

'''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


UpperCamelCase_    						=       get_logger(__name__)






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

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






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






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







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












def 				_UpperCAmelCase			(    A     ):




   '''simple docstring'''

   for i in range(len(A     ) - 1				,							0				,							-1     ):
      UpperCAmelCase__						=False

      for j in range(A				,							0				,							-1     ):
         if unsorted[j] < unsorted[j - 1]:
            UpperCAmelCase__			,							UpperCAmelCase__						=unsorted[j - 1], unsorted[j]
            UpperCAmelCase__						=True

      for j in range(A     ):
         if unsorted[j] > unsorted[j + 1]:
            UpperCAmelCase__			,							UpperCAmelCase__						=unsorted[j + 1], unsorted[j]
            UpperCAmelCase__						=True

      if not swapped:
         break
   return unsorted


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    UpperCamelCase_												=	input('Enter numbers separated by a comma:\n').strip()
    UpperCamelCase_												=	[int(item) for item in user_input.split(',')]
    print(f"""{cocktail_shaker_sort(unsorted) = }""")



