marianafmedeiros
commited on
Commit
•
28a1026
1
Parent(s):
b10ad65
Initial commit2
Browse files- README.md +1 -1
- a2c-PandaReachDense-v2.zip +2 -2
- a2c-PandaReachDense-v2/data +11 -11
- a2c-PandaReachDense-v2/policy.optimizer.pth +1 -1
- a2c-PandaReachDense-v2/policy.pth +1 -1
- config.json +1 -1
- results.json +1 -1
- vec_normalize.pkl +1 -1
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: PandaReachDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value: -
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: PandaReachDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: -2.02 +/- 0.99
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
a2c-PandaReachDense-v2.zip
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fc0cc8ebb0c03adac464b92c090b94476b16826f51f31241c52c8215a23c2eee
|
3 |
+
size 107944
|
a2c-PandaReachDense-v2/data
CHANGED
@@ -19,12 +19,12 @@
|
|
19 |
"weight_decay": 0
|
20 |
}
|
21 |
},
|
22 |
-
"num_timesteps":
|
23 |
-
"_total_timesteps":
|
24 |
"_num_timesteps_at_start": 0,
|
25 |
"seed": null,
|
26 |
"action_noise": null,
|
27 |
-
"start_time":
|
28 |
"learning_rate": 0.0007,
|
29 |
"tensorboard_log": null,
|
30 |
"lr_schedule": {
|
@@ -33,10 +33,10 @@
|
|
33 |
},
|
34 |
"_last_obs": {
|
35 |
":type:": "<class 'collections.OrderedDict'>",
|
36 |
-
":serialized:": "
|
37 |
-
"achieved_goal": "[[0.
|
38 |
-
"desired_goal": "[[-1.
|
39 |
-
"observation": "[[0.
|
40 |
},
|
41 |
"_last_episode_starts": {
|
42 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -44,9 +44,9 @@
|
|
44 |
},
|
45 |
"_last_original_obs": {
|
46 |
":type:": "<class 'collections.OrderedDict'>",
|
47 |
-
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPQFqGqxDI0o+6nIdPQFqGqxDI0o+6nIdPQFqGqxDI0o+6nIdPQFqGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////
|
48 |
"achieved_goal": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]]",
|
49 |
-
"desired_goal": "[[
|
50 |
"observation": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
|
51 |
},
|
52 |
"_episode_num": 0,
|
@@ -56,13 +56,13 @@
|
|
56 |
"_stats_window_size": 100,
|
57 |
"ep_info_buffer": {
|
58 |
":type:": "<class 'collections.deque'>",
|
59 |
-
":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////
|
60 |
},
|
61 |
"ep_success_buffer": {
|
62 |
":type:": "<class 'collections.deque'>",
|
63 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
64 |
},
|
65 |
-
"_n_updates":
|
66 |
"n_steps": 5,
|
67 |
"gamma": 0.99,
|
68 |
"gae_lambda": 1.0,
|
|
|
19 |
"weight_decay": 0
|
20 |
}
|
21 |
},
|
22 |
+
"num_timesteps": 1010000,
|
23 |
+
"_total_timesteps": 1010000,
|
24 |
"_num_timesteps_at_start": 0,
|
25 |
"seed": null,
|
26 |
"action_noise": null,
|
27 |
+
"start_time": 1690147718571213000,
|
28 |
"learning_rate": 0.0007,
|
29 |
"tensorboard_log": null,
|
30 |
"lr_schedule": {
|
|
|
33 |
},
|
34 |
"_last_obs": {
|
35 |
":type:": "<class 'collections.OrderedDict'>",
|
36 |
+
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAArIHJPrpYh7wbihU/rIHJPrpYh7wbihU/rIHJPrpYh7wbihU/rIHJPrpYh7wbihU/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAYQSpv8fbxT8mx0S/a51rv4m2cz0jUZ8/j+HOP5lWk78yFaM/YmOMP+CL1D+fYts+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAACsgck+uliHvBuKFT+uMHi8gFO3umA5vrysgck+uliHvBuKFT+uMHi8gFO3umA5vrysgck+uliHvBuKFT+uMHi8gFO3umA5vrysgck+uliHvBuKFT+uMHi8gFO3umA5vryUaA5LBEsGhpRoEnSUUpR1Lg==",
|
37 |
+
"achieved_goal": "[[ 0.39356744 -0.0165218 0.5841386 ]\n [ 0.39356744 -0.0165218 0.5841386 ]\n [ 0.39356744 -0.0165218 0.5841386 ]\n [ 0.39356744 -0.0165218 0.5841386 ]]",
|
38 |
+
"desired_goal": "[[-1.3204461 1.5457696 -0.76866376]\n [-0.92037076 0.05950025 1.2446636 ]\n [ 1.6162585 -1.1510803 1.2740843 ]\n [ 1.0967829 1.6605186 0.4284868 ]]",
|
39 |
+
"observation": "[[ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]\n [ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]\n [ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]\n [ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]]"
|
40 |
},
|
41 |
"_last_episode_starts": {
|
42 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
44 |
},
|
45 |
"_last_original_obs": {
|
46 |
":type:": "<class 'collections.OrderedDict'>",
|
47 |
+
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPQFqGqxDI0o+6nIdPQFqGqxDI0o+6nIdPQFqGqxDI0o+6nIdPQFqGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAxByyPQbXVrwsYTk+mat/vLk8hT2q5Xc978qEvOmz2z3eYhw9XqWJPd7j6j343Co+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09AWoarEMjSj4AAAAAAAAAgAAAAADqch09AWoarEMjSj4AAAAAAAAAgAAAAADqch09AWoarEMjSj4AAAAAAAAAgAAAAADqch09AWoarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==",
|
48 |
"achieved_goal": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]]",
|
49 |
+
"desired_goal": "[[ 0.08696893 -0.01311279 0.18103474]\n [-0.01560488 0.06505723 0.06052176]\n [-0.01621005 0.10727675 0.03818022]\n [ 0.06720994 0.11469243 0.16685855]]",
|
50 |
"observation": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
