Initial commit
Browse files- README.md +1 -1
- a2c-PandaReachDense-v2.zip +2 -2
- a2c-PandaReachDense-v2/data +18 -16
- a2c-PandaReachDense-v2/policy.optimizer.pth +2 -2
- a2c-PandaReachDense-v2/policy.pth +2 -2
- config.json +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
- vec_normalize.pkl +1 -1
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: PandaReachDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value: -
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: PandaReachDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: -0.61 +/- 0.20
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
a2c-PandaReachDense-v2.zip
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d3c536f4fafc8c6c98bfea0eeefa565bbb6efc9df8e7a035059358eea49bb073
|
3 |
+
size 109675
|
a2c-PandaReachDense-v2/data
CHANGED
@@ -11,7 +11,9 @@
|
|
11 |
"verbose": 1,
|
12 |
"policy_kwargs": {
|
13 |
":type:": "<class 'dict'>",
|
14 |
-
":serialized:": "
|
|
|
|
|
15 |
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
16 |
"optimizer_kwargs": {
|
17 |
"alpha": 0.99,
|
@@ -24,19 +26,19 @@
|
|
24 |
"_num_timesteps_at_start": 0,
|
25 |
"seed": null,
|
26 |
"action_noise": null,
|
27 |
-
"start_time":
|
28 |
-
"learning_rate": 0.
|
29 |
"tensorboard_log": null,
|
30 |
"lr_schedule": {
|
31 |
":type:": "<class 'function'>",
|
32 |
-
":serialized:": "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
|
33 |
},
|
34 |
"_last_obs": {
|
35 |
":type:": "<class 'collections.OrderedDict'>",
|
36 |
-
":serialized:": "
|
37 |
-
"achieved_goal": "[[0.
|
38 |
-
"desired_goal": "[[
|
39 |
-
"observation": "[[
|
40 |
},
|
41 |
"_last_episode_starts": {
|
42 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -44,30 +46,30 @@
|
|
44 |
},
|
45 |
"_last_original_obs": {
|
46 |
":type:": "<class 'collections.OrderedDict'>",
|
47 |
-
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////
|
48 |
"achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]",
|
49 |
-
"desired_goal": "[[ 0.
|
50 |
"observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
|
51 |
},
|
52 |
"_episode_num": 0,
|
53 |
-
"use_sde":
|
54 |
"sde_sample_freq": -1,
|
55 |
"_current_progress_remaining": 0.0,
|
56 |
"_stats_window_size": 100,
|
57 |
"ep_info_buffer": {
|
58 |
":type:": "<class 'collections.deque'>",
|
59 |
-
":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////
|
60 |
},
|
61 |
"ep_success_buffer": {
|
62 |
":type:": "<class 'collections.deque'>",
|
63 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
64 |
},
|
65 |
-
"_n_updates":
|
66 |
-
"n_steps":
|
67 |
"gamma": 0.99,
|
68 |
-
"gae_lambda":
|
69 |
"ent_coef": 0.0,
|
70 |
-
"vf_coef": 0.
