Hugging Face's logo

dungtd2403
/
a2c-PandaReachDense-v2

Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results
Model card Files Community
1
dungtd2403 commited on
Commit
a6ac41d
·
1 Parent(s): a54faed

UPLOAD MODEL

Browse files
Files changed (11) hide show
  1. README.md +37 -0
  2. a2c-PandaReachDense-v2.zip +3 -0
  3. a2c-PandaReachDense-v2/_stable_baselines3_version +1 -0
  4. a2c-PandaReachDense-v2/data +94 -0
  5. a2c-PandaReachDense-v2/policy.optimizer.pth +3 -0
  6. a2c-PandaReachDense-v2/policy.pth +3 -0
  7. a2c-PandaReachDense-v2/pytorch_variables.pth +3 -0
  8. a2c-PandaReachDense-v2/system_info.txt +7 -0
  9. config.json +1 -0
  10. replay.mp4 +0 -0
  11. results.json +1 -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: -2.54 +/- 0.44
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:de385bef04d75ed45f6ed487f5c4cc65dc7a8f9e2fecbf2ca9ae83d24198fb56
3
+ size 115572
a2c-PandaReachDense-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
a2c-PandaReachDense-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7fd321b96ee0>",
8
+ "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7fd321b97b80>"
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
+ "observation_space": {
23
+ ":type:": "<class 'gym.spaces.dict.Dict'>",
24
+ ":serialized:": "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",
25
+ "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))])",
26
+ "_shape": null,
27
+ "dtype": null,
28
+ "_np_random": null
29
+ },
30
+ "action_space": {
31
+ ":type:": "<class 'gym.spaces.box.Box'>",
32
+ ":serialized:": "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",
33
+ "dtype": "float32",
34
+ "_shape": [
35
+ 3
36
+ ],
37
+ "low": "[-1. -1. -1.]",
38
+ "high": "[1. 1. 1.]",
39
+ "bounded_below": "[ True True True]",
40
+ "bounded_above": "[ True True True]",
41
+ "_np_random": null
42
+ },
43
+ "n_envs": 20,
44
+ "num_timesteps": 1000000,
45
+ "_total_timesteps": 1000000,
46
+ "_num_timesteps_at_start": 0,
47
+ "seed": null,
48
+ "action_noise": null,
49
+ "start_time": 1682069731801450165,
50
+ "learning_rate": 0.0007,
51
+ "tensorboard_log": null,
52
+ "lr_schedule": {
53
+ ":type:": "<class 'function'>",
54
+ ":serialized:": "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"
55
+ },
56
+ "_last_obs": {
57
+ ":type:": "<class 'collections.OrderedDict'>",
58
+ ":serialized:": "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",
59
+ "achieved_goal": "[[0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]]",
60
