






'''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     :   Union[str, Any]	      =		get_logger(__name__)
def     A__      (					__lowerCAmelCase		:      Optional[int] ,     __lowerCAmelCase		:      Dict ,     __lowerCAmelCase		:      Union[str, Any] ,     __lowerCAmelCase		:      Tuple ,     __lowerCAmelCase		:      List[str]=0    ):
						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__      (					__lowerCAmelCase		:      Optional[int] ,     __lowerCAmelCase		:      Optional[int] ,     __lowerCAmelCase		:      str ,     __lowerCAmelCase		:      str ,     __lowerCAmelCase		:      Dict=0    ):
						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__      (					__lowerCAmelCase		:      Union[str, Any] ,     __lowerCAmelCase		:      Any ,     __lowerCAmelCase		:      int ,     __lowerCAmelCase		:      str ,     __lowerCAmelCase		:      Optional[int] ,     __lowerCAmelCase		:      int=0    ):
						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__      (					__lowerCAmelCase		:      Optional[Any] ,     __lowerCAmelCase		:      Optional[int] ,     __lowerCAmelCase		:      str ,     __lowerCAmelCase		:      str ,     __lowerCAmelCase		:      Tuple ,     __lowerCAmelCase		:      Optional[Any]=0    ):
						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    )








def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     Union[str, Any] 						=      []
		lowerCamelCase_	:     Tuple 						=      []
		lowerCamelCase_	:     Dict 						=      {
		    '^': 3,
		    '*': 2,
		    '/': 2,
		    '%': 2,
		    '+': 1,
		    '-': 1,
		}  # Priority of each operator
		lowerCamelCase_	:     Optional[int] 						=      len(lowerCAmelCase__						) if (len(lowerCAmelCase__						) > 7) else 7

		# Print table header for output
		print(
		    'Symbol'.center(8						)							,'Stack'.center(lowerCAmelCase__						)							,'Postfix'.center(lowerCAmelCase__						)							,sep=' | '							,)
		print('-' * (print_width * 3 + 7)						)

		for x in infix:
				if x.isalpha() or x.isdigit():
						post_fix.append(lowerCAmelCase__						)  # if x is Alphabet / Digit, add it to Postfix
				elif x == "(":
						stack.append(lowerCAmelCase__						)  # if x is "(" push to Stack
				elif x == ")":  # if x is ")" pop stack until "(" is encountered
						while stack[-1] != "(":
								post_fix.append(stack.pop()						)  # Pop stack & add the content to Postfix
						stack.pop()
				else:
						if len(lowerCAmelCase__						) == 0:
								stack.append(lowerCAmelCase__						)  # If stack is empty, push x to stack
						else:  # while priority of x is not > priority of element in the stack
								while len(lowerCAmelCase__						) > 0 and priority[x] <= priority[stack[-1]]:
										post_fix.append(stack.pop()						)  # pop stack & add to Postfix
								stack.append(lowerCAmelCase__						)  # push x to stack

				print(
				    x.center(8						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,sep=' | '							,)  # Output in tabular format

		while len(lowerCAmelCase__						) > 0:  # while stack is not empty
				post_fix.append(stack.pop()						)  # pop stack & add to Postfix
				print(
				    ' '.center(8						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,sep=' | '							,)  # Output in tabular format

		return "".join(lowerCAmelCase__						)  # return Postfix as str


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     Dict 						=      list(infix[::-1]						)  # reverse the infix equation

		for i in range(len(lowerCAmelCase__						)						):
				if infix[i] == "(":
						lowerCamelCase_	:     str 						=      ')'  # change "(" to ")"
				elif infix[i] == ")":
						lowerCamelCase_	:     Optional[Any] 						=      '('  # change ")" to "("

		return (infix_2_postfix(''.join(lowerCAmelCase__						)						))[
		    ::-1
		]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
		_lowercase		:  int			       =input("""\nEnter an Infix Equation = """)  # Input an Infix equation
		_lowercase		:  Optional[Any]			       ="""""".join(Infix.split())  # Remove spaces from the input
		print("""\n\t""", Infix, """(Infix) -> """, infix_2_prefix(Infix), """(Prefix)""")
