sergey-antonov
commited on
Commit
•
13a7d34
1
Parent(s):
261c09e
Initial commit
Browse files- README.md +37 -0
- a2c-PandaReachDense-v2.zip +3 -0
- a2c-PandaReachDense-v2/_stable_baselines3_version +1 -0
- a2c-PandaReachDense-v2/data +96 -0
- a2c-PandaReachDense-v2/policy.optimizer.pth +3 -0
- a2c-PandaReachDense-v2/policy.pth +3 -0
- a2c-PandaReachDense-v2/pytorch_variables.pth +3 -0
- a2c-PandaReachDense-v2/system_info.txt +7 -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 |
+
- PandaReachDense-v2
|
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: PandaReachDense-v2
|
16 |
+
type: PandaReachDense-v2
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: -2.58 +/- 0.47
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **A2C** Agent playing **PandaReachDense-v2**
|
25 |
+
This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
|
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-PandaReachDense-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c43a3de316b695ac283854060ee6c7682a4b562ec9ea737b2c80184811714b0e
|
3 |
+
size 107887
|
a2c-PandaReachDense-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
a2c-PandaReachDense-v2/data
ADDED
@@ -0,0 +1,96 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 feature extractor.\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 0x7fa1357b9ea0>",
|
8 |
+
"__abstractmethods__": "frozenset()",
|
9 |
+
"_abc_impl": "<_abc._abc_data object at 0x7fa1357c5380>"
|
10 |
+
},
|
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,
|
20 |
+
"eps": 1e-05,
|
21 |
+
"weight_decay": 0
|
22 |
+
}
|
23 |
+
},
|
24 |
+
"observation_space": {
|
25 |
+
":type:": "<class 'gym.spaces.dict.Dict'>",
|
26 |
+
":serialized:": "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",
|
27 |
+
"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))])",
|
28 |
+
"_shape": null,
|
29 |
+
"dtype": null,
|
30 |
+
"_np_random": null
|
31 |
+
},
|
32 |
+
"action_space": {
|
33 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
34 |
+
":serialized:": "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",
|
35 |
+
"dtype": "float32",
|
36 |
+
"_shape": [
|
37 |
+
3
|
38 |
+
],
|
39 |
+
"low": "[-1. -1. -1.]",
|
40 |
+
"high": "[1. 1. 1.]",
|
41 |
+
"bounded_below": "[ True True True]",
|
42 |
+
"bounded_above": "[ True True True]",
|
43 |
+
"_np_random": null
|
44 |
+
},
|
45 |
+
"n_envs": 4,
|
46 |
+
"num_timesteps": 2000016,
|
47 |
+
"_total_timesteps": 2000000,
|
48 |
+
"_num_timesteps_at_start": 0,
|
49 |
+
"seed": null,
|
50 |
+
"action_noise": null,
|
51 |
+
"start_time": 1676579004832655284,
|
52 |
+
"learning_rate": 0.0007,
|
53 |
+
"tensorboard_log": null,
|
54 |
+
"lr_schedule": {
|
55 |
+
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
+
},
|
58 |
+
"_last_obs": {
|
59 |
+
":type:": "<class 'collections.OrderedDict'>",
|
60 |
+
":serialized:": "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",
|
61 |
+
"achieved_goal": "[[ 3.5721701e-01 -9.4452161e-01 3.1746249e-04]\n [ 1.0397720e+00 2.4752641e-01 1.6357917e+00]\n [ 1.0494003e+00 4.9461949e-01 1.5147951e+00]\n [ 1.0193063e+00 9.6164584e-01 1.6307747e+00]]",
|
62 |
+
"desired_goal": "[[-0.21547584 -1.1523788 0.21627152]\n [ 1.1539892 -1.6509827 1.0018264 ]\n [ 1.5558372 -0.78771174 0.558961 ]\n [ 1.5596424 -0.48727983 0.96007216]]",
|
63 |
+
"observation": "[[ 3.5721701e-01 -9.4452161e-01 3.1746249e-04 -2.5266710e-01\n -1.5128351e+00 -1.2365237e-01]\n [ 1.0397720e+00 2.4752641e-01 1.6357917e+00 4.8863047e-01\n -6.3185102e-01 1.6667178e+00]\n [ 1.0494003e+00 4.9461949e-01 1.5147951e+00 4.9766937e-01\n -2.0054945e-01 1.3643125e+00]\n [ 1.0193063e+00 9.6164584e-01 1.6307747e+00 4.6394283e-01\n 3.8613815e-02 1.6415871e+00]]"
|
64 |
+
},
|
65 |
+
"_last_episode_starts": {
|
66 |
+
":type:": "<class 'numpy.ndarray'>",
|
67 |
+
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
|
68 |
+
},
|
69 |
+
"_last_original_obs": {
|
70 |
+
":type:": "<class 'collections.OrderedDict'>",
|
71 |
+
":serialized:": "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",
|
72 |
+
"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]]",
|
73 |
+
"desired_goal": "[[-0.02938484 -0.0331512 0.2714201 ]\n [-0.0220243 -0.13172671 0.13055326]\n [ 0.1316682 -0.09655855 0.05594268]\n [-0.14368819 0.06097815 0.15502983]]",