|
51 |
},
|
52 |
"_episode_num": 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": 50500,
|
66 |
"n_steps": 5,
|
67 |
"gamma": 0.99,
|
68 |
"gae_lambda": 1.0,
|
a2c-PandaReachDense-v2/policy.optimizer.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 44606
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fbe2d6386ae555433a34056c1c660e979ac34fd95d984012d1bc6219e76c8a39
|
3 |
size 44606
|
a2c-PandaReachDense-v2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 45886
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c301be6a116fa66dfb78552788d4af4eafa1a0d64147ba83d787a925613a9fdb
|
3 |
size 45886
|
config.json
CHANGED
@@ -1 +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 0x16d727430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x16d726480>"}, "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": 1690145971259490000, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAaFTNPtUqlDxKxBE/aFTNPtUqlDxKxBE/aFTNPtUqlDxKxBE/aFTNPtUqlDxKxBE/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAHmGiv2Kp0r89UXQ/QMm8P+ntEL8pM80+8jzyvZU8g7/4JoA/MpSgP9Ei1rwfF7S/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAABoVM0+1SqUPErEET+bmUg8jj0bOzb4gTxoVM0+1SqUPErEET+bmUg8jj0bOzb4gTxoVM0+1SqUPErEET+bmUg8jj0bOzb4gTxoVM0+1SqUPErEET+bmUg8jj0bOzb4gTyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.4010346 0.01808683 0.5694014 ]\n [0.4010346 0.01808683 0.5694014 ]\n [0.4010346 0.01808683 0.5694014 ]\n [0.4010346 0.01808683 0.5694014 ]]", "desired_goal": "[[-1.2685888 -1.6457942 0.9543646 ]\n [ 1.4748917 -0.5661302 0.40078095]\n [-0.11828031 -1.0252863 1.0011892 ]\n [ 1.2545226 -0.02613965 -1.4069556 ]]", "observation": "[[0.4010346 0.01808683 0.5694014 0.01224365 0.00236878 0.01586543]\n [0.4010346 0.01808683 0.5694014 0.01224365 0.00236878 0.01586543]\n [0.4010346 0.01808683 0.5694014 0.01224365 0.00236878 0.01586543]\n [0.4010346 0.01808683 0.5694014 0.01224365 0.00236878 0.01586543]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]]", "desired_goal": "[[-0.02664285 0.00382475 0.03706342]\n [ 0.08257988 -0.102946 0.21118966]\n [ 0.0449439 0.0539487 0.262205 ]\n [-0.09315067 0.10781306 0.15134561]]", "observation": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-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 'gym.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 'gym.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, "system_info": {"OS": "macOS-13.4.1-arm64-arm-64bit Darwin Kernel Version 22.5.0: Thu Jun 8 22:22:20 PDT 2023; root:xnu-8796.121.3~7/RELEASE_ARM64_T6000", "Python": "3.9.17", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1", "GPU Enabled": "False", "Numpy": "1.25.1", "Gym": "0.23.0"}}
|
|
|
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 0x16d727430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x16d726480>"}, "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": 1010000, "_total_timesteps": 1010000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1690147718571213000, "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": "[[ 0.39356744 -0.0165218 0.5841386 ]\n [ 0.39356744 -0.0165218 0.5841386 ]\n [ 0.39356744 -0.0165218 0.5841386 ]\n [ 0.39356744 -0.0165218 0.5841386 ]]", "desired_goal": "[[-1.3204461 1.5457696 -0.76866376]\n [-0.92037076 0.05950025 1.2446636 ]\n [ 1.6162585 -1.1510803 1.2740843 ]\n [ 1.0967829 1.6605186 0.4284868 ]]", "observation": "[[ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]\n [ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]\n [ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]\n [ 0.39356744 -0.0165218 0.5841386 -0.01514832 -0.00139867 -0.02322072]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01]]", "desired_goal": "[[ 0.08696893 -0.01311279 0.18103474]\n [-0.01560488 0.06505723 0.06052176]\n [-0.01621005 0.10727675 0.03818022]\n [ 0.06720994 0.11469243 0.16685855]]", "observation": "[[ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1943560e-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": 50500, "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 'gym.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 'gym.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, "system_info": {"OS": "macOS-13.4.1-arm64-arm-64bit Darwin Kernel Version 22.5.0: Thu Jun 8 22:22:20 PDT 2023; root:xnu-8796.121.3~7/RELEASE_ARM64_T6000", "Python": "3.9.17", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1", "GPU Enabled": "False", "Numpy": "1.25.1", "Gym": "0.23.0"}}
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward": -
|
|
|
1 |
+
{"mean_reward": -2.0182852809550242, "std_reward": 0.98906562506113, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-23T18:59:27.335619"}
|
vec_normalize.pkl
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 2515
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2af654df20ddf5ba3fe73a2bb193bab4c4473b617156615d90457582cedf3c07
|
3 |
size 2515
|