IlluminatiPudding
commited on
Commit
•
1720ff0
1
Parent(s):
0d0e782
Initial commit
Browse files- README.md +37 -0
- a2c-PandaPickAndPlaceDense-v3.zip +3 -0
- a2c-PandaPickAndPlaceDense-v3/_stable_baselines3_version +1 -0
- a2c-PandaPickAndPlaceDense-v3/data +101 -0
- a2c-PandaPickAndPlaceDense-v3/policy.optimizer.pth +3 -0
- a2c-PandaPickAndPlaceDense-v3/policy.pth +3 -0
- a2c-PandaPickAndPlaceDense-v3/pytorch_variables.pth +3 -0
- a2c-PandaPickAndPlaceDense-v3/system_info.txt +9 -0
- config.json +1 -0
- replay.mp4 +0 -0
- results.json +1 -0
- vec_normalize.pkl +3 -0
README.md
ADDED
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- PandaPickAndPlaceDense-v3
|
5 |
+
- deep-reinforcement-learning
|
6 |
+
- reinforcement-learning
|
7 |
+
- stable-baselines3
|
8 |
+
model-index:
|
9 |
+
- name: A2C
|
10 |
+
results:
|
11 |
+
- task:
|
12 |
+
type: reinforcement-learning
|
13 |
+
name: reinforcement-learning
|
14 |
+
dataset:
|
15 |
+
name: PandaPickAndPlaceDense-v3
|
16 |
+
type: PandaPickAndPlaceDense-v3
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: -50.00 +/- 0.00
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **A2C** Agent playing **PandaPickAndPlaceDense-v3**
|
25 |
+
This is a trained model of a **A2C** agent playing **PandaPickAndPlaceDense-v3**
|
26 |
+
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
27 |
+
|
28 |
+
## Usage (with Stable-baselines3)
|
29 |
+
TODO: Add your code
|
30 |
+
|
31 |
+
|
32 |
+
```python
|
33 |
+
from stable_baselines3 import ...
|
34 |
+
from huggingface_sb3 import load_from_hub
|
35 |
+
|
36 |
+
...
|
37 |
+
```
|
a2c-PandaPickAndPlaceDense-v3.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8841761a6bc3e987c1f84be5288a28167342c2be108d35842972562bc2d0a034
|
3 |
+
size 4464531
|
a2c-PandaPickAndPlaceDense-v3/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.1.0
|
a2c-PandaPickAndPlaceDense-v3/data
ADDED
@@ -0,0 +1,101 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"policy_class": {
|
3 |
+
":type:": "<class 'abc.ABCMeta'>",
|
4 |
+
":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
|
5 |
+
"__module__": "stable_baselines3.common.policies",
|
6 |
+
"__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 ",
|
7 |
+
"__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7cad8f027b50>",
|
8 |
+
"__abstractmethods__": "frozenset()",
|
9 |
+
"_abc_impl": "<_abc._abc_data object at 0x7cad8ee2db40>"
|
10 |
+
},
|
11 |
+
"verbose": 1,
|
12 |
+
"policy_kwargs": {
|
13 |
+
