def main(cls, parse_args):
args, device = cls.initialize(parse_args())
##########################################
# update args for pre-trained primitives
# ****************************************
ckpts = cls.load_checkpoints(args.primitives,
args,
ckpt_type='primitive')
args = cls.update_dirs_primitive(args,
[c['args'].expname for c in ckpts])
args.num_primitives = len(ckpts)
##########################################
logger = MultiBaseLogger(args=args)
task_progression = cls.create_task_progression(logger, args)
organism = cls.create_organism(device, task_progression, args)
##########################################
# load weights for pre-trained primitives
# ****************************************
organism = cls.load_primitive_weights(organism, ckpts, logger.printf)
##########################################
rl_alg = rlalg_switch(args.alg_name)(device=device, args=args)
experiment = Experiment(learner=CentralizedLearner(
organism=organism,
rl_alg=rl_alg,
logger=logger,
device=device,
args=args,
),
task_progression=task_progression,
logger=logger,
args=args)
experiment.main_loop(max_epochs=args.max_epochs)
def main(cls, parse_args):
args, device = cls.initialize(parse_args())
logger = MultiBaseLogger(args=args)
task_progression = cls.create_task_progression(logger, args)
organism = cls.create_organism(device, task_progression, args)
rl_alg = rlalg_switch(args.alg_name)(device=device, args=args)
experiment_builder = cls.experiment_switch(args.env_name[0])
experiment = experiment_builder(society=organism,
task_progression=task_progression,
rl_alg=rl_alg,
logger=logger,
device=device,
args=args)
experiment.main_loop(max_epochs=args.max_epochs)
def main(cls, parse_args):
args, device = cls.initialize(parse_args())
logger = MultiBaseLogger(args=args)
task_progression = cls.create_task_progression(logger, args)
organism = cls.create_organism(device, task_progression, args)
rl_alg = rlalg_switch(args.alg_name)(device=device, args=args)
experiment = Experiment(learner=CentralizedLearner(
organism=organism,
rl_alg=rl_alg,
logger=logger,
device=device,
args=args,
),
task_progression=task_progression,
logger=logger,
args=args)
experiment.main_loop(max_epochs=args.max_epochs)
def main(cls, parse_args):
args, device = cls.initialize(parse_args())
# ########################################
# update args for pre-trained parent
# ****************************************
parent_ckpts = cls.load_checkpoints(args.ckpts,
args,
ckpt_type='parent')
args = cls.update_dirs_parent(
args, [c['args'].expname for c in parent_ckpts])
args = cls.transfer_args(args, parent_ckpts)
# ****************************************
# update args for pre-trained primitives
# ****************************************
primitive_ckpts = cls.load_checkpoints(args.primitives,
args,
ckpt_type='primitive')
args = cls.update_dirs_primitive(
args, [c['args'].expname for c in primitive_ckpts])
args.num_primitives = len(primitive_ckpts)
##########################################
logger = MultiBaseLogger(args=args)
task_progression = cls.create_task_progression(logger, args)
organism = cls.create_organism(device, task_progression, args)
##########################################
# load weights for pre-trained primitives
# ****************************************
organism = cls.load_primitive_weights(organism, primitive_ckpts,
logger.printf)
# ****************************************
# load weights for parents
# ****************************************
organism = cls.load_organism_weights(organism, parent_ckpts,
logger.printf)
##########################################
rl_alg = rlalg_switch(args.alg_name)(device=device, args=args)
experiment_builder = cls.experiment_switch(args.env_name[0])
experiment = experiment_builder(society=organism,
task_progression=task_progression,
rl_alg=rl_alg,
logger=logger,
device=device,
args=args)
experiment.main_loop(max_epochs=args.max_epochs)