|
71 |
"max_grad_norm": 0.5,
|
72 |
"normalize_advantage": false,
|
73 |
"observation_space": {
|
|
|
11 |
"verbose": 1,
|
12 |
"policy_kwargs": {
|
13 |
":type:": "<class 'dict'>",
|
14 |
+
":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
|
15 |
+
"log_std_init": -2,
|
16 |
+
"ortho_init": false,
|
17 |
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
18 |
"optimizer_kwargs": {
|
19 |
"alpha": 0.99,
|
|
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
+
"start_time": 1681375142849072290,
|
30 |
+
"learning_rate": 0.00096,
|
31 |
"tensorboard_log": null,
|
32 |
"lr_schedule": {
|
33 |
":type:": "<class 'function'>",
|
34 |
+
":serialized:": "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"
|
35 |
},
|
36 |
"_last_obs": {
|
37 |
":type:": "<class 'collections.OrderedDict'>",
|
38 |
+
":serialized:": "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",
|
39 |
+
"achieved_goal": "[[ 0.43085906 -0.00301856 0.59868556]\n [ 0.43085906 -0.00301856 0.59868556]\n [ 0.43085906 -0.00301856 0.59868556]\n [ 0.43085906 -0.00301856 0.59868556]]",
|
40 |
+
"desired_goal": "[[ 0.10309792 1.5590055 -0.5663382 ]\n [ 0.9556199 0.14618732 1.3841752 ]\n [ 1.282797 0.7711009 0.4337387 ]\n [-1.1935312 0.33299118 1.60713 ]]",
|
41 |
+
"observation": "[[ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]\n [ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]\n [ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]\n [ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]]"
|
42 |
},
|
43 |
"_last_episode_starts": {
|
44 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
46 |
},
|
47 |
"_last_original_obs": {
|
48 |
":type:": "<class 'collections.OrderedDict'>",
|
49 |
+
":serialized:": "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",
|
50 |
"achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]",
|
51 |
+
"desired_goal": "[[ 0.01209264 0.08778638 0.2352361 ]\n [-0.11432365 0.08557644 0.2670476 ]\n [ 0.015327 0.08269451 0.28230497]\n [ 0.08827544 0.1304073 0.12207159]]",
|
52 |
"observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
|
53 |
},
|
54 |
"_episode_num": 0,
|
55 |
+
"use_sde": true,
|
56 |
"sde_sample_freq": -1,
|
57 |
"_current_progress_remaining": 0.0,
|
58 |
"_stats_window_size": 100,
|
59 |
"ep_info_buffer": {
|
60 |
":type:": "<class 'collections.deque'>",
|
61 |
+