|
74 |
+
"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]]"
|
75 |
+
},
|
76 |
+
"_episode_num": 0,
|
77 |
+
"use_sde": false,
|
78 |
+
"sde_sample_freq": -1,
|
79 |
+
"_current_progress_remaining": -8.000000000008e-06,
|
80 |
+
"ep_info_buffer": {
|
81 |
+
":type:": "<class 'collections.deque'>",
|
82 |
+
":serialized:": "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"
|
83 |
+
},
|
84 |
+
"ep_success_buffer": {
|
85 |
+
":type:": "<class 'collections.deque'>",
|
86 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
87 |
+
},
|
88 |
+
"_n_updates": 83334,
|
89 |
+
"n_steps": 6,
|
90 |
+
"gamma": 0.99,
|
91 |
+
"gae_lambda": 0.95,
|
92 |
+
"ent_coef": 0.0,
|
93 |
+
"vf_coef": 0.5,
|
94 |
+
"max_grad_norm": 0.5,
|
95 |
+
"normalize_advantage": false
|
96 |
+
}
|
a2c-PandaReachDense-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:55e75bb664279a54d71ea0c199780ba5768c03be86c90aaedbd8c4d78339bbe8
|
3 |
+
size 44734
|
a2c-PandaReachDense-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:52971d4e574e49bd2b286f4a701b46ad912d6fed03dcfe7ca56e3ca31cd0c8b5
|
3 |
+
size 45502
|
a2c-PandaReachDense-v2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
a2c-PandaReachDense-v2/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
OS: Linux-6.1.0-3-amd64-x86_64-with-glibc2.36 #1 SMP PREEMPT_DYNAMIC Debian 6.1.8-1 (2023-01-29)
|
2 |
+
Python: 3.10.8
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.23.4
|
7 |
+
Gym: 0.21.0
|
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 feature extractor.\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 0x7fa1357b9ea0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fa1357c5380>"}, "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}}, "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, "num_timesteps": 2000016, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676579004832655284, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAJuW2PivMcb8YcaY5QBeFP5B3fT6fYdE/wFKGP8Q+/T7O5ME/oXiCP2wudj86vdA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAs6VcviaBk79Idl0+67WTP2dT07/ZO4A/rCXHP3qnSb8RGA8/XaLHP758+b5Kx3U/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAAAm5bY+K8xxvxhxpjmVXYG+laTBv3Q9/b1AF4U/kHd9Pp9h0T/GLfo+/cAhvwJX1T/AUoY/xD79Ps7kwT+Fzv4+1lxNvsuhrj+heII/bC52Pzq90D/qie0+hSkePYcf0j+UaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[ 3.5721701e-01 -9.4452161e-01 3.1746249e-04]\n [ 1.0397720e+00 2.4752641e-01 1.6357917e+00]\n [ 1.0494003e+00 4.9461949e-01 1.5147951e+00]\n [ 1.0193063e+00 9.6164584e-01 1.6307747e+00]]", "desired_goal": "[[-0.21547584 -1.1523788 0.21627152]\n [ 1.1539892 -1.6509827 1.0018264 ]\n [ 1.5558372 -0.78771174 0.558961 ]\n [ 1.5596424 -0.48727983 0.96007216]]", "observation": "[[ 3.5721701e-01 -9.4452161e-01 3.1746249e-04 -2.5266710e-01\n -1.5128351e+00 -1.2365237e-01]\n [ 1.0397720e+00 2.4752641e-01 1.6357917e+00 4.8863047e-01\n -6.3185102e-01 1.6667178e+00]\n [ 1.0494003e+00 4.9461949e-01 1.5147951e+00 4.9766937e-01\n -2.0054945e-01 1.3643125e+00]\n [ 1.0193063e+00 9.6164584e-01 1.6307747e+00 4.6394283e-01\n 3.8613815e-02 1.6415871e+00]]"}, "_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": "[[ 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": "[[-0.02938484 -0.0331512 0.2714201 ]\n [-0.0220243 -0.13172671 0.13055326]\n [ 0.1316682 -0.09655855 0.05594268]\n [-0.14368819 0.06097815 0.15502983]]", "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": -8.000000000008e-06, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 83334, "n_steps": 6, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-6.1.0-3-amd64-x86_64-with-glibc2.36 #1 SMP PREEMPT_DYNAMIC Debian 6.1.8-1 (2023-01-29)", "Python": "3.10.8", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0", "GPU Enabled": "True", "Numpy": "1.23.4", "Gym": "0.21.0"}}
|
replay.mp4
ADDED
Binary file (793 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -2.5841076808283105, "std_reward": 0.4661263011944786, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-17T00:32:00.586755"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4625fd97e9c8845e8eddd724f59fcd4d3d40cd3f7301d4b671b64e28f19f49da
|
3 |
+
size 3273
|