":type:": "<class 'dict'>",
|
14 |
+
":serialized:": "gAWVlgAAAAAAAAB9lCiMCG5ldF9hcmNolF2UKE0AAk0AAmWMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
|
15 |
+
"net_arch": [
|
16 |
+
512,
|
17 |
+
512
|
18 |
+
],
|
19 |
+
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
20 |
+
"optimizer_kwargs": {
|
21 |
+
"alpha": 0.99,
|
22 |
+
"eps": 1e-05,
|
23 |
+
"weight_decay": 0
|
24 |
+
}
|
25 |
+
},
|
26 |
+
"num_timesteps": 100000,
|
27 |
+
"_total_timesteps": 100000.0,
|
28 |
+
"_num_timesteps_at_start": 0,
|
29 |
+
"seed": null,
|
30 |
+
"action_noise": null,
|
31 |
+
"start_time": 1700044951324505047,
|
32 |
+
"learning_rate": 0.1,
|
33 |
+
"tensorboard_log": null,
|
34 |
+
"_last_obs": {
|
35 |
+
":type:": "<class 'collections.OrderedDict'>",
|
36 |
+
":serialized:": "gAWViwIAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAJpoUv/j2FT8B+1U9KpSqvmiIUb8B+1U9pQBFP0887L4B+1U9K/+0P/yxij8y9lU9lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAASvnUPjOdPr/2Jo6/9GWKv7Vbjb/2Jo6/5Gxcvt1VG72D0xk/WE57vgq+jD/2Jo6/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWMAEAAAAAAABOKgY/nJm2P31tZb92bjO+JjdYvRYTML/T6ly/JpoUv/j2FT8B+1U95Sm8vL2g+7xrLrq7+yXYPMssyDyPBqU847OLvMi7LrxInlK7Q3n7PsSGlL+nUWC+AGsEP7yzMr4p6p8/DOtcvyqUqr5oiFG/AftVPZuqvrzloP28q0/3ux6W5TyGQro8jQalPN+JFryLd1e7ahVquyFKxL/YP/2+Z1sIvha0KMC4lOw/KnkAPqyymT+lAEU/TzzsvgH7VT3kKby8vaD7vLeGsbvZJdg8syzIPI0GpTx/s4u8Eb0uvNOcUrsHO8i/T2r/P0mzDbmp4Wq/CR2Qvel/Bb+Sspk/K/+0P/yxij8y9lU9YZ6/vJPt+rwaQpq7f1PhPLlyxDzHMak8OZFIvFKf/7sP3i27lGgOSwRLE4aUaBJ0lFKUdS4=",
|
37 |
+
"achieved_goal": "[[-0.5804771 0.5857997 0.05224133]\n [-0.33316165 -0.81848764 0.05224133]\n [ 0.7695411 -0.46139762 0.05224133]\n [ 1.4140371 1.0835567 0.05223674]]",
|
38 |
+
"desired_goal": "[[ 0.41596442 -0.74458617 -1.110564 ]\n [-1.0812364 -1.1043612 -1.110564 ]\n [-0.21525913 -0.03792368 0.60088366]\n [-0.24541605 1.0995495 -1.110564 ]]",
|
39 |
+
"observation": "[[ 5.2408302e-01 1.4265628e+00 -8.9620191e-01 -1.7522606e-01\n -5.2786969e-02 -6.8779123e-01 -8.6295813e-01 -5.8047712e-01\n 5.8579969e-01 5.2241329e-02 -2.2969196e-02 -3.0716294e-02\n -5.6818030e-03 2.6385298e-02 2.4435421e-02 2.0144729e-02\n -1.7053550e-02 -1.0664888e-02 -3.2137800e-03]\n [ 4.9115953e-01 -1.1603627e+00 -2.1906148e-01 5.1725769e-01\n -1.7451376e-01 1.2493335e+00 -8.6296153e-01 -3.3316165e-01\n -8.1848764e-01 5.2241329e-02 -2.3274710e-02 -3.0960510e-02\n -7.5473390e-03 2.8025683e-02 2.2736799e-02 2.0144725e-02\n -9.1881445e-03 -3.2877650e-03 -3.5718330e-03]\n [-1.5335122e+00 -4.9462771e-01 -1.3316117e-01 -2.6359916e+00\n 1.8482885e+00 1.2546220e-01 1.2007651e+00 7.6954108e-01\n -4.6139762e-01 5.2241329e-02 -2.2969194e-02 -3.0716294e-02\n -5.4176706e-03 2.6385235e-02 2.4435377e-02 2.0144725e-02\n -1.7053364e-02 -1.0665194e-02 -3.2136932e-03]\n [-1.5643014e+00 1.9954318e+00 -1.3513597e-04 -9.1750580e-01\n -7.0367880e-02 -5.2148300e-01 1.2007620e+00 1.4140371e+00\n 1.0835567e+00 5.2236743e-02 -2.3390951e-02 -3.0630862e-02\n -4.7075870e-03 2.7505634e-02 2.3980485e-02 2.0653618e-02\n -1.2241655e-02 -7.8009749e-03 -2.6530062e-03]]"
|
40 |
+
},
|
41 |
+
"_last_episode_starts": {
|
42 |
+
":type:": "<class 'numpy.ndarray'>",
|
43 |
+
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
|
44 |
+
},
|
45 |
+
"_last_original_obs": {
|
46 |
+
":type:": "<class 'collections.OrderedDict'>",
|
47 |
+
":serialized:": "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",
|
48 |
+
"achieved_goal": "[[-0.05171139 -0.12660232 0.02 ]\n [-0.09215479 0.02575223 0.02 ]\n [-0.1234035 -0.06684168 0.02 ]\n [ 0.07460041 0.00335589 0.02 ]]",
|
49 |
+
"desired_goal": "[[ 0.04525072 -0.05884082 0.11584055]\n [ 0.12405972 0.0985745 0.12789455]\n [-0.07377146 0.0262122 0.02 ]\n [ 0.07113237 0.01473783 0.18356384]]",
|
50 |
+
"observation": "[[ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -5.17113917e-02\n -1.26602322e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -9.21547860e-02\n 2.57522333e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -1.23403504e-01\n -6.68416768e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 7.46004060e-02\n 3.35589424e-03 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]]"
|
51 |
+
},
|
52 |
+
"_episode_num": 0,
|
53 |
+
"use_sde": false,
|
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:": "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"
|
60 |
+
},
|
61 |
+
"ep_success_buffer": {
|
62 |
+
":type:": "<class 'collections.deque'>",
|
63 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
64 |
+
},
|
65 |
+
"_n_updates": 1250,
|
66 |
+
"n_steps": 20,
|
67 |
+
"gamma": 0.999,
|
68 |
+
"gae_lambda": 0.99,
|
69 |
+
"ent_coef": 0.0001,
|
70 |
+
"vf_coef": 0.5,
|
71 |
+
"max_grad_norm": 0.5,
|
72 |
+
"normalize_advantage": true,
|
73 |
+
"observation_space": {
|
74 |
+
":type:": "<class 'gymnasium.spaces.dict.Dict'>",
|
75 |
+
":serialized:": "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",
|
76 |
+
"spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (19,), float32))])",
