
"""simple docstring"""




from typing import Any



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a,				):
		_validation(
		    __a,				__a,				__a,				__a,				__a,				)
		# Creates data structures and fill initial step
		SCREAMING_SNAKE_CASE_    			=			{}
		SCREAMING_SNAKE_CASE_    			=			{}
		for state in states_space:
				SCREAMING_SNAKE_CASE_    			=			observations_space[0]
				SCREAMING_SNAKE_CASE_    			=			(
				    initial_probabilities[state] * emission_probabilities[state][observation]
				)
				SCREAMING_SNAKE_CASE_    			=			None

		# Fills the data structure with the probabilities of
		# different transitions and pointers to previous states
		for o in range(1,				len(__a     )     ):
				SCREAMING_SNAKE_CASE_    			=			observations_space[o]
				SCREAMING_SNAKE_CASE_    			=			observations_space[o - 1]
				for state in states_space:
						# Calculates the argmax for probability function
						SCREAMING_SNAKE_CASE_    			=			''''''
						SCREAMING_SNAKE_CASE_    			=			-1
						for k_state in states_space:
								SCREAMING_SNAKE_CASE_    			=			(
								    probabilities[(k_state, prior_observation)]
								    * transition_probabilities[k_state][state]
								    * emission_probabilities[state][observation]
								)
								if probability > max_probability:
										SCREAMING_SNAKE_CASE_    			=			probability
										SCREAMING_SNAKE_CASE_    			=			k_state

            # Update probabilities and pointers dicts
						SCREAMING_SNAKE_CASE_    			=			(
						    probabilities[(arg_max, prior_observation)]
						    * transition_probabilities[arg_max][state]
						    * emission_probabilities[state][observation]
						)

						SCREAMING_SNAKE_CASE_    			=			arg_max

    # The final observation
		SCREAMING_SNAKE_CASE_    			=			observations_space[len(__a     ) - 1]

		# argmax for given final observation
		SCREAMING_SNAKE_CASE_    			=			''''''
		SCREAMING_SNAKE_CASE_    			=			-1
		for k_state in states_space:
				SCREAMING_SNAKE_CASE_    			=			probabilities[(k_state, final_observation)]
				if probability > max_probability:
						SCREAMING_SNAKE_CASE_    			=			probability
						SCREAMING_SNAKE_CASE_    			=			k_state
		SCREAMING_SNAKE_CASE_    			=			arg_max

		# Process pointers backwards
		SCREAMING_SNAKE_CASE_    			=			last_state
		SCREAMING_SNAKE_CASE_    			=			[]
		for o in range(len(__a     ) - 1,				-1,				-1     ):
				result.append(__a     )
				SCREAMING_SNAKE_CASE_    			=			pointers[previous, observations_space[o]]
		result.reverse()

		return result



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a,				):
		_validate_not_empty(
		    __a,				__a,				__a,				__a,				__a,				)
		_validate_lists(__a,				__a     )
		_validate_dicts(
		    __a,				__a,				__a     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a,				):
		if not all(
		    [
		        observations_space,
		        states_space,
		        initial_probabilities,
		        transition_probabilities,
		        emission_probabilities,
		    ]     ):
				raise ValueError('''There\'s an empty parameter'''     )



def 							_lowerCamelCase			(			__a,				__a     ):
		_validate_list(__a,				'''observations_space'''     )
		_validate_list(__a,				'''states_space'''     )



def 							_lowerCamelCase			(			__a,				__a     ):
		if not isinstance(_object,				__a     ):
				SCREAMING_SNAKE_CASE_    			=			F'{var_name} must be a list'
				raise ValueError(__a     )
		else:
				for x in _object:
						if not isinstance(__a,				__a     ):
								SCREAMING_SNAKE_CASE_    			=			F'{var_name} must be a list of strings'
								raise ValueError(__a     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				):
		_validate_dict(__a,				'''initial_probabilities''',				__a     )
		_validate_nested_dict(__a,				'''transition_probabilities'''     )
		_validate_nested_dict(__a,				'''emission_probabilities'''     )



def 							_lowerCamelCase			(			__a,				__a     ):
		_validate_dict(_object,				__a,				__a     )
		for x in _object.values():
				_validate_dict(__a,				__a,				__a,				__a     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a = False     ):
		if not isinstance(_object,				__a     ):
				SCREAMING_SNAKE_CASE_    			=			F'{var_name} must be a dict'
				raise ValueError(__a     )
		if not all(isinstance(__a,				__a     ) for x in _object     ):
				SCREAMING_SNAKE_CASE_    			=			F'{var_name} all keys must be strings'
				raise ValueError(__a     )
		if not all(isinstance(__a,				__a     ) for x in _object.values()     ):
				SCREAMING_SNAKE_CASE_    			=			'''nested dictionary ''' if nested else ''''''
				SCREAMING_SNAKE_CASE_    			=			F'{var_name} {nested_text}all values must be {value_type.__name__}'
				raise ValueError(__a     )


if __name__ == "__main__":
						from doctest import testmod

						testmod()

