Commit
•
4551cb9
1
Parent(s):
5c4f5da
Initial commit
Browse files- README.md +37 -0
- a2c-PandaReachDense-v3.zip +3 -0
- a2c-PandaReachDense-v3/_stable_baselines3_version +1 -0
- a2c-PandaReachDense-v3/data +97 -0
- a2c-PandaReachDense-v3/policy.optimizer.pth +3 -0
- a2c-PandaReachDense-v3/policy.pth +3 -0
- a2c-PandaReachDense-v3/pytorch_variables.pth +3 -0
- a2c-PandaReachDense-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 |
+
- PandaReachDense-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: PandaReachDense-v3
|
16 |
+
type: PandaReachDense-v3
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: -0.20 +/- 0.09
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **A2C** Agent playing **PandaReachDense-v3**
|
25 |
+
This is a trained model of a **A2C** agent playing **PandaReachDense-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-PandaReachDense-v3.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b8b497cebb872a1b3167b752b00560ed571f7adb8ebb3aeb32bde053adab2c26
|
3 |
+
size 106831
|
a2c-PandaReachDense-v3/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.1.0
|
a2c-PandaReachDense-v3/data
ADDED
@@ -0,0 +1,97 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x787fdd019990>",
|
8 |
+
"__abstractmethods__": "frozenset()",
|
9 |
+
"_abc_impl": "<_abc._abc_data object at 0x787fdd01de00>"
|
10 |
+
},
|
11 |
+
"verbose": 1,
|
12 |
+
"policy_kwargs": {
|
13 |
+
":type:": "<class 'dict'>",
|
14 |
+
":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
|
15 |
+
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
16 |
+
"optimizer_kwargs": {
|
17 |
+
"alpha": 0.99,
|
18 |
+
"eps": 1e-05,
|
19 |
+
"weight_decay": 0
|
20 |
+
}
|
21 |
+
},
|
22 |
+
"num_timesteps": 1000000,
|
23 |
+
"_total_timesteps": 1000000,
|
24 |
+
"_num_timesteps_at_start": 0,
|
25 |
+
"seed": null,
|
26 |
+
"action_noise": null,
|
27 |
+
"start_time": 1692469584917036247,
|
28 |
+
"learning_rate": 0.0007,
|
29 |
+
"tensorboard_log": null,
|
30 |
+
"_last_obs": {
|
31 |
+
":type:": "<class 'collections.OrderedDict'>",
|
32 |
+
":serialized:": "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",
|
33 |
+
"achieved_goal": "[[-2.4550467 1.8079145 1.3348882 ]\n [ 0.28831294 -0.00774798 0.44165477]\n [ 0.28831294 -0.00774798 0.44165477]\n [-3.2994232 2.9566765 -2.2159283 ]]",
|
34 |
+
"desired_goal": "[[-0.989277 0.48403224 1.1880586 ]\n [-0.83640355 1.1153401 1.7131724 ]\n [-0.08052751 0.24610342 -0.9734253 ]\n [-1.5107766 0.9822673 -1.0927742 ]]",
|
35 |
+
"observation": "[[-2.4550467 1.8079145 1.3348882 1.0541044 -1.6672704 1.3278633 ]\n [ 0.28831294 -0.00774798 0.44165477 0.4946456 -0.00604388 0.3859572 ]\n [ 0.28831294 -0.00774798 0.44165477 0.4946456 -0.00604388 0.3859572 ]\n [-3.2994232 2.9566765 -2.2159283 -1.8215652 1.0201007 0.7904826 ]]"
|
36 |
+
},
|
37 |
+
"_last_episode_starts": {
|
38 |
+
":type:": "<class 'numpy.ndarray'>",
|
39 |
+
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAABAQCUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
|
40 |
+
},
|
41 |
+
"_last_original_obs": {
|
42 |
+
":type:": "<class 'collections.OrderedDict'>",
|
43 |
+
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA8snsPLH2oTxNqvQ9DZeMPR9tAT3A1fI8+wBtvRPGwTzc8vI8Aej/vTzrA74bd989lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==",
|
44 |
+
"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]]",
|
45 |
+
"desired_goal": "[[ 0.02890489 0.01977095 0.11946545]\n [ 0.06864748 0.03159821 0.02964294]\n [-0.05786226 0.02365402 0.02965682]\n [-0.12495423 -0.12882704 0.10911389]]",
|
46 |
+
"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]]"
|
47 |
+
},
|
48 |
+
"_episode_num": 0,
|
49 |
+
"use_sde": false,
|
50 |
+
"sde_sample_freq": -1,
|
51 |
+
"_current_progress_remaining": 0.0,
|
52 |
+
"_stats_window_size": 100,
|
53 |
+
"ep_info_buffer": {
|
54 |
+
":type:": "<class 'collections.deque'>",
|
55 |
+