|
77 |
+
"_shape": null,
|
78 |
+
"dtype": null,
|
79 |
+
"_np_random": null
|
80 |
+
},
|
81 |
+
"action_space": {
|
82 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
83 |
+
":serialized:": "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",
|
84 |
+
"dtype": "float32",
|
85 |
+
"bounded_below": "[ True True True True]",
|
86 |
+
"bounded_above": "[ True True True True]",
|
87 |
+
"_shape": [
|
88 |
+
4
|
89 |
+
],
|
90 |
+
"low": "[-1. -1. -1. -1.]",
|
91 |
+
"high": "[1. 1. 1. 1.]",
|
92 |
+
"low_repr": "-1.0",
|
93 |
+
"high_repr": "1.0",
|
94 |
+
"_np_random": null
|
95 |
+
},
|
96 |
+
"n_envs": 4,
|
97 |
+
"lr_schedule": {
|
98 |
+
":type:": "<class 'function'>",
|
99 |
+
":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuDQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz+5mZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
100 |
+
}
|
101 |
+
}
|
a2c-PandaPickAndPlaceDense-v3/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:71e7cc21746cb3cad30fe9135f03418e156564988abfe59ff9e11b44475a021a
|
3 |
+
size 2222063
|
a2c-PandaPickAndPlaceDense-v3/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:415deac41f71dec10abb67782c6d8f0fd19bffc624fb73b716007485bb5a7aaa
|
3 |
+
size 2223343
|
a2c-PandaPickAndPlaceDense-v3/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
3 |
+
size 864
|
a2c-PandaPickAndPlaceDense-v3/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.1.0
|
4 |
+
- PyTorch: 2.1.0+cu118
|
5 |
+
- GPU Enabled: False
|
6 |
+
- Numpy: 1.23.5
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.29.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
config.json
ADDED
@@ -0,0 +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 0x7cad8f027b50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cad8ee2db40>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVlgAAAAAAAAB9lCiMCG5ldF9hcmNolF2UKE0AAk0AAmWMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "net_arch": [512, 512], "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 100000, "_total_timesteps": 100000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700044951324505047, "learning_rate": 