if args.mp:
num_processes = min([hp.nb_directions, max_processes])
print('processes: ', num_processes)
processes = []
childPipes = []
parentPipes = []
for pr in range(num_processes):
parentPipe, childPipe = Pipe()
parentPipes.append(parentPipe)
childPipes.append(childPipe)
for rank in range(num_processes):
p = mp.Process(target=ExploreWorker,
args=(rank, childPipes[rank], hp.env_name, args))
p.start()
processes.append(p)
# env = stoch2_gym_env.StochBulletEnv(render = False, gait = 'trot')
nb_inputs = env.observation_space.sample().shape[0]
nb_outputs = env.action_space.sample().shape[0] * 2
policy = Policy(nb_inputs, nb_outputs, hp.env_name, hp.normal, args)
hp.nb_directions = int(policy.theta.shape[0] * policy.theta.shape[1])
hp.nb_best_directions = int(hp.nb_directions / 2)
normalizer = Normalizer(nb_inputs)
print("start training")
train(env, policy, normalizer, hp, parentPipes, args)
if args.mp:
for parentPipe in parentPipes:
# Author: Sida Liu 2020 ([email protected]) # This is a demo of using wrappers import pybullet as p # This tricky import brings back the IntelliSense if this repo exists as a subfolder of a workspace. if __name__ == '__main__': from pybullet_wrapper.base import BaseWrapperPyBullet from pybullet_wrapper.handy import HandyPyBullet else: from .pybullet_wrapper.base import BaseWrapperPyBullet from .pybullet_wrapper.handy import HandyPyBullet p = BaseWrapperPyBullet(p) p = HandyPyBullet(p) p.start(withPanels=True) while True: p.stepSimulation() p.sleep()
