851ca5bfb3
Use python -m pybullet_envs.examples.testEnv --env AntBulletEnv-v0 --render=1 --steps 1000 --resetbenchmark=1 Added environments: HumanoidFlagrunBulletEnv-v0, HumanoidFlagrunHarderBulletEnv-v0, StrikerBulletEnv-v0, ThrowerBulletEnv-v0, PusherBulletEnv-v0, ReacherBulletEnv-v0, CartPoleBulletEnv-v0 and register them to OpenAI Gym. Allow numpy/humanoid_running.py to use abtch or non-batch update (setJointMotorControl2/setJointMotorControlArray)
58 lines
1.6 KiB
Python
58 lines
1.6 KiB
Python
import os
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import inspect
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currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
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parentdir = os.path.dirname(os.path.dirname(currentdir))
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os.sys.path.insert(0,parentdir)
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import pybullet_envs
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import gym
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import argparse
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import pybullet as p
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def test(args):
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count = 0
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env = gym.make(args.env)
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env.env.configure(args)
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print("args.render=",args.render)
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if (args.render==1):
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env.render(mode="human")
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env.reset()
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if (args.resetbenchmark):
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while (1):
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env.reset()
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print("p.getNumBodies()=",p.getNumBodies())
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print("count=",count)
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count+=1
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print("action space:")
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sample = env.action_space.sample()
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action = sample*0.0
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print("action=")
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print(action)
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for i in range(args.steps):
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obs,rewards,done,_ =env.step(action)
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if (args.rgb):
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print(env.render(mode="rgb_array"))
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print("obs=")
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print(obs)
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print("rewards")
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print (rewards)
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print ("done")
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print(done)
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def main():
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import argparse
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parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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parser.add_argument('--env', help='environment ID', default='AntBulletEnv-v0')
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parser.add_argument('--seed', help='RNG seed', type=int, default=0)
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parser.add_argument('--render', help='OpenGL Visualizer', type=int, default=0)
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parser.add_argument('--rgb',help='rgb_array gym rendering',type=int, default=0)
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parser.add_argument('--resetbenchmark',help='Repeat reset to show reset performance',type=int, default=0)
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parser.add_argument('--steps', help='Number of steps', type=int, default=1)
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args = parser.parse_args()
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test(args)
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if __name__ == '__main__':
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main()
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