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import torch
from copy import deepcopy
from dizoo.classic_control.pendulum.config.pendulum_sac_data_generation_default_config import main_config, create_config
from ding.entry import serial_pipeline_offline, collect_demo_data, eval, serial_pipeline
def train_cql(args):
from dizoo.classic_control.pendulum.config.pendulum_cql_config import main_config, create_config
main_config.exp_name = 'cql_sac'
main_config.policy.collect.data_path = './sac/expert_demos.hdf5'
main_config.policy.collect.data_type = 'hdf5'
config = deepcopy([main_config, create_config])
serial_pipeline_offline(config, seed=args.seed)
def eval_ckpt(args):
main_config.exp_name = 'sac'
main_config.policy.learn.learner.load_path = './sac/ckpt/ckpt_best.pth.tar'
main_config.policy.learn.learner.hook.load_ckpt_before_run = './sac/ckpt/ckpt_best.pth.tar'
state_dict = torch.load(main_config.policy.learn.learner.load_path, map_location='cpu')
config = deepcopy([main_config, create_config])
eval(config, seed=args.seed, load_path=main_config.policy.learn.learner.hook.load_ckpt_before_run)
def generate(args):
main_config.exp_name = 'sac'
main_config.policy.learn.learner.load_path = './sac/ckpt/ckpt_best.pth.tar'
main_config.policy.collect.save_path = './sac/expert.pkl'
main_config.policy.collect.data_type = 'hdf5'
config = deepcopy([main_config, create_config])
state_dict = torch.load(main_config.policy.learn.learner.load_path, map_location='cpu')
collect_demo_data(
config,
collect_count=main_config.policy.other.replay_buffer.replay_buffer_size,
seed=args.seed,
expert_data_path=main_config.policy.collect.save_path,
state_dict=state_dict
)
def train_expert(args):
from dizoo.classic_control.pendulum.config.pendulum_sac_config import main_config, create_config
config = deepcopy([main_config, create_config])
config[0].exp_name = 'sac'
serial_pipeline(config, seed=args.seed)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--seed', '-s', type=int, default=10)
args = parser.parse_args()
train_expert(args)
eval_ckpt(args)
generate(args)
train_cql(args)
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