":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBYwubw5X7b+UhpRSlIwBbJRLMowBdJRHQKgvTL26ClJ1fZQoaAZoCWgPQwjOwTOhSWLlv5SGlFKUaBVLMmgWR0CoLxKnNxEOdX2UKGgGaAloD0MIYVPnUfE/8b+UhpRSlGgVSzJoFkdAqC7UqQRwqHV9lChoBmgJaA9DCDOkiuJV1uO/lIaUUpRoFUsyaBZHQKgulcqvvBt1fZQoaAZoCWgPQwhDGhU42Ubyv5SGlFKUaBVLMmgWR0CoMK8kUsWgdX2UKGgGaAloD0MILZljeVe94L+UhpRSlGgVSzJoFkdAqDB0edTYNHV9lChoBmgJaA9DCLqFrkSg+t2/lIaUUpRoFUsyaBZHQKgwNdszl911fZQoaAZoCWgPQwjVXdkFg+vlv5SGlFKUaBVLMmgWR0CoL/YgA6uGdX2UKGgGaAloD0MIsfojDAOW6r+UhpRSlGgVSzJoFkdAqDG6I55qunV9lChoBmgJaA9DCPd4IR0ewsq/lIaUUpRoFUsyaBZHQKgxf2C/XXl1fZQoaAZoCWgPQwhp5POKpx7kv5SGlFKUaBVLMmgWR0CoMUBdD6WPdX2UKGgGaAloD0MImMEYkSg057+UhpRSlGgVSzJoFkdAqDEAZIg/1XV9lChoBmgJaA9DCOtWz0nvG/K/lIaUUpRoFUsyaBZHQKgyy7wrlNl1fZQoaAZoCWgPQwhAijpzD4nlv5SGlFKUaBVLMmgWR0CoMpDn/1g6dX2UKGgGaAloD0MI2qhOB7Ie8b+UhpRSlGgVSzJoFkdAqDJSABkqc3V9lChoBmgJaA9DCBu7RPXWQOa/lIaUUpRoFUsyaBZHQKgyEjM3ZPF1fZQoaAZoCWgPQwjxY8xdS8j0v5SGlFKUaBVLMmgWR0CoM863iJfqdX2UKGgGaAloD0MIRL5LqUvG3r+UhpRSlGgVSzJoFkdAqDOUsDnvD3V9lChoBmgJaA9DCMgG0sWmlee/lIaUUpRoFUsyaBZHQKgzVn4fwJB1fZQoaAZoCWgPQwjaqiSyDzLmv5SGlFKUaBVLMmgWR0CoMxeEh7mddX2UKGgGaAloD0MI9Q8iGXKs9L+UhpRSlGgVSzJoFkdAqDThlBhQWXV9lChoBmgJaA9DCFw5e2e01eW/lIaUUpRoFUsyaBZHQKg0prk8zRB1fZQoaAZoCWgPQwjCwHPv4RLov5SGlFKUaBVLMmgWR0CoNGgAhje9dX2UKGgGaAloD0MIJPHydK6o6r+UhpRSlGgVSzJoFkdAqDQoXGff43V9lChoBmgJaA9DCJ1KBoAq7um/lIaUUpRoFUsyaBZHQKg150DEFW51fZQoaAZoCWgPQwhK7xtfe8YAwJSGlFKUaBVLMmgWR0CoNax+8XendX2UKGgGaAloD0MIYJSgv9Aj9r+UhpRSlGgVSzJoFkdAqDVtmSQo1HV9lChoBmgJaA9DCLtjsU0qGu6/lIaUUpRoFUsyaBZHQKg1La9K28Z1fZQoaAZoCWgPQwiKVYMwt/vuv5SGlFKUaBVLMmgWR0CoNv1x82JjdX2UKGgGaAloD0MIZw+0AkNW6b+UhpRSlGgVSzJoFkdAqDbCv3ai9XV9lChoBmgJaA9DCDiie9Y1Wve/lIaUUpRoFUsyaBZHQKg2hAmAskJ1fZQoaAZoCWgPQwgno8ow7gbtv5SGlFKUaBVLMmgWR0CoNkQtSQ5ndX2UKGgGaAloD0MIXVFKCFbV57+UhpRSlGgVSzJoFkdAqDgJBu4wy3V9lChoBmgJaA9DCC3pKAezCea/lIaUUpRoFUsyaBZHQKg3zj8UEgZ1fZQoaAZoCWgPQwgA5lq0AO3uv5SGlFKUaBVLMmgWR0CoN49sJpnIdX2UKGgGaAloD0MI9UcYBiw56r+UhpRSlGgVSzJoFkdAqDdPvrnkk3V9lChoBmgJaA9DCNScvMgEfO2/lIaUUpRoFUsyaBZHQKg5DHjIaLp1fZQoaAZoCWgPQwgEV3kCYafhv5SGlFKUaBVLMmgWR0CoONGcnVoYdX2UKGgGaAloD0MICFbVy++07b+UhpRSlGgVSzJoFkdAqDiS6H0sfHV9lChoBmgJaA9DCH+hR4yeW+a/lIaUUpRoFUsyaBZHQKg4UttALRd1fZQoaAZoCWgPQwjEJFzII7jjv5SGlFKUaBVLMmgWR0CoOh+lsP8RdX2UKGgGaAloD0MIKNap8j0j5r+UhpRSlGgVSzJoFkdAqDnk5OrQxHV9lChoBmgJaA9DCJM4K6Imeuy/lIaUUpRoFUsyaBZHQKg5piKBNEh1fZQoaAZoCWgPQwhGQ8ajVELkv5SGlFKUaBVLMmgWR0CoOWY5Lh73dX2UKGgGaAloD0MIBcO5hhna9L+UhpRSlGgVSzJoFkdAqDs0otthu3V9lChoBmgJaA9DCLhYUYNpGOu/lIaUUpRoFUsyaBZHQKg6+eT3Zf51fZQoaAZoCWgPQwhtAgzLn+/vv5SGlFKUaBVLMmgWR0CoOrscZLqVdX2UKGgGaAloD0MIq5ffaTLj0r+UhpRSlGgVSzJoFkdAqDp7PUrkKnV9lChoBmgJaA9DCOPD7GXbadq/lIaUUpRoFUsyaBZHQKg8QpgkTpR1fZQoaAZoCWgPQwiDwTV39L/mv5SGlFKUaBVLMmgWR0CoPAfKISDidX2UKGgGaAloD0MINPPkmgIZ9L+UhpRSlGgVSzJoFkdAqDvJI1+AmXV9lChoBmgJaA9DCNEHy9jQTey/lIaUUpRoFUsyaBZHQKg7iSeRPoF1fZQoaAZoCWgPQwiZYaOs38z6v5SGlFKUaBVLMmgWR0CoPVCrLhaUdX2UKGgGaAloD0MI63O1FfsL8r+UhpRSlGgVSzJoFkdAqD0V6NVBEHV9lChoBmgJaA9DCK3AkNWtHum/lIaUUpRoFUsyaBZHQKg81zND+it1fZQoaAZoCWgPQwjg9gSJ7W7nv5SGlFKUaBVLMmgWR0CoPJeSB9ThdX2UKGgGaAloD0MIkuaPaW0a1r+UhpRSlGgVSzJoFkdAqD5n4CZF5XV9lChoBmgJaA9DCEfmkT8YeN+/lIaUUpRoFUsyaBZHQKg+LR0lqrR1fZQoaAZoCWgPQwgPRYE+kSfcv5SGlFKUaBVLMmgWR0CoPe52pyZKdX2UKGgGaAloD0MIe9tMhXik7b+UhpRSlGgVSzJoFkdAqD2uu1WsBHV9lChoBmgJaA9DCByastMP6uW/lIaUUpRoFUsyaBZHQKg/bDZUT+N1fZQoaAZoCWgPQwjHTKJe8Onkv5SGlFKUaBVLMmgWR0CoPzFeOXE7dX2UKGgGaAloD0MI+kFdpFCW5r+UhpRSlGgVSzJoFkdAqD7yYLLIP3V9lChoBmgJaA9DCBgJbTmX4t+/lIaUUpRoFUsyaBZHQKg+soNutOp1fZQoaAZoCWgPQwirPeyFArbpv5SGlFKUaBVLMmgWR0CoQGiuEEkjdX2UKGgGaAloD0MIFOeoo+Pq4L+UhpRSlGgVSzJoFkdAqEAt2icoY3V9lChoBmgJaA9DCLTk8bT8wNy/lIaUUpRoFUsyaBZHQKg/7v4ubqh1fZQoaAZoCWgPQwgBMnTsoFLwv5SGlFKUaBVLMmgWR0CoP67t7a7FdX2UKGgGaAloD0MIhel7DcFx4L+UhpRSlGgVSzJoFkdAqEGHVNHpbHV9lChoBmgJaA9DCFioNc07Ttq/lIaUUpRoFUsyaBZHQKhBTJEH+qB1fZQoaAZoCWgPQwjlXmBWKNLgv5SGlFKUaBVLMmgWR0CoQQ3TmW+odX2UKGgGaAloD0MIxZEHIos06b+UhpRSlGgVSzJoFkdAqEDOD6Fds3V9lChoBmgJaA9DCCJVFK+yNua/lIaUUpRoFUsyaBZHQKhCl78ejmF1fZQoaAZoCWgPQwhdhv90AwXiv5SGlFKUaBVLMmgWR0CoQl0aAFxGdX2UKGgGaAloD0MINUOqKF5l37+UhpRSlGgVSzJoFkdAqEIeK4x1xXV9lChoBmgJaA9DCGQ+INCZNOy/lIaUUpRoFUsyaBZHQKhB3kLhJiB1fZQoaAZoCWgPQwhWtg95y1Xhv5SGlFKUaBVLMmgWR0CoQ6AUDdP+dX2UKGgGaAloD0MILskBu5q85L+UhpRSlGgVSzJoFkdAqENlcSoOx3V9lChoBmgJaA9DCBeBsb6BydS/lIaUUpRoFUsyaBZHQKhDJms/6ft1fZQoaAZoCWgPQwhQVaGBWDbsv5SGlFKUaBVLMmgWR0CoQuZ7ojfOdX2UKGgGaAloD0MI8s6hDFXx8L+UhpRSlGgVSzJoFkdAqEUTurp7kXV9lChoBmgJaA9DCBPVWwNbJem/lIaUUpRoFUsyaBZHQKhE2a0hNdt1fZQoaAZoCWgPQwh7aB8r+G3uv5SGlFKUaBVLMmgWR0CoRJuby6MBdX2UKGgGaAloD0MIR8oWSbvR5b+UhpRSlGgVSzJoFkdAqERcjNY8uHV9lChoBmgJaA9DCHzxRXu8kNi/lIaUUpRoFUsyaBZHQKhG5huO0b91fZQoaAZoCWgPQwiVY7K4/0jsv5SGlFKUaBVLMmgWR0CoRqxrSE13dX2UKGgGaAloD0MIKes3E9MF67+UhpRSlGgVSzJoFkdAqEZuhdt2tHV9lChoBmgJaA9DCMVTjzS4reK/lIaUUpRoFUsyaBZHQKhGL5zo2XN1fZQoaAZoCWgPQwgo8iTpmsnjv5SGlFKUaBVLMmgWR0CoSK3S8an8dX2UKGgGaAloD0MI6NuCpbqA5r+UhpRSlGgVSzJoFkdAqEh0QNCqqHV9lChoBmgJaA9DCLIrLSP1nuG/lIaUUpRoFUsyaBZHQKhINnr6ciJ1fZQoaAZoCWgPQwhhp1g1CHPJv5SGlFKUaBVLMmgWR0CoR/dy1eBydX2UKGgGaAloD0MIo+nsZHAU5b+UhpRSlGgVSzJoFkdAqEp0auOjqXV9lChoBmgJaA9DCCe9b3ztGeK/lIaUUpRoFUsyaBZHQKhKOgVXV9Z1fZQoaAZoCWgPQwhUdCSX/5Dav5SGlFKUaBVLMmgWR0CoSfvaL4vfdX2UKGgGaAloD0MIJ2ppboWw7b+UhpRSlGgVSzJoFkdAqEm9zQu27XV9lChoBmgJaA9DCCAldm1vt+a/lIaUUpRoFUsyaBZHQKhMRUgB91F1fZQoaAZoCWgPQwibyqKwi6Lbv5SGlFKUaBVLMmgWR0CoTAtv4ubrdX2UKGgGaAloD0MIBmhbzTpj47+UhpRSlGgVSzJoFkdAqEvNMfzSTnV9lChoBmgJaA9DCK0XQznRLuK/lIaUUpRoFUsyaBZHQKhLjiF0xM51ZS4="
