




'''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_ :						str				 =			get_logger(__name__)





def 	a_				( __snake_case				:     Tuple  ,			__snake_case				:     List[Any]  ,			__snake_case				:     Dict  ,			__snake_case				:     Any  ,			__snake_case				:     Dict=0  )				->		int:



       """simple docstring"""
       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  ):
              lowerCamelCase_				=model.state_dict()
              if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
                     lowerCamelCase_				=F'''{MODEL_NAME}.bin''' if model_index == 0 else F'''{MODEL_NAME}_{model_index}.bin'''
                     lowerCamelCase_				=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:
                     lowerCamelCase_				=(
                         F'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
                         if model_index == 0
                         else F'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
                     )
                     lowerCamelCase_				=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:
                     lowerCamelCase_				=os.path.join(lowerCAmelCase__  ,			F'''{MODEL_NAME}_{model_index}'''  )
                     os.makedirs(lowerCAmelCase__  ,			exist_ok=lowerCAmelCase__  )
                     logger.info(F'''Saving model to {ckpt_dir}'''  )
                     lowerCamelCase_				={"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 	a_				( __snake_case				:     List[Any]  ,			__snake_case				:     Optional[Any]  ,			__snake_case				:     List[str]  ,			__snake_case				:     List[Any]  ,			__snake_case				:     Dict=0  )				->		List[Any]:



       """simple docstring"""
       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
                     lowerCamelCase_				=F'''{MODEL_NAME}.bin''' if model_index == 0 else F'''{MODEL_NAME}_{model_index}.bin'''
                     lowerCamelCase_				=os.path.join(lowerCAmelCase__  ,			lowerCAmelCase__  )
                     logger.info(F'''Loading model from {input_model_file}'''  )
                     lowerCamelCase_				=torch.load(lowerCAmelCase__  )
                     logger.info(F'''Model loaded from {input_model_file}'''  )
              elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
                     lowerCamelCase_				=(
                         F'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
                         if model_index == 0
                         else F'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
                     )
                     lowerCamelCase_				=os.path.join(lowerCAmelCase__  ,			lowerCAmelCase__  )
                     logger.info(F'''Loading model from {input_model_file}'''  )
                     lowerCamelCase_				=torch.load(lowerCAmelCase__  )
                     logger.info(F'''Model loaded from {input_model_file}'''  )
              elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
                     lowerCamelCase_				=(
                         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}'''  )
                     lowerCamelCase_				={"model": model.state_dict()}
                     dist_cp.load_state_dict(
                         state_dict=lowerCAmelCase__  ,			storage_reader=dist_cp.FileSystemReader(lowerCAmelCase__  )  ,			planner=DefaultLoadPlanner()  ,			)
                     lowerCamelCase_				=state_dict["model"]
                     logger.info(F'''Model loaded from {ckpt_dir}'''  )
              model.load_state_dict(lowerCAmelCase__  )





def 	a_				( __snake_case				:     Optional[Any]  ,			__snake_case				:     List[str]  ,			__snake_case				:     Dict  ,			__snake_case				:     Any  ,			__snake_case				:     Tuple  ,			__snake_case				:     Dict=0  )				->		List[str]:



       """simple docstring"""
       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  ):
              lowerCamelCase_				=FSDP.optim_state_dict(lowerCAmelCase__  ,			lowerCAmelCase__  )
              if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
                     if accelerator.process_index == 0:
                            lowerCamelCase_				=(
                                F'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else F'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
                            )
                            lowerCamelCase_				=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:
                     lowerCamelCase_				=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 	a_				( __snake_case				:     Union[str, Any]  ,			__snake_case				:     Any  ,			__snake_case				:     Any  ,			__snake_case				:     Optional[int]  ,			__snake_case				:     Any  ,			__snake_case				:     List[str]=0  )				->		str:



       """simple docstring"""
       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:
                     lowerCamelCase_				=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:
                     lowerCamelCase_				=(
                         F'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else F'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
                     )
                     lowerCamelCase_				=os.path.join(lowerCAmelCase__  ,			lowerCAmelCase__  )
                     logger.info(F'''Loading Optimizer state from {input_optimizer_file}'''  )
                     lowerCamelCase_				=torch.load(lowerCAmelCase__  )
                     logger.info(F'''Optimizer state loaded from {input_optimizer_file}'''  )
              else:
                     lowerCamelCase_				=(
                         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}'''  )
                     lowerCamelCase_				=load_sharded_optimizer_state_dict(
                         model_state_dict=model.state_dict()  ,			optimizer_key='''optimizer'''  ,			storage_reader=dist_cp.FileSystemReader(lowerCAmelCase__  )  ,			)
                     lowerCamelCase_				=optim_state["optimizer"]
                     logger.info(F'''Optimizer loaded from {ckpt_dir}'''  )
              lowerCamelCase_				=FSDP.optim_state_dict_to_load(lowerCAmelCase__  ,			lowerCAmelCase__  ,			lowerCAmelCase__  )
              optimizer.load_state_dict(lowerCAmelCase__  )











"""simple docstring"""






import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin



class 					__UpperCAmelCase							(						unittest.TestCase						,  _UpperCamelCase  ):
				def       UpperCAmelCase      (		self    :			Dict    )	->	List[Any]:



							'''simple docstring'''



							a__  :	Any		 =			load_tool("text-classification"    )
							self.tool.setup()
							a__  :	List[Any]		 =			load_tool("text-classification"	, remote=a_    )
				def       UpperCAmelCase      (		self    :			Optional[int]    )	->	Optional[Any]:



							'''simple docstring'''



							a__  :	str		 =			self.tool("That's quite cool"	, ["positive", "negative"]    )
							self.assertEqual(a_	, "positive"    )
				def       UpperCAmelCase      (		self    :			Union[str, Any]    )	->	Optional[int]:



							'''simple docstring'''



							a__  :	List[str]		 =			self.remote_tool("That's quite cool"	, ["positive", "negative"]    )
							self.assertEqual(a_	, "positive"    )
				def       UpperCAmelCase      (		self    :			Dict    )	->	Any:



							'''simple docstring'''



							a__  :	List[str]		 =			self.tool(text="That's quite cool"	, labels=["positive", "negative"]    )
							self.assertEqual(a_	, "positive"    )






				def       UpperCAmelCase      (		self    :			List[Any]    )	->	List[Any]:



							'''simple docstring'''



							a__  :	Tuple		 =			self.remote_tool(text="That's quite cool"	, labels=["positive", "negative"]    )
							self.assertEqual(a_	, "positive"    )