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This commit is contained in:
Maximilian Huettenrauch 2021-03-26 14:30:58 +01:00
parent 6233c85904
commit f730cb92ba
2 changed files with 21 additions and 19 deletions
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14
dmp_env_wrapper_example.py
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@ -16,12 +16,14 @@ if __name__ == "__main__":
test_env = make_holereacher_env(0)() test_env = make_holereacher_env(0)()
# params = np.random.randn(n_samples, dim) # params = np.random.randn(n_samples, dim)
params = np.array([[ 1.386102 , -3.29980525, 4.70402733, 1.3966668 , 0.73774902, params = np.array([ 0.57622273, 0.98294602, 1.48964131, 0.65430972,
3.14676681, -4.98644416, 6.20303193, 1.30502127, -0.09330522, -0.26028221, 4.84693322, 1.77366128, 0.51080511,
7.62656797, -5.76893033, 3.4706711 , -0.6944142 , -3.33442788, -2.38201107, -0.84990048, 1.02289828, 1.20675551,
12.31421548, -0.72760271, -6.9090723 , 7.02903814, -8.7236836 , 0.38075566, -1.84282938, -3.48690172, 2.17434711,
1.4805914 , 0.53185824, -5.46626893, 0.69692163, 13.58472666, -1.79285349, -1.7533641 , 0.62802966, 1.18928357,
0.77199316, 2.02906724, -3.0203244 , -1.00533159, -0.57417351]]) 0.2818753 , -3.27708291, -0.91761804, -0.38350967,
2.25849139, 21.57786524, -14.38494647, -11.5380005 ,
-11.09529721, -0.39453533])
# params = np.hstack([50 * np.random.randn(n_samples, 25), np.tile(np.array([np.pi/2, -np.pi/4, -np.pi/4, -np.pi/4, -np.pi/4]), [n_samples, 1])]) # params = np.hstack([50 * np.random.randn(n_samples, 25), np.tile(np.array([np.pi/2, -np.pi/4, -np.pi/4, -np.pi/4, -np.pi/4]), [n_samples, 1])])

26
dmp_pd_control_example.py
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@ -8,20 +8,20 @@ if __name__ == "__main__":
dim = 15 dim = 15
n_cpus = 4 n_cpus = 4
n_samples = 10 # n_samples = 10
vec_env = DmpAsyncVectorEnv([make_simple_env(i) for i in range(n_cpus)],
n_samples=n_samples)
params = np.tile(1 * np.random.randn(n_samples, dim), (10, 1))
rewards, infos = vec_env(params)
print(rewards)
# #
# non_vec_env = make_simple_env(0, 0)() # vec_env = DmpAsyncVectorEnv([make_simple_env(i) for i in range(n_cpus)],
# n_samples=n_samples)
# #
# params = 10 * np.random.randn(dim) # params = np.tile(1 * np.random.randn(n_samples, dim), (10, 1))
#
# rewards, infos = vec_env(params)
# print(rewards)
#
non_vec_env = make_simple_env(0, 0)()
# out2 = non_vec_env.rollout(params, render=True) params = 0.1 * np.random.randn(dim)
# print(out2) out2 = non_vec_env.rollout(params, render=True)
print(out2)