Model commit: PandaPickAndPlaceSAC-n3
Browse files- PandaPickAndPlaceSAC-n3.zip +3 -0
- PandaPickAndPlaceSAC-n3/_stable_baselines3_version +1 -0
- PandaPickAndPlaceSAC-n3/actor.optimizer.pth +3 -0
- PandaPickAndPlaceSAC-n3/critic.optimizer.pth +3 -0
- PandaPickAndPlaceSAC-n3/data +117 -0
- PandaPickAndPlaceSAC-n3/ent_coef_optimizer.pth +3 -0
- PandaPickAndPlaceSAC-n3/policy.pth +3 -0
- PandaPickAndPlaceSAC-n3/pytorch_variables.pth +3 -0
- PandaPickAndPlaceSAC-n3/system_info.txt +7 -0
- README.md +1 -1
- config.json +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
- vec_normalize.pkl +2 -2
PandaPickAndPlaceSAC-n3.zip
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PandaPickAndPlaceSAC-n3/_stable_baselines3_version
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PandaPickAndPlaceSAC-n3/actor.optimizer.pth
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PandaPickAndPlaceSAC-n3/critic.optimizer.pth
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PandaPickAndPlaceSAC-n3/data
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{
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"policy_class": {
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":type:": "<class 'abc.ABCMeta'>",
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"__module__": "stable_baselines3.sac.policies",
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"__doc__": "\n Policy class (with both actor and critic) for SAC.\n\n :param observation_space: Observation space\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 use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE 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 clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\n :param features_extractor_class: Features extractor to use.\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 :param n_critics: Number of critic networks to create.\n :param share_features_extractor: Whether to share or not the features extractor\n between the actor and the critic (this saves computation time)\n ",
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},
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|
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}
|
PandaPickAndPlaceSAC-n3/ent_coef_optimizer.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 1507
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PandaPickAndPlaceSAC-n3/policy.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:0e43ce9fc6451f47383da1f54aebe0664c356ea7c0077cca7d34d6d27324c422
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size 253768
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PandaPickAndPlaceSAC-n3/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:c1b6ecb22d52a2ffa96ff04f7ece0fc28454f86b476fa84185fcee6acde54e67
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size 747
|
PandaPickAndPlaceSAC-n3/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
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1 |
+
- OS: Linux-5.15.0-60-generic-x86_64-with-glibc2.35 # 66-Ubuntu SMP Fri Jan 20 14:29:49 UTC 2023
|
2 |
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- Python: 3.9.16
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
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- PyTorch: 1.13.1+cu117
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.21.6
|
7 |
+
- Gym: 0.21.0
|
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: PandaPickAndPlaceDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value: -
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: PandaPickAndPlaceDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: -10.03 +/- 2.69
|
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name: mean_reward
|
21 |
verified: false
|
22 |
---
|
config.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNwAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnNhYy5wb2xpY2llc5SMEE11bHRpSW5wdXRQb2xpY3mUk5Qu", "__module__": "stable_baselines3.sac.policies", "__doc__": "\n Policy class (with both actor and critic) for SAC.\n\n :param observation_space: Observation space\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 use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. 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