



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

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



def      __UpperCAmelCase      (    __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase=0	)							->      Tuple:
		accelerator.wait_for_everyone()
		with FSDP.state_dict_type(
		    __lowerCamelCase						,     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(__lowerCamelCase	) != 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__   :    Optional[Any]				=			f"""{MODEL_NAME}.bin""" if model_index == 0 else f"""{MODEL_NAME}_{model_index}.bin"""
						lowercase__   :    Any				=			os.path.join(__lowerCamelCase						,     __lowerCamelCase	)
						logger.info(f"""Loading model from {input_model_file}"""	)
						lowercase__   :    List[Any]				=			torch.load(__lowerCamelCase	)
						logger.info(f"""Model loaded from {input_model_file}"""	)
				elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
						lowercase__   :    List[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__   :    Dict				=			os.path.join(__lowerCamelCase						,     __lowerCamelCase	)
						logger.info(f"""Loading model from {input_model_file}"""	)
						lowercase__   :    List[str]				=			torch.load(__lowerCamelCase	)
						logger.info(f"""Model loaded from {input_model_file}"""	)
				elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
						lowercase__   :    str				=			(
						    os.path.join(__lowerCamelCase						,     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__   :    Dict				=			{'''model''': model.state_dict()}
						dist_cp.load_state_dict(
						    state_dict=__lowerCamelCase						,     storage_reader=dist_cp.FileSystemReader(__lowerCamelCase	)						,     planner=DefaultLoadPlanner()						,     )
						lowercase__   :    Optional[int]				=			state_dict['''model''']
						logger.info(f"""Model loaded from {ckpt_dir}"""	)
				model.load_state_dict(__lowerCamelCase	)



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





def      __UpperCAmelCase      (    __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase=0	)							->      Any:
		accelerator.wait_for_everyone()
		with FSDP.state_dict_type(
		    __lowerCamelCase						,     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__   :    Optional[Any]				=			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__   :    Optional[int]				=			(
						    f"""{OPTIMIZER_NAME}.bin""" if optimizer_index == 0 else f"""{OPTIMIZER_NAME}_{optimizer_index}.bin"""
						)
						lowercase__   :    Any				=			os.path.join(__lowerCamelCase						,     __lowerCamelCase	)
						logger.info(f"""Loading Optimizer state from {input_optimizer_file}"""	)
						lowercase__   :    Tuple				=			torch.load(__lowerCamelCase	)
						logger.info(f"""Optimizer state loaded from {input_optimizer_file}"""	)
				else:
						lowercase__   :    Any				=			(
						    os.path.join(__lowerCamelCase						,     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__   :    List[str]				=			load_sharded_optimizer_state_dict(
						    model_state_dict=model.state_dict()						,     optimizer_key='''optimizer'''						,     storage_reader=dist_cp.FileSystemReader(__lowerCamelCase	)						,     )
						lowercase__   :    int				=			optim_state['''optimizer''']
						logger.info(f"""Optimizer loaded from {ckpt_dir}"""	)
				lowercase__   :    List[Any]				=			FSDP.optim_state_dict_to_load(__lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase	)
				optimizer.load_state_dict(__lowerCamelCase	)





"""simple docstring"""







def      __UpperCAmelCase      (    __lowerCamelCase						,     __lowerCamelCase	)							->      str:
		if not isinstance(__lowerCamelCase						,     __lowerCamelCase	):
				raise ValueError('''iterations must be defined as integers'''	)
		if not isinstance(__lowerCamelCase						,     __lowerCamelCase	) or not number >= 1:
				raise ValueError(
				    '''starting number must be
                         and integer and be more than 0'''	)
		if not iterations >= 1:
				raise ValueError('''Iterations must be done more than 0 times to play FizzBuzz'''	)

		lowercase__   :    Tuple				=			''''''
		while number <= iterations:
				if number % 3 == 0:
						out += "Fizz"
				if number % 5 == 0:
						out += "Buzz"
				if 0 not in (number % 3, number % 5):
						out += str(__lowerCamelCase	)

				# print(out)
				number += 1
				out += " "
		return out


if __name__ == "__main__":
							import doctest

							doctest.testmod()