"""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 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a=0     ):
		os.makedirs(__a,				exist_ok=__a     )
		with FSDP.state_dict_type(
		    __a,				fsdp_plugin.state_dict_type,				fsdp_plugin.state_dict_config,				fsdp_plugin.optim_state_dict_config     ):
				SCREAMING_SNAKE_CASE_    			=			model.state_dict()
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			F'{MODEL_NAME}.bin' if model_index == 0 else F'{MODEL_NAME}_{model_index}.bin'
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						if accelerator.process_index == 0:
								logger.info(F'Saving model to {output_model_file}'     )
								torch.save(__a,				__a     )
								logger.info(F'Model saved to {output_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			(
						    F'{MODEL_NAME}_rank{accelerator.process_index}.bin'
						    if model_index == 0
						    else F'{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'
						)
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Saving model to {output_model_file}'     )
						torch.save(__a,				__a     )
						logger.info(F'Model saved to {output_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				F'{MODEL_NAME}_{model_index}'     )
						os.makedirs(__a,				exist_ok=__a     )
						logger.info(F'Saving model to {ckpt_dir}'     )
						SCREAMING_SNAKE_CASE_    			=			{'''model''': state_dict}

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



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a=0     ):
		accelerator.wait_for_everyone()
		with FSDP.state_dict_type(
		    __a,				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(__a     ) != 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
						SCREAMING_SNAKE_CASE_    			=			F'{MODEL_NAME}.bin' if model_index == 0 else F'{MODEL_NAME}_{model_index}.bin'
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Loading model from {input_model_file}'     )
						SCREAMING_SNAKE_CASE_    			=			torch.load(__a     )
						logger.info(F'Model loaded from {input_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			(
						    F'{MODEL_NAME}_rank{accelerator.process_index}.bin'
						    if model_index == 0
						    else F'{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'
						)
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Loading model from {input_model_file}'     )
						SCREAMING_SNAKE_CASE_    			=			torch.load(__a     )
						logger.info(F'Model loaded from {input_model_file}'     )
				elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
						SCREAMING_SNAKE_CASE_    			=			(
						    os.path.join(__a,				F'{MODEL_NAME}_{model_index}'     )
						    if F'{MODEL_NAME}' not in input_dir
						    else input_dir
						)
						logger.info(F'Loading model from {ckpt_dir}'     )
						SCREAMING_SNAKE_CASE_    			=			{'''model''': model.state_dict()}
						dist_cp.load_state_dict(
						    state_dict=__a,				storage_reader=dist_cp.FileSystemReader(__a     ),				planner=DefaultLoadPlanner(),				)
						SCREAMING_SNAKE_CASE_    			=			state_dict['''model''']
						logger.info(F'Model loaded from {ckpt_dir}'     )
				model.load_state_dict(__a     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a,				__a=0     ):
		os.makedirs(__a,				exist_ok=__a     )
		with FSDP.state_dict_type(
		    __a,				fsdp_plugin.state_dict_type,				fsdp_plugin.state_dict_config,				fsdp_plugin.optim_state_dict_config     ):
				SCREAMING_SNAKE_CASE_    			=			FSDP.optim_state_dict(__a,				__a     )
				if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
						if accelerator.process_index == 0:
								SCREAMING_SNAKE_CASE_    			=			(
								    F'{OPTIMIZER_NAME}.bin' if optimizer_index == 0 else F'{OPTIMIZER_NAME}_{optimizer_index}.bin'
								)
								SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
								logger.info(F'Saving Optimizer state to {output_optimizer_file}'     )
								torch.save(__a,				__a     )
								logger.info(F'Optimizer state saved in {output_optimizer_file}'     )
				else:
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				F'{OPTIMIZER_NAME}_{optimizer_index}'     )
						os.makedirs(__a,				exist_ok=__a     )
						logger.info(F'Saving Optimizer state to {ckpt_dir}'     )
						dist_cp.save_state_dict(
						    state_dict={'''optimizer''': optim_state},				storage_writer=dist_cp.FileSystemWriter(__a     ),				planner=DefaultSavePlanner(),				)
						logger.info(F'Optimizer state saved in {ckpt_dir}'     )



def 							_lowerCamelCase			(			__a,				__a,				__a,				__a,				__a,				__a=0     ):
		accelerator.wait_for_everyone()
		with FSDP.state_dict_type(
		    __a,				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:
						SCREAMING_SNAKE_CASE_    			=			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:
						SCREAMING_SNAKE_CASE_    			=			(
						    F'{OPTIMIZER_NAME}.bin' if optimizer_index == 0 else F'{OPTIMIZER_NAME}_{optimizer_index}.bin'
						)
						SCREAMING_SNAKE_CASE_    			=			os.path.join(__a,				__a     )
						logger.info(F'Loading Optimizer state from {input_optimizer_file}'     )
						SCREAMING_SNAKE_CASE_    			=			torch.load(__a     )
						logger.info(F'Optimizer state loaded from {input_optimizer_file}'     )
				else:
						SCREAMING_SNAKE_CASE_    			=			(
						    os.path.join(__a,				F'{OPTIMIZER_NAME}_{optimizer_index}'     )
						    if F'{OPTIMIZER_NAME}' not in input_dir
						    else input_dir
						)
						logger.info(F'Loading Optimizer from {ckpt_dir}'     )
						SCREAMING_SNAKE_CASE_    			=			load_sharded_optimizer_state_dict(
						    model_state_dict=model.state_dict(),				optimizer_key='''optimizer''',				storage_reader=dist_cp.FileSystemReader(__a     ),				)
						SCREAMING_SNAKE_CASE_    			=			optim_state['''optimizer''']
						logger.info(F'Optimizer loaded from {ckpt_dir}'     )
				SCREAMING_SNAKE_CASE_    			=			FSDP.optim_state_dict_to_load(__a,				__a,				__a     )
				optimizer.load_state_dict(__a     )