":serialized:": "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"
|
56 |
+
},
|
57 |
+
"ep_success_buffer": {
|
58 |
+
":type:": "<class 'collections.deque'>",
|
59 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
60 |
+
},
|
61 |
+
"_n_updates": 50000,
|
62 |
+
"n_steps": 5,
|
63 |
+
"gamma": 0.99,
|
64 |
+
"gae_lambda": 1.0,
|
65 |
+
"ent_coef": 0.0,
|
66 |
+
"vf_coef": 0.5,
|
67 |
+
"max_grad_norm": 0.5,
|
68 |
+
"normalize_advantage": false,
|
69 |
+
"observation_space": {
|
70 |
+
":type:": "<class 'gymnasium.spaces.dict.Dict'>",
|
71 |
+
":serialized:": "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",
|
72 |
+
"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, (6,), float32))])",
|
73 |
+
"_shape": null,
|
74 |
+
"dtype": null,
|
75 |
+
"_np_random": null
|
76 |
+
},
|
77 |
+
"action_space": {
|
78 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
79 |
+
":serialized:": "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",
|
80 |
+
"dtype": "float32",
|
81 |
+
"bounded_below": "[ True True True]",
|
82 |
+
"bounded_above": "[ True True True]",
|
83 |
+
"_shape": [
|
84 |
+
3
|
85 |
+
],
|
86 |
+
"low": "[-1. -1. -1.]",
|
87 |
+
"high": "[1. 1. 1.]",
|
88 |
+
"low_repr": "-1.0",
|
89 |
+
"high_repr": "1.0",
|
90 |
+
"_np_random": null
|
91 |
+
},
|
92 |
+
"n_envs": 4,
|
93 |
+
"lr_schedule": {
|
94 |
+
":type:": "<class 'function'>",
|
95 |
+
":serialized:": "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"
|
96 |
+
}
|
97 |
+
}
|
a2c-PandaReachDense-v3/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8d5808c9ecb6a7d5958de5eb35013d35a6fadf687271b30252343a198c376a91
|
3 |
+
size 44734
|
a2c-PandaReachDense-v3/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d437e3eb60e121f2df1577e81bf902921eb02f8d8e06c9a469a015264a8857cd
|
3 |
+
size 46014
|
a2c-PandaReachDense-v3/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-v3/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.1.0
|
4 |
+
- PyTorch: 2.0.1+cu118
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.23.5
|
7 |
+
- Cloudpickle: 2.2.1
|
8 |
+
- Gymnasium: 0.29.0
|
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 0x787fdd019990>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x787fdd01de00>"}, "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": 1692469584917036247, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-2.4550467 1.8079145 1.3348882 ]\n [ 0.28831294 -0.00774798 0.44165477]\n [ 0.28831294 -0.00774798 0.44165477]\n [-3.2994232 2.9566765 -2.2159283 ]]", "desired_goal": "[[-0.989277 0.48403224 1.1880586 ]\n [-0.83640355 1.1153401 1.7131724 ]\n [-0.08052751 0.24610342 -0.9734253 ]\n [-1.5107766 0.9822673 -1.0927742 ]]", "observation": "[[-2.4550467 1.8079145 1.3348882 1.0541044 -1.6672704 1.3278633 ]\n [ 0.28831294 -0.00774798 0.44165477 0.4946456 -0.00604388 0.3859572 ]\n [ 0.28831294 -0.00774798 0.44165477 0.4946456 -0.00604388 0.3859572 ]\n [-3.2994232 2.9566765 -2.2159283 -1.8215652 1.0201007 0.7904826 ]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAABAQCUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "[[ 0.02890489 0.01977095 0.11946545]\n [ 0.06864748 0.03159821 0.02964294]\n [-0.05786226 0.02365402 0.02965682]\n [-0.12495423 -0.12882704 0.10911389]]", "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 '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, (6,), 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]", "bounded_above": "[ True True True]", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.0", "OpenAI Gym": "0.25.2"}}
|
replay.mp4
ADDED
Binary file (751 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -0.19647101368755102, "std_reward": 0.08669766048515616, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-19T19:19:51.833021"}
|
vec_normalize.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:93970686043f2850e1ccffcd7c0642cc4200103206ddb11f72c1cbe63e22139f
|
3 |
+
size 2623
|