pybullet a bit more refactoring, moving around files.
pybullet: move data to pybullet_data package, with getDataPath() method
This commit is contained in:
@@ -0,0 +1,44 @@
|
||||
#add parent dir to find package. Only needed for source code build, pip install doesn't need it.
|
||||
import os, inspect
|
||||
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
|
||||
parentdir = os.path.dirname(os.path.dirname(currentdir))
|
||||
os.sys.path.insert(0,parentdir)
|
||||
|
||||
import gym
|
||||
from pybullet_envs.bullet.racecarGymEnv import RacecarGymEnv
|
||||
|
||||
from baselines import deepq
|
||||
|
||||
import datetime
|
||||
|
||||
|
||||
|
||||
def callback(lcl, glb):
|
||||
# stop training if reward exceeds 199
|
||||
total = sum(lcl['episode_rewards'][-101:-1]) / 100
|
||||
totalt = lcl['t']
|
||||
is_solved = totalt > 2000 and total >= -50
|
||||
return is_solved
|
||||
|
||||
|
||||
def main():
|
||||
|
||||
env = RacecarGymEnv(renders=False,isDiscrete=True)
|
||||
model = deepq.models.mlp([64])
|
||||
act = deepq.learn(
|
||||
env,
|
||||
q_func=model,
|
||||
lr=1e-3,
|
||||
max_timesteps=10000,
|
||||
buffer_size=50000,
|
||||
exploration_fraction=0.1,
|
||||
exploration_final_eps=0.02,
|
||||
print_freq=10,
|
||||
callback=callback
|
||||
)
|
||||
print("Saving model to racecar_model.pkl")
|
||||
act.save("racecar_model.pkl")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
Reference in New Issue
Block a user