|
62 |
},
|
63 |
"ep_success_buffer": {
|
64 |
":type:": "<class 'collections.deque'>",
|
65 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
66 |
},
|
67 |
+
"_n_updates": 31250,
|
68 |
+
"n_steps": 8,
|
69 |
"gamma": 0.99,
|
70 |
+
"gae_lambda": 0.9,
|
71 |
"ent_coef": 0.0,
|
72 |
+
"vf_coef": 0.4,
|
73 |
"max_grad_norm": 0.5,
|
74 |
"normalize_advantage": false,
|
75 |
"observation_space": {
|
a2c-PandaReachDense-v2/policy.optimizer.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:834542a8ab822800a5ade8bd9f4d1a7d5a477dff28dd50a86266fa259b4b8721
|
3 |
+
size 45438
|
a2c-PandaReachDense-v2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:196d5fd5bdc5dec862e094d1d2227208da2efa09711bdc19998ee602ee862978
|
3 |
+
size 46718
|
config.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n MultiInputActorClass policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space (Tuple)\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Uses the CombinedExtractor\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7fbf83d293a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fbf83d288c0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681370465067037516, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOS9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/RvAGjbi6x4WUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAxIv2Pi2Glj2udRg/xIv2Pi2Glj2udRg/xIv2Pi2Glj2udRg/xIv2Pi2Glj2udRg/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAExlUv0Jvob6NUGy/AyYLPu4u1z89D5W+ayXvPb4Onj8rSKq/LuLoPtrXtj/NU2G/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADEi/Y+LYaWPa51GD+q1yY8PuuaO9CHUTzEi/Y+LYaWPa51GD+q1yY8PuuaO9CHUTzEi/Y+LYaWPa51GD+q1yY8PuuaO9CHUTzEi/Y+LYaWPa51GD+q1yY8PuuaO9CHUTyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.48153508 0.07349811 0.59554565]\n [0.48153508 0.07349811 0.59554565]\n [0.48153508 0.07349811 0.59554565]\n [0.48153508 0.07349811 0.59554565]]", "desired_goal": "[[-0.8285076 -0.31530195 -0.9231041 ]\n [ 0.13588719 1.6811197 -0.29113188]\n [ 0.11677059 1.2348249 -1.3303274 ]\n [ 0.4548506 1.4284623 -0.88018495]]", "observation": "[[0.48153508 