+ "desired_goal": "[[-0.53107846 -1.4707826 -0.8956424 ]\n [ 1.0552645 -1.3575125 -1.5091821 ]\n [-0.44352257 -0.89970064 1.3312105 ]\n [-1.3509917 0.36882117 -0.20394756]\n [ 0.8220247 0.12068018 -1.332381 ]\n [-0.8678345 -0.80075514 -0.15934938]\n [-1.7115133 0.7838016 0.35017714]\n [ 0.97544706 0.32749248 -1.6276835 ]\n [-0.12264132 -1.3371422 0.67445934]\n [ 0.53074616 0.84058976 -0.6331333 ]\n [-0.04008456 1.3924253 -1.12953 ]\n [-1.3631772 0.48787647 0.27082938]\n [ 1.0948611 0.34355125 -0.01869993]\n [-0.24016751 0.07779362 0.06829292]\n [-1.6351295 0.47394106 -0.22601964]\n [-0.69791937 0.5056739 -1.1297716 ]\n [ 0.6211684 0.8932751 -1.3494475 ]\n [ 1.5875145 -1.1711041 -0.83491236]\n [ 0.09884629 0.57614434 -0.4365491 ]\n [-1.6438065 0.2527009 1.2604667 ]]",
61
+ "observation": "[[ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]]"
62
+ },
63
+ "_last_episode_starts": {
64
+ ":type:": "<class 'numpy.ndarray'>",
65
+ ":serialized:": "gAWVhwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYUAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksUhZSMAUOUdJRSlC4="
66
+ },
67
+ "_last_original_obs": {
68
+ ":type:": "<class 'collections.OrderedDict'>",
69
+ ":serialized:": "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",
70
+ "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]\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]\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]\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]\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]\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]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]",
71
+ "desired_goal": "[[ 0.09413335 -0.01882031 0.25073195]\n [-0.05618938 0.10624158 0.19512305]\n [ 0.07297471 -0.1485425 0.20474121]\n [-0.02871402 0.06476927 0.05301381]\n [-0.02980384 -0.10503923 0.18530077]\n [ 0.01990482 0.10240646 0.16490348]\n [-0.06577393 0.02997838 0.20839606]\n [ 0.05313187 0.10800289 0.07910573]\n [ 0.02539762 0.01085876 0.136643 ]\n [-0.12544903 0.07127339 0.08008247]\n [-0.13532579 -0.14935684 0.20745945]\n [ 0.01485917 0.12436228 0.05067174]\n [ 0.07933057 0.07172243 0.29178572]\n [ 0.00034459 0.11620568 0.24688637]\n [ 0.02226135 0.13601972 0.22737917]\n [ 0.0142379 0.06167288 0.17984307]\n [ 0.04183808 0.10094006 0.29970658]\n [ 0.12944095 0.00790316 0.01237978]\n [ 0.13662273 0.10746679 0.20955828]\n [-0.14154245 0.10401107 0.11310757]]",
72
+ "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]\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]\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]\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]\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]\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]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
