






"""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


__A		:       Dict  				=		get_logger(__name__)



def 						lowercase    (				__snake_case				: Any		,					__snake_case				: int		,					__snake_case				: Union[str, Any]		,					__snake_case				: Dict		,					__snake_case				: str=0	):
		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	):
				lowercase_ : str							       =   model.state_dict()
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						lowercase_ : Any							       =   F'''{MODEL_NAME}.bin''' if model_index == 0 else F'''{MODEL_NAME}_{model_index}.bin'''
						lowercase_ : str							       =   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:
						lowercase_ : str							       =   (
						    F'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
						    if model_index == 0
						    else F'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
						)
						lowercase_ : int							       =   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:
						lowercase_ : int							       =   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}'''	)
						lowercase_ : Dict							       =   {'''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				: Tuple		,					__snake_case				: Union[str, Any]		,					__snake_case				: Union[str, Any]		,					__snake_case				: List[Any]		,					__snake_case				: Tuple=0	):
		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
						lowercase_ : int							       =   F'''{MODEL_NAME}.bin''' if model_index == 0 else F'''{MODEL_NAME}_{model_index}.bin'''
						lowercase_ : Dict							       =   os.path.join(__snake_case		,					__snake_case	)
						logger.info(F'''Loading model from {input_model_file}'''	)
						lowercase_ : Any							       =   torch.load(__snake_case	)
						logger.info(F'''Model loaded from {input_model_file}'''	)
				elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
						lowercase_ : 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'''
						)
						lowercase_ : Any							       =   os.path.join(__snake_case		,					__snake_case	)
						logger.info(F'''Loading model from {input_model_file}'''	)
						lowercase_ : int							       =   torch.load(__snake_case	)
						logger.info(F'''Model loaded from {input_model_file}'''	)
				elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
						lowercase_ : Union[str, Any]							       =   (
						    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}'''	)
						lowercase_ : List[Any]							       =   {'''model''': model.state_dict()}
						dist_cp.load_state_dict(
						    state_dict=__snake_case		,					storage_reader=dist_cp.FileSystemReader(__snake_case	)		,					planner=DefaultLoadPlanner()		,					)
						lowercase_ : Optional[Any]							       =   state_dict['''model''']
						logger.info(F'''Model loaded from {ckpt_dir}'''	)
				model.load_state_dict(__snake_case	)



def 						lowercase    (				__snake_case				: Any		,					__snake_case				: List[Any]		,					__snake_case				: Dict		,					__snake_case				: Union[str, Any]		,					__snake_case				: Tuple		,					__snake_case				: Tuple=0	):
		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	):
				lowercase_ : Tuple							       =   FSDP.optim_state_dict(__snake_case		,					__snake_case	)
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						if accelerator.process_index == 0:
								lowercase_ : Any							       =   (
								    F'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else F'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
								)
								lowercase_ : Optional[Any]							       =   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:
						lowercase_ : List[Any]							       =   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				: Tuple		,					__snake_case				: Union[str, Any]		,					__snake_case				: List[str]		,					__snake_case				: Any		,					__snake_case				: Tuple		,					__snake_case				: Optional[int]=0	):
		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:
						lowercase_ : int							       =   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:
						lowercase_ : List[str]							       =   (
						    F'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else F'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
						)
						lowercase_ : List[Any]							       =   os.path.join(__snake_case		,					__snake_case	)
						logger.info(F'''Loading Optimizer state from {input_optimizer_file}'''	)
						lowercase_ : str							       =   torch.load(__snake_case	)
						logger.info(F'''Optimizer state loaded from {input_optimizer_file}'''	)
				else:
						lowercase_ : Union[str, Any]							       =   (
						    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}'''	)
						lowercase_ : Tuple							       =   load_sharded_optimizer_state_dict(
						    model_state_dict=model.state_dict()		,					optimizer_key='''optimizer'''		,					storage_reader=dist_cp.FileSystemReader(__snake_case	)		,					)
						lowercase_ : Optional[int]							       =   optim_state['''optimizer''']
						logger.info(F'''Optimizer loaded from {ckpt_dir}'''	)
				lowercase_ : Optional[int]							       =   FSDP.optim_state_dict_to_load(__snake_case		,					__snake_case		,					__snake_case	)
				optimizer.load_state_dict(__snake_case	)









"""simple docstring"""






import socket







def      _snake_case			(				):
				_lowerCamelCase     :			List[Any]    =    socket.socket(socket.AF_INET							,    socket.SOCK_STREAM		)
				_lowerCamelCase     :			Union[str, Any]    =    socket.gethostname()
				_lowerCamelCase     :			List[Any]    =    12312

				sock.connect((host, port)		)
				sock.send(B'Hello server!'		)

				with open('Received_file'							,    'wb'		) as out_file:
								print('File opened'		)
								print('Receiving data...'		)
								while True:
												_lowerCamelCase     :			int    =    sock.recv(1024		)
												if not data:
																break
												out_file.write(lowercase__		)

				print('Successfully received the file'		)
				sock.close()
				print('Connection closed'		)


if __name__ == "__main__":
			main()