0.1, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWViwIAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAJpoUv/j2FT8B+1U9KpSqvmiIUb8B+1U9pQBFP0887L4B+1U9K/+0P/yxij8y9lU9lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAASvnUPjOdPr/2Jo6/9GWKv7Vbjb/2Jo6/5Gxcvt1VG72D0xk/WE57vgq+jD/2Jo6/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWMAEAAAAAAABOKgY/nJm2P31tZb92bjO+JjdYvRYTML/T6ly/JpoUv/j2FT8B+1U95Sm8vL2g+7xrLrq7+yXYPMssyDyPBqU847OLvMi7LrxInlK7Q3n7PsSGlL+nUWC+AGsEP7yzMr4p6p8/DOtcvyqUqr5oiFG/AftVPZuqvrzloP28q0/3ux6W5TyGQro8jQalPN+JFryLd1e7ahVquyFKxL/YP/2+Z1sIvha0KMC4lOw/KnkAPqyymT+lAEU/TzzsvgH7VT3kKby8vaD7vLeGsbvZJdg8syzIPI0GpTx/s4u8Eb0uvNOcUrsHO8i/T2r/P0mzDbmp4Wq/CR2Qvel/Bb+Sspk/K/+0P/yxij8y9lU9YZ6/vJPt+rwaQpq7f1PhPLlyxDzHMak8OZFIvFKf/7sP3i27lGgOSwRLE4aUaBJ0lFKUdS4=", "achieved_goal": "[[-0.5804771 0.5857997 0.05224133]\n [-0.33316165 -0.81848764 0.05224133]\n [ 0.7695411 -0.46139762 0.05224133]\n [ 1.4140371 1.0835567 0.05223674]]", "desired_goal": "[[ 0.41596442 -0.74458617 -1.110564 ]\n [-1.0812364 -1.1043612 -1.110564 ]\n [-0.21525913 -0.03792368 0.60088366]\n [-0.24541605 1.0995495 -1.110564 ]]", "observation": "[[ 5.2408302e-01 1.4265628e+00 -8.9620191e-01 -1.7522606e-01\n -5.2786969e-02 -6.8779123e-01 -8.6295813e-01 -5.8047712e-01\n 5.8579969e-01 5.2241329e-02 -2.2969196e-02 -3.0716294e-02\n -5.6818030e-03 2.6385298e-02 2.4435421e-02 2.0144729e-02\n -1.7053550e-02 -1.0664888e-02 -3.2137800e-03]\n [ 4.9115953e-01 -1.1603627e+00 -2.1906148e-01 5.1725769e-01\n -1.7451376e-01 1.2493335e+00 -8.6296153e-01 -3.3316165e-01\n -8.1848764e-01 5.2241329e-02 -2.3274710e-02 -3.0960510e-02\n -7.5473390e-03 2.8025683e-02 2.2736799e-02 2.0144725e-02\n -9.1881445e-03 -3.2877650e-03 -3.5718330e-03]\n [-1.5335122e+00 -4.9462771e-01 -1.3316117e-01 -2.6359916e+00\n 1.8482885e+00 1.2546220e-01 1.2007651e+00 7.6954108e-01\n -4.6139762e-01 5.2241329e-02 -2.2969194e-02 -3.0716294e-02\n -5.4176706e-03 2.6385235e-02 2.4435377e-02 2.0144725e-02\n -1.7053364e-02 -1.0665194e-02 -3.2136932e-03]\n [-1.5643014e+00 1.9954318e+00 -1.3513597e-04 -9.1750580e-01\n -7.0367880e-02 -5.2148300e-01 1.2007620e+00 1.4140371e+00\n 1.0835567e+00 5.2236743e-02 -2.3390951e-02 -3.0630862e-02\n -4.7075870e-03 2.7505634e-02 2.3980485e-02 2.0653618e-02\n -1.2241655e-02 -7.8009749e-03 -2.6530062e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.05171139 -0.12660232 0.02 ]\n [-0.09215479 0.02575223 0.02 ]\n [-0.1234035 -0.06684168 0.02 ]\n [ 0.07460041 0.00335589 0.02 ]]", "desired_goal": "[[ 0.04525072 -0.05884082 0.11584055]\n [ 0.12405972 0.0985745 0.12789455]\n [-0.07377146 0.0262122 0.02 ]\n [ 0.07113237 0.01473783 0.18356384]]", "observation": "[[ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -5.17113917e-02\n -1.26602322e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -9.21547860e-02\n 