73
+ },
74
+ "_episode_num": 0,
75
+ "use_sde": false,
76
+ "sde_sample_freq": -1,
77
+ "_current_progress_remaining": 0.0,
78
+ "ep_info_buffer": {
79
+ ":type:": "<class 'collections.deque'>",
80
+ ":serialized:": "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"
81
+ },
82
+ "ep_success_buffer": {
83
+ ":type:": "<class 'collections.deque'>",
84
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
85
+ },
86
+ "_n_updates": 10000,
87
+ "n_steps": 5,
88
+ "gamma": 0.99,
89
+ "gae_lambda": 1.0,
90
+ "ent_coef": 0.0,
91
+ "vf_coef": 0.5,
92
+ "max_grad_norm": 0.5,
93
+ "normalize_advantage": false
94
+ }
a2c-PandaReachDense-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f0b47851d9f86aa5e431a4d100966ff44095d31934e78c15b3ac1752ea5d7ea5
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:bed68d80b59babcc3ed80f1d7a4be868eea5b6c197f24fd3b66d588316556209
3
+ size 46014
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-5.15.0-69-generic-x86_64-with-glibc2.31 # 76~20.04.1-Ubuntu SMP Mon Mar 20 15:54:19 UTC 2023
2
+ - Python: 3.9.0
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu117
5
+ - GPU Enabled: True
6
+ - Numpy: 1.23.2
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 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 0x7fd321b96ee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd321b97b80>"}, "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}}, "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:": "gAWVbQEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaApLA4WUjAFDlHSUUpSMBGhpZ2iUaBIolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgKSwOFlGgVdJRSlIwNYm91bmRlZF9iZWxvd5RoEiiWAwAAAAAAAAABAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYDAAAAAAAAAAEBAZRoIUsDhZRoFXSUUpSMCl9ucF9yYW5kb22UTnViLg==", "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": 20, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682069731801450165, "learning_rate": 0.0007, "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": "[[0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]\n [0.3810234 0.00422501 0.51282835]]", "desired_goal": "[[-0.53107846 -1.4707826 -0.8956424 ]\n [ 1.0552645 -1.3575125 -1.5091821 ]\n [-0.44352257 -0.89970064 1.3312105 ]\n [-1.3509917 0.36882117 -0.20394756]\n [ 0.8220247 0.12068018 -1.332381 ]\n [-0.8678345 -0.80075514 -0.15934938]\n [-1.7115133 0.7838016 0.35017714]\n [ 0.97544706 0.32749248 -1.6276835 ]\n [-0.12264132 -1.3371422 0.67445934]\n [ 0.53074616 0.84058976 -0.6331333 ]\n [-0.04008456 1.3924253 -1.12953 ]\n [-1.3631772 0.48787647 0.27082938]\n [ 1.0948611 0.34355125 -0.01869993]\n [-0.24016751 0.07779362 0.06829292]\n [-1.6351295 0.47394106 -0.22601964]\n [-0.69791937 0.5056739 -1.1297716 ]\n [ 0.6211684 0.8932751 -1.3494475 ]\n [ 1.5875145 -1.1711041 -0.83491236]\n [ 0.09884629 0.57614434 -0.4365491 ]\n [-1.6438065 0.2527009 1.2604667 ]]", "observation": "[[ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]\n [ 0.3810234 0.00422501 0.51282835 -0.00608232 -0.00122006 0.0013309 ]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYUAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksUhZSMAUOUdJRSlC4="}, "_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]\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]\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]\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]\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]\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]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]", "desired_goal": "[[ 0.09413335 -0.01882031 0.25073195]\n [-0.05618938 0.10624158 0.19512305]\n [ 0.07297471 -0.1485425 0.20474121]\n [-0.02871402 0.06476927 0.05301381]\n [-0.02980384 -0.10503923 0.18530077]\n [ 0.01990482 0.10240646 0.16490348]\n [-0.06577393 0.02997838 0.20839606]\n [ 0.05313187 0.10800289 0.07910573]\n [ 0.02539762 0.01085876 0.136643 ]\n [-0.12544903 0.07127339 0.08008247]\n [-0.13532579 -0.14935684 0.20745945]\n [ 0.01485917 0.12436228 0.05067174]\n [ 0.07933057 0.07172243 0.29178572]\n [ 0.00034459 0.11620568 0.24688637]\n [ 0.02226135 0.13601972 0.22737917]\n [ 0.0142379 0.06167288 0.17984307]\n [ 0.04183808 0.10094006 0.29970658]\n [ 0.12944095 0.00790316 0.01237978]\n [ 0.13662273 0.10746679 0.20955828]\n [-0.14154245 0.10401107 0.11310757]]", "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]\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]\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]\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]\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]\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]\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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIyF2EKcql1b+UhpRSlIwBbJRLMowBdJRHQKD43u2qkuZ1fZQoaAZoCWgPQwh2i8BY38DQv5SGlFKUaBVLMmgWR0Cg+Jn4XXRPdX2UKGgGaAloD0MI2ZjXEYdsyL+UhpRSlGgVSzJoFkdAoPhUAcT8HnV9lChoBmgJaA9DCPdWJCao4dS/lIaUUpRoFUsyaBZHQKD4DjhDPWx1fZQoaAZoCWgPQwhXBWoxeJjGv5SGlFKUaBVLMmgWR0Cg98en62v0dX2UKGgGaAloD0MIuaXVkLjH07+UhpRSlGgVSzJoFkdAoPeBcHGCI3V9lChoBmgJaA9DCKH18GWiCOG/lIaUUpRoFUsyaBZHQKD3OvwEyL11fZQoaAZoCWgPQwj0GrtE9dbWv5SGlFKUaBVLMmgWR0Cg9vRx95QhdX2UKGgGaAloD0MIvTWwVYLF2r+UhpRSlGgVSzJoFkdAoPat0NjLCHV9lChoBmgJaA9DCG5oyk4/qOG/lIaUUpRoFUsyaBZHQKD2Z114gRt1fZQoaAZoCWgPQwiGcTeI1griv5SGlFKUaBVLMmgWR0Cg9iGO2iL3dX2UKGgGaAloD0MI0PHR4ozh4L+UhpRSlGgVSzJoFkdAoPXaN83Mp3V9lChoBmgJaA9DCFlrKLUX0dq/lIaUUpRoFUsyaBZHQKD1k7+1jRV1fZQoaAZoCWgPQwjXFwltOZfWv5SGlFKUaBVLMmgWR0Cg9U0DMeOodX2UKGgGaAloD0MI8aFESx7P4L+UhpRSlGgVSzJoFkdAoPUFxlxwQ3V9lChoBmgJaA9DCHr/HydMGNS/lIaUUpRoFUsyaBZHQKD0vz+3pfR1fZQoaAZoCWgPQwjbboJvmj7fv5SGlFKUaBVLMmgWR0Cg9Hlrl/6PdX2UKGgGaAloD0MIhQoOL4hI0L+UhpRSlGgVSzJoFkdAoPQydQO4G3V9lChoBmgJaA9DCKn4vyMqVNC/lIaUUpRoFUsyaBZHQKDz6sFt8/l1fZQoaAZoCWgPQwhIMUCiCRTTv5SGlFKUaBVLMmgWR0Cg86QPZqVRdX2UKGgGaAloD0MIbR/ylqsf37+UhpRSlGgVSzJoFkdAoP3PBN21UnV9lChoBmgJaA9DCD49tmXAWeK/lIaUUpRoFUsyaBZHQKD9ifTTfBN1fZQoaAZoCWgPQwjCMcueBLbgv5SGlFKUaBVLMmgWR0Cg/UQDNhVmdX2UKGgGaAloD0MI3o0FhUGZxr+UhpRSlGgVSzJoFkdAoPz+M4tHx3V9lChoBmgJaA9DCLM/UG7b99C/lIaUUpRoFUsyaBZHQKD8t8QZn+R1fZQoaAZoCWgPQwhrC89LxcbZv5SGlFKUaBVLMmgWR0Cg/HF+Vkc0dX2UKGgGaAloD0MIpDMw8rKm47+UhpRSlGgVSzJoFkdAoPwrFGXoknV9lChoBmgJaA9DCOfkRSbg19+/lIaUUpRoFUsyaBZHQKD75H4oJAt1fZQoaAZoCWgPQwjQRUPGo1TIv5SGlFKUaBVLMmgWR0Cg+53Dm8ujdX2UKGgGaAloD0MIdH0fDhKi0r+UhpRSlGgVSzJoFkdAoPtXTPSlWXV9lChoBmgJaA9DCCGtMeiE0NC/lIaUUpRoFUsyaBZHQKD7EWqtHQR1fZQoaAZoCWgPQwgC9Pv+zYvHv5SGlFKUaBVLMmgWR0Cg+soHTqjadX2UKGgGaAloD0MIVHB4QURq2r+UhpRSlGgVSzJoFkdAoPqDhP0qY3V9lChoBmgJaA9DCPWhC+pb5tK/lIaUUpRoFUsyaBZHQKD6POD8Lrp1fZQoaAZoCWgPQwjFyf0ORYHev5SGlFKUaBVLMmgWR0Cg+fWNedCmdX2UKGgGaAloD0MIlpUmpaBb47+UhpRSlGgVSzJoFkdAoPmvO6d1+3V9lChoBmgJaA9DCONUa2EW2ta/lIaUUpRoFUsyaBZHQKD5aeuFHrh1fZQoaAZoCWgPQwih98YQABzLv5SGlFKUaBVLMmgWR0Cg+SMCcPOIdX2UKGgGaAloD0MIxebj2lAxzL+UhpRSlGgVSzJoFkdAoPjbZvkzXXV9lChoBmgJaA9DCOxq8pTVdNO/lIaUUpRoFUsyaBZHQKD4lLr5ZbJ1fZQoaAZoCWgPQwj7ITZYOEnZv5SGlFKUaBVLMmgWR0ChAtrmp2lmdX2UKGgGaAloD0MIOBCSBUzgzr+UhpRSlGgVSzJoFkdAoQKV9Dx9X3V9lChoBmgJaA9DCHWQ14NJ8dS/lIaUUpRoFUsyaBZHQKECT+Idlup1fZQoaAZoCWgPQwiCj8GKU63fv5SGlFKUaBVLMmgWR0ChAgoN3GGVdX2UKGgGaAloD0MI3V1nQ/6Z5b+UhpRSlGgVSzJoFkdAoQHEGPgeinV9lChoBmgJaA9DCJKU9DC0Ot+/lIaUUpRoFUsyaBZHQKEBfd+G47R1fZQoaAZoCWgPQwhoeLMG76vav5SGlFKUaBVLMmgWR0ChATduYQardX2UKGgGaAloD0MIrDsW26Six7+UhpRSlGgVSzJoFkdAoQDw9cKPXHV9lChoBmgJaA9DCKOx9ne2R9C/lIaUUpRoFUsyaBZHQKEAqkUsWft1fZQoaAZoCWgPQwjwxKwXQznWv5SGlFKUaBVLMmgWR0ChAGPLHMlkdX2UKGgGaAloD0MIC5dV2Axw0r+UhpRSlGgVSzJoFkdAoQAd8VpKz3V9lChoBmgJaA9DCDlf7L34Iua/lIaUUpRoFUsyaBZHQKD/10ZFXq91fZQoaAZoCWgPQwjT9NkB1xXPv5SGlFKUaBVLMmgWR0Cg/5DGcWj5dX2UKGgGaAloD0MITkaVYdwN2b+UhpRSlGgVSzJoFkdAoP9KGBWge3V9lChoBmgJaA9DCMCWV663zdq/lIaUUpRoFUsyaBZHQKD/At7KJVN1fZQoaAZoCWgPQwiVn1T7dDzcv5SGlFKUaBVLMmgWR0Cg/ryIHkcTdX2UKGgGaAloD0MIqIx/n3Hh1L+UhpRSlGgVSzJoFkdAoP52jGkvb3V9lChoBmgJaA9DCFQ1QdR9AOC/lIaUUpRoFUsyaBZHQKD+L6Vt4zJ1fZQoaAZoCWgPQwgOoN/3b17hv5SGlFKUaBVLMmgWR0Cg/efYraufdX2UKGgGaAloD0MIeHqlLEMc27+UhpRSlGgVSzJoFkdAoP2g+fRNRHV9lChoBmgJaA9DCOWzPA/uTuS/lIaUUpRoFUsyaBZHQKEH5PJJXhh1fZQoaAZoCWgPQwh6q65DNSXZv5SGlFKUaBVLMmgWR0ChB6ANgBtDdX2UKGgGaAloD0MIixpMw/AR1L+UhpRSlGgVSzJoFkdAoQdaD0163XV9lChoBmgJaA9DCEhPkUPEzda/lIaUUpRoFUsyaBZHQKEHFCswL3N1fZQoaAZoCWgPQwi2upwSEJPTv5SGlFKUaBVLMmgWR0ChBs2joIOZdX2UKGgGaAloD0MIoUs49BYP0r+UhpRSlGgVSzJoFkdAoQaHWWhRInV9lChoBmgJaA9DCEMewY2ULd+/lIaUUpRoFUsyaBZHQKEGQK0D2al1fZQoaAZoCWgPQwhtkbQbfUzgv5SGlFKUaBVLMmgWR0ChBfoppeu3dX2UKGgGaAloD0MI9UpZhjjW0L+UhpRSlGgVSzJoFkdAoQWzhm5DqnV9lChoBmgJaA9DCAUabOo8Ksy/lIaUUpRoFUsyaBZHQKEFbRJEpiJ1fZQoaAZoCWgPQwg3UrZI2o3Zv5SGlFKUaBVLMmgWR0ChBSdIwudxdX2UKGgGaAloD0MIT7LV5ZSA0L+UhpRSlGgVSzJoFkdAoQTf8n/kvXV9lChoBmgJaA9DCBO54Az+fs+/lIaUUpRoFUsyaBZHQKEEmWrwOON1fZQoaAZoCWgPQwjoE3mSdM3Rv5SGlFKUaBVLMmgWR0ChBFKx9oexdX2UKGgGaAloD0MIGCXoL/QI4r+UhpRSlGgVSzJoFkdAoQQLcO9WZXV9lChoBmgJaA9DCOohGt1B7NK/lIaUUpRoFUsyaBZHQKEDxRLsa891fZQoaAZoCWgPQwi31awzvi/cv5SGlFKUaBVLMmgWR0ChA37p/wy7dX2UKGgGaAloD0MI5llJK76h1L+UhpRSlGgVSzJoFkdAoQM4COmzjXV9lChoBmgJaA9DCGxfQC/cudC/lIaUUpRoFUsyaBZHQKEC8GFi8Wd1fZQoaAZoCWgPQwiuuDgqN9Hhv5SGlFKUaBVLMmgWR0ChAqmpVCHAdX2UKGgGaAloD0MIjuVd9YB53r+UhpRSlGgVSzJoFkdAoQzENH6MznV9lChoBmgJaA9DCMJNRpVh3Na/lIaUUpRoFUsyaBZHQKEMf0V8CxN1fZQoaAZoCWgPQwix4H7AAwPhv5SGlFKUaBVLMmgWR0ChDDlFtsN2dX2UKGgGaAloD0MInG9E96xr37+UhpRSlGgVSzJoFkdAoQvzamGdqnV9lChoBmgJaA9DCPci2o6pu9u/lIaUUpRoFUsyaBZHQKELrOPeYUp1fZQoaAZoCWgPQwgCDMufbwvgv5SGlFKUaBVLMmgWR0ChC2a5PM0QdX2UKGgGaAloD0MIgA9eu7Th4b+UhpRSlGgVSzJoFkdAoQsgQe3hGnV9lChoBmgJaA9DCGqGVFG8ytm/lIaUUpRoFUsyaBZHQKEK2cENe+p1fZQoaAZoCWgPQwjGhQMhWcDUv5SGlFKUaBVLMmgWR0ChCpMUqQRxdX2UKGgGaAloD0MIOPQWD+8527+UhpRSlGgVSzJoFkdAoQpMl7dBSnV9lChoBmgJaA9DCLG/7J48LNm/lIaUUpRoFUsyaBZHQKEKBrJr+Hd1fZQoaAZoCWgPQwiaCYZzDTPXv5SGlFKUaBVLMmgWR0ChCb9U0elsdX2UKGgGaAloD0MIcVrwoq8g1L+UhpRSlGgVSzJoFkdAoQl440dilXV9lChoBmgJaA9DCET7WMFvQ92/lIaUUpRoFUsyaBZHQKEJMjZcs191fZQoaAZoCWgPQwiPVrWko5zgv5SGlFKUaBVLMmgWR0ChCOr1dxACdX2UKGgGaAloD0MIA2A8g4b+3r+UhpRSlGgVSzJoFkdAoQikmjTKDHV9lChoBmgJaA9DCNZSQNr/ANC/lIaUUpRoFUsyaBZHQKEIXsJpnHx1fZQoaAZoCWgPQwj7sN6oFabfv5SGlFKUaBVLMmgWR0ChCBfe+Eh8dX2UKGgGaAloD0MIu31WmSmt2r+UhpRSlGgVSzJoFkdAoQfQNCqp+HV9lChoBmgJaA9DCBAIdCZtqtC/lIaUUpRoFUsyaBZHQKEHiXRgJC11ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 10000, "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, "system_info": {"OS": "Linux-5.15.0-69-generic-x86_64-with-glibc2.31 # 76~20.04.1-Ubuntu SMP Mon Mar 20 15:54:19 UTC 2023", "Python": "3.9.0", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.23.2", "Gym": "0.21.0"}}
replay.mp4 ADDED
Binary file (531 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -2.5445211, "std_reward": 0.4389262065615244, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-21T17:14:31.751564"}