logger.info(f'''Model saved to {output_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
												__magic_name__		:Optional[int]   =   (
												    f'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
												    if model_index == 0
												    else f'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
												)
												__magic_name__		:List[Any]   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Saving model to {output_model_file}'''			)
												torch.save(snake_case,	snake_case			)
												logger.info(f'''Model saved to {output_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
												__magic_name__		:Optional[Any]   =   os.path.join(snake_case,	f'''{MODEL_NAME}_{model_index}'''			)
												os.makedirs(snake_case,	exist_ok=snake_case			)
												logger.info(f'''Saving model to {ckpt_dir}'''			)
												__magic_name__		:List[Any]   =   {'''model''': state_dict}

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

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				accelerator.wait_for_everyone()
				with FSDP.state_dict_type(
				    snake_case,	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(snake_case			) != 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
												__magic_name__		:List[Any]   =   f'''{MODEL_NAME}.bin''' if model_index == 0 else f'''{MODEL_NAME}_{model_index}.bin'''
												__magic_name__		:Any   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Loading model from {input_model_file}'''			)
												__magic_name__		:Any   =   torch.load(snake_case			)
												logger.info(f'''Model loaded from {input_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
												__magic_name__		:Union[str, Any]   =   (
												    f'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
												    if model_index == 0
												    else f'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
												)
												__magic_name__		:Tuple   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Loading model from {input_model_file}'''			)
												__magic_name__		:List[Any]   =   torch.load(snake_case			)
												logger.info(f'''Model loaded from {input_model_file}'''			)
								elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
												__magic_name__		:Tuple   =   (
												    os.path.join(snake_case,	f'''{MODEL_NAME}_{model_index}'''			)
												    if f'''{MODEL_NAME}''' not in input_dir
												    else input_dir
												)
												logger.info(f'''Loading model from {ckpt_dir}'''			)
												__magic_name__		:Any   =   {'''model''': model.state_dict()}
												dist_cp.load_state_dict(
												    state_dict=snake_case,	storage_reader=dist_cp.FileSystemReader(snake_case			),	planner=DefaultLoadPlanner(),	)
												__magic_name__		:Any   =   state_dict['''model''']
												logger.info(f'''Model loaded from {ckpt_dir}'''			)
								model.load_state_dict(snake_case			)

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				os.makedirs(snake_case,	exist_ok=snake_case			)
				with FSDP.state_dict_type(
				    snake_case,	fsdp_plugin.state_dict_type,	fsdp_plugin.state_dict_config,	fsdp_plugin.optim_state_dict_config			):
								__magic_name__		:List[Any]   =   FSDP.optim_state_dict(snake_case,	snake_case			)
								if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
												if accelerator.process_index == 0:
																__magic_name__		:Optional[int]   =   (
																    f'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else f'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
																)
																__magic_name__		:str   =   os.path.join(snake_case,	snake_case			)
																logger.info(f'''Saving Optimizer state to {output_optimizer_file}'''			)
																torch.save(snake_case,	snake_case			)
																logger.info(f'''Optimizer state saved in {output_optimizer_file}'''			)
								else:
												__magic_name__		:Tuple   =   os.path.join(snake_case,	f'''{OPTIMIZER_NAME}_{optimizer_index}'''			)
												os.makedirs(snake_case,	exist_ok=snake_case			)
												logger.info(f'''Saving Optimizer state to {ckpt_dir}'''			)
												dist_cp.save_state_dict(
												    state_dict={'''optimizer''': optim_state},	storage_writer=dist_cp.FileSystemWriter(snake_case			),	planner=DefaultSavePlanner(),	)
												logger.info(f'''Optimizer state saved in {ckpt_dir}'''			)

def   __lowercase       (			snake_case,	snake_case,	snake_case,	snake_case,	snake_case,	snake_case=0			):







				"""simple docstring"""






				accelerator.wait_for_everyone()
				with FSDP.state_dict_type(
				    snake_case,	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:
												__magic_name__		:Tuple   =   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:
												__magic_name__		:Optional[Any]   =   (
												    f'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else f'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
												)
												__magic_name__		:str   =   os.path.join(snake_case,	snake_case			)
												logger.info(f'''Loading Optimizer state from {input_optimizer_file}'''			)
												__magic_name__		:Optional[int]   =   torch.load(snake_case			)
												logger.info(f'''Optimizer state loaded from {input_optimizer_file}'''			)
								else:
												__magic_name__		:Tuple   =   (
												    os.path.join(snake_case,	f'''{OPTIMIZER_NAME}_{optimizer_index}'''			)
												    if f'''{OPTIMIZER_NAME}''' not in input_dir
												    else input_dir
												)
												logger.info(f'''Loading Optimizer from {ckpt_dir}'''			)
												__magic_name__		:List[str]   =   load_sharded_optimizer_state_dict(
												    model_state_dict=model.state_dict(),	optimizer_key='''optimizer''',	storage_reader=dist_cp.FileSystemReader(snake_case			),	)
												__magic_name__		:str   =   optim_state['''optimizer''']
												logger.info(f'''Optimizer loaded from {ckpt_dir}'''			)
								__magic_name__		:Tuple   =   FSDP.optim_state_dict_to_load(snake_case,	snake_case,	snake_case			)
								optimizer.load_state_dict(snake_case			)














def   __lowercase       (			snake_case			):







				"""simple docstring"""






				if not isinstance(snake_case,	snake_case			):
								raise ValueError('''multiplicative_persistence() only accepts integral values'''			)
				if num < 0:
								raise ValueError('''multiplicative_persistence() does not accept negative values'''			)

				__magic_name__		:str   =   0
				__magic_name__		:Dict   =   str(snake_case			)

				while len(snake_case			) != 1:
								__magic_name__		:Optional[Any]   =   [int(snake_case			) for i in num_string]

								__magic_name__		:Dict   =   1
								for i in range(0,	len(snake_case			)			):
												total *= numbers[i]

								__magic_name__		:int   =   str(snake_case			)

								steps += 1
				return steps

def   __lowercase       (			snake_case			):







				"""simple docstring"""






				if not isinstance(snake_case,	snake_case			):
								raise ValueError('''additive_persistence() only accepts integral values'''			)
				if num < 0:
								raise ValueError('''additive_persistence() does not accept negative values'''			)

				__magic_name__		:str   =   0
				__magic_name__		:Union[str, Any]   =   str(snake_case			)

				while len(snake_case			) != 1:
								__magic_name__		:str   =   [int(snake_case			) for i in num_string]

								__magic_name__		:Optional[int]   =   0
								for i in range(0,	len(snake_case			)			):
												total += numbers[i]

								__magic_name__		:int   =   str(snake_case			)

								steps += 1
				return steps


if __name__ == "__main__":
					import doctest

					doctest.testmod()