0.07349811 0.59554565 0.01018325 0.00472775 0.01278873]\n [0.48153508 0.07349811 0.59554565 0.01018325 0.00472775 0.01278873]\n [0.48153508 0.07349811 0.59554565 0.01018325 0.00472775 0.01278873]\n [0.48153508 0.07349811 0.59554565 0.01018325 0.00472775 0.01278873]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]", "desired_goal": "[[ 0.02440785 0.02473501 0.22989823]\n [ 0.03611701 -0.05878683 0.20246772]\n [ 0.05609988 0.04433204 0.22607633]\n [ 0.03941405 -0.06546137 0.12838516]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 50000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
|
|
1 |
+
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n MultiInputActorClass policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space (Tuple)\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Uses the CombinedExtractor\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7fbf83d293a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fbf83d288c0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681375142849072290, "learning_rate": 0.00096, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.43085906 -0.00301856 0.59868556]\n [ 0.43085906 -0.00301856 0.59868556]\n [ 0.43085906 -0.00301856 0.59868556]\n [ 0.43085906 -0.00301856 0.59868556]]", "desired_goal": "[[ 0.10309792 1.5590055 -0.5663382 ]\n [ 0.9556199 0.14618732 1.3841752 ]\n [ 1.282797 0.7711009 0.4337387 ]\n [-1.1935312 0.33299118 1.60713 ]]", "observation": "[[ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]\n [ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]\n [ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]\n [ 4.30859059e-01 -3.01855640e-03 5.98685563e-01 7.83352181e-02\n 1.20980745e-04 6.79290816e-02]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]", "desired_goal": "[[ 0.01209264 0.08778638 0.2352361 ]\n [-0.11432365 0.08557644 0.2670476 ]\n [ 0.015327 0.08269451 0.28230497]\n [ 0.08827544 0.1304073 0.12207159]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 31250, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward": -
|
|
|
1 |
+
{"mean_reward": -0.6058791131945327, "std_reward": 0.19567170625488417, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-13T09:30:56.150055"}
|
vec_normalize.pkl
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 2381
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c1d483d878175edbb3b4ae06c4e1d54ab2accb3ef2182b6fb1487ddeddcd7c8b
|
3 |
size 2381
|