File size: 1,529 Bytes
079c32c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
import gym
from ditk import logging
import torch
from ding.model import ContinuousQAC
from ding.policy import SACPolicy
from ding.envs import DingEnvWrapper, BaseEnvManagerV2
from ding.data import offline_data_save_type
from ding.config import compile_config
from ding.framework import task
from ding.framework.context import OnlineRLContext
from ding.framework.middleware import StepCollector, offline_data_saver
from ding.utils import set_pkg_seed
from dizoo.classic_control.pendulum.envs.pendulum_env import PendulumEnv
from dizoo.classic_control.pendulum.config.pendulum_sac_data_generation_config import main_config, create_config
def main():
logging.getLogger().setLevel(logging.INFO)
cfg = compile_config(main_config, create_cfg=create_config, auto=True, evaluator=None)
with task.start(async_mode=False, ctx=OnlineRLContext()):
collector_env = BaseEnvManagerV2(env_fn=[lambda: PendulumEnv(cfg.env) for _ in range(10)], cfg=cfg.env.manager)
set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda)
model = ContinuousQAC(**cfg.policy.model)
policy = SACPolicy(cfg.policy, model=model, enable_field=['collect'])
state_dict = torch.load(cfg.policy.collect.state_dict_path, map_location='cpu')
policy.collect_mode.load_state_dict(state_dict)
task.use(StepCollector(cfg, policy.collect_mode, collector_env))
task.use(offline_data_saver(cfg.policy.collect.save_path, data_type='hdf5'))
task.run(max_step=1)
if __name__ == "__main__":
main()
|