2.57522333e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -1.23403504e-01\n -6.68416768e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 7.46004060e-02\n 3.35589424e-03 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+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:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwCFnHxSYPXmMAWyUSzKMAXSUR0B25e2BreqJdX2UKGgGR8AsQKCxu89PaAdLMmgIR0B26LaxoqTbdX2UKGgGR8AGsaAFxGUfaAdLMmgIR0B27OA+Y+jedX2UKGgGR8APTIikfs/qaAdLMmgIR0B25h3dKujidX2UKGgGR8AaoGqxTsIFaAdLMmgIR0B28IGjbi6ydX2UKGgGR8AhqZxaPjn3aAdLMmgIR0B280vSMLncdX2UKGgGR8AW01cdHUc5aAdLMmgIR0B290Xj2i+MdX2UKGgGR8AqWD+zdDYzaAdLMmgIR0B28NbA1vVFdX2UKGgGR8ArDqUNayKOaAdLMmgIR0B2+4is4ku6dX2UKGgGR8AkdcAR02cbaAdLMmgIR0B2/lkFwDNhdX2UKGgGR8Am32/zreImaAdLMmgIR0B3Ao+B6KLsdX2UKGgGR8Aaq77Kq4pdaAdLMmgIR0B2+9eY2Kl6dX2UKGgGR8AYCJ+DvmYCaAdLMmgIR0B3Br2i+L3sdX2UKGgGR8Al7jS5RTCMaAdLMmgIR0B3CYht+CsfdX2UKGgGR8AhcnTAnDziaAdLMmgIR0B3DYyylenidX2UKGgGR8AboL/jsD4haAdLMmgIR0B3BsAlv60qdX2UKGgGR8AFRiPQv6CUaAdLMmgIR0B3EUhwEQoTdX2UKGgGR8AvXWvKU3XJaAdLMmgIR0B3FBVyWAwxdX2UKGgGR8AjuZmZmZmaaAdLMmgIR0B3GIQZn+Q2dX2UKGgGR8AjAm6XjU/faAdLMmgIR0B3EfwVj7Q+dX2UKGgGR8AoTSUkfLcLaAdLMmgIR0B3HIiKR+z/dX2UKGgGR8Ajosny/bj+aAdLMmgIR0B3H1X8wYcedX2UKGgGR8AiF61LJ0W/aAdLMmgIR0B3I0LQXyiFdX2UKGgGR8AtM1kUbkwOaAdLMmgIR0B3HIeLehwmdX2UKGgGR8AqeotL+PzWaAdLMmgIR0B3JxkUbkwOdX2UKGgGR8AqsVFhG6PKaAdLMmgIR0B3Ke/BWPtEdX2UKGgGR8AJGy7f51vEaAdLMmgIR0B3Lgz41xbTdX2UKGgGR8ApU9DhLoOhaAdLMmgIR0B3J0yZa3ZxdX2UKGgGR8AmsV8CxNZeaAdLMmgIR0B3MeJYT0xudX2UKGgGR8AjeRdQfp2VaAdLMmgIR0B3NLDAJswddX2UKGgGR8AmTCSidrftaAdLMmgIR0B3OLklu3tsdX2UKGgGR7+kDQqqfe1saAdLAWgIR0B3OPMyJsO5dX2UKGgGR8AklgWJrLyMaAdLMmgIR0B3MgAaNuLrdX2UKGgGR8Ao2rELpiZwaAdLMmgIR0B3PtsVLzwudX2UKGgGR8AoFijL0SRKaAdLMmgIR0B3Qbk5p8F7dX2UKGgGR8AZE2tMfzSUaAdLMmgIR0B3RwpiI+GHdX2UKGgGR8AUPbVSXMQmaAdLMmgIR0B3QGsdT5wgdX2UKGgGR8Ah5KSPluFYaAdLMmgIR0B3UPHWBjFydX2UKGgGR8AXYGxD9fkWaAdLMmgIR0B3U9wm3OObdX2UKGgGR8AavOfNA1NyaAdLMmgIR0B3WQMEzO5bdX2UKGgGR8AO6U3XI2fkaAdLMmgIR0B3UpyimEXddX2UKGgGR8AobrrPdEb6aAdLMmgIR0B3YtOh0yP/dX2UKGgGR8AZZayKNyYHaAdLMmgIR0B3Zbt5UtI1dX2UKGgGR7+ZP2wmmce9aAdLAWgIR0B3YzAM2FWXdX2UKGgGR8AhvVawD/2kaAdLMmgIR0B3axS9/SYxdX2UKGgGR8Agg9mHxjJ/aAdLMmgIR0B3ZIV8CxNZdX2UKGgGR8AJyxgRbr1NaAdLMmgIR0B3dViUgSvldX2UKGgGR8Awj6reZXuFaAdLMmgIR0B3cs8ifQKKdX2UKGgGR8AlwwaisXBQaAdLMmgIR0B3emyX2M86dX2UKGgGR8AhHeqJdjXnaAdLMmgIR0B3c/kHUtqYdX2UKGgGR8AwAOUt7KJVaAdLMmgIR0B3hefapPykdX2UKGgGR8AVHeLvTgEVaAdLMmgIR0B3g2JoCdSVdX2UKGgGR8AehVo6CDmKaAdLMmgIR0B3i5BIFvAHdX2UKGgGR8Ad4FC9h7VsaAdLMmgIR0B3hTiOvMbFdX2UKGgGR8AhwJfpljEvaAdLMmgIR0B3lAD0UXYUdX2UKGgGR8Ap0HN5dGAkaAdLMmgIR0B3kXKji4rjdX2UKGgGR8AjddPci4axaAdLMmgIR0B3mCXw9aEBdX2UKGgGR8Ag1BbfP5YYaAdLMmgIR0B3kT2/SH/MdX2UKGgGR8AtZOQhfShKaAdLMmgIR0B3nrw+dK/VdX2UKGgGR8Adn4YaYNRWaAdLMmgIR0B3nDD3ueBhdX2UKGgGR8AhcwHJLdvbaAdLMmgIR0B3oxEG7jDLdX2UKGgGR8AYu2jO9nK5aAdLMmgIR0B3nBsguAZsdX2UKGgGR7+amTC+De0paAdLAWgIR0B3nE0Ltu1ndX2UKGgGR8AsZBX0XgtOaAdLMmgIR0B3qUL9deIEdX2UKGgGR8AixWlMyrPuaAdLMmgIR0B3prMmnfl7dX2UKGgGR8AlNPDYRNAUaAdLMmgIR0B3rXLZBcAzdX2UKGgGR8AgtN3W4EwGaAdLMmgIR0B3pqn+AEt/dX2UKGgGR8AjwB9Tgl4UaAdLMmgIR0B3s7XqZ+hHdX2UKGgGR8AnoOn2qT8paAdLMmgIR0B3sSNsFdLQdX2UKGgGR8AclS0jTrmhaAdLMmgIR0B3uDh3qzJIdX2UKGgGR8Aiz9kz41xbaAdLMmgIR0B3sXsAvL5idX2UKGgGR8Ahni3G4qgAaAdLMmgIR0B3vjKV6eGxdX2UKGgGR8AjJCrtE5QxaAdLMmgIR0B3u6MFUyYYdX2UKGgGR8AXMdELH+6zaAdLMmgIR0B3wleHBUJfdX2UKGgGR8Ar4gQpWmxdaAdLMmgIR0B3u6A9V3lkdX2UKGgGR8ALBhjOLR8daAdLMmgIR0B3yJb7j1f3dX2UKGgGR8AbN59mYjSoaAdLMmgIR0B3xgdU83dcdX2UKGgGR8Atk8/2TPjXaAdLMmgIR0B3zO9OARTTdX2UKGgGR8AiYtwJgLJCaAdLMmgIR0B3xi3lS0jUdX2UKGgGR8AjafGMn7YTaAdLMmgIR0B30ukwevIPdX2UKGgGR8Al9FOO801qaAdLMmgIR0B30FgSeyzHdX2UKGgGR8AqV7fpD/lyaAdLMmgIR0B31xzKcNH6dX2UKGgGR8AO4qwyIpH7aAdLMmgIR0B30JtXPqs2dX2UKGgGR8AmXSc9W6siaAdLMmgIR0B33ngm7aqTdX2UKGgGR8AZEow22oegaAdLMmgIR0B32+kCV8kVdX2UKGgGR8AwMn+yZ8a5aAdLMmgIR0B34uqCHymRdX2UKGgGR8Ajv6nivPkaaAdLMmgIR0B33EGlhw2mdX2UKGgGR8AnvMUypJf6aAdLMmgIR0B36Mfms/6gdX2UKGgGR8AhFi6xxDLKaAdLMmgIR0B35jaRISUUdX2UKGgGR8Ah4s4ku6EraAdLMmgIR0B37PPKMefadX2UKGgGR8AxUv7FbVz7aAdLMmgIR0B35jaZhKDkdX2UKGgGR8APO9vjwQUYaAdLMmgIR0B3875GjKxLdX2UKGgGR8Ai98UEgW8AaAdLMmgIR0B38S8vmHQAdX2UKGgGR7+ne+Eh7mdRaAdLAWgIR0B38/eGfwqidX2UKGgGR8AJOPYFqzqsaAdLMmgIR0B3+BMHryDqdX2UKGgGR8AjPI5HVf/naAdLMmgIR0B38W5c1O0tdX2UKGgGR8Aq82MsH0K7aAdLMmgIR0B3/EVrRBu5dX2UKGgGR8AiUvSMLncMaAdLMmgIR0B3/xCrtE5RdX2UKGgGR8AbG3iJfpljaAdLMmgIR0B4AxuhsZYQdX2UKGgGR8AhHxIatLcsaAdLMmgIR0B3/GOxSpBHdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1250, "n_steps": 20, "gamma": 0.999, "gae_lambda": 0.99, "ent_coef": 0.0001, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": true, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (19,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.0+cu118", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
|
replay.mp4
ADDED
Binary file (741 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -50.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-15T10:50:18.231164"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d909638834b52740ef09ed2d3484b7d09cf9d9ad559eef52b407dcb8780397fb
|
3 |
+
size 3013
|