second commit
Browse files- README.md +1 -1
- a2c-PandaReachDense-v2.zip +2 -2
- a2c-PandaReachDense-v2/data +14 -14
- a2c-PandaReachDense-v2/policy.optimizer.pth +1 -1
- a2c-PandaReachDense-v2/policy.pth +1 -1
- config.json +1 -1
- replay.mp4 +0 -0
- 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: -2.
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: PandaReachDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: -2.69 +/- 1.03
|
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:f738704897811a249c1995bec9c548ab12153387c980ddba99e053a00c11198a
|
3 |
+
size 108089
|
a2c-PandaReachDense-v2/data
CHANGED
@@ -4,9 +4,9 @@
|
|
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
|
8 |
"__abstractmethods__": "frozenset()",
|
9 |
-
"_abc_impl": "<_abc._abc_data object at
|
10 |
},
|
11 |
"verbose": 1,
|
12 |
"policy_kwargs": {
|
@@ -19,12 +19,12 @@
|
|
19 |
"weight_decay": 0
|
20 |
}
|
21 |
},
|
22 |
-
"num_timesteps":
|
23 |
"_total_timesteps": 1000000,
|
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": {
|
@@ -33,36 +33,36 @@
|
|
33 |
},
|
34 |
"_last_obs": {
|
35 |
":type:": "<class 'collections.OrderedDict'>",
|
36 |
-
":serialized:": "
|
37 |
-
"achieved_goal": "[[
|
38 |
-
"desired_goal": "[[-1.
|
39 |
-
"observation": "[[
|
40 |
},
|
41 |
"_last_episode_starts": {
|
42 |
":type:": "<class 'numpy.ndarray'>",
|
43 |
-
":serialized:": "
|
44 |
},
|
45 |
"_last_original_obs": {
|
46 |
":type:": "<class 'collections.OrderedDict'>",
|
47 |
-
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////
|
48 |
"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]]",
|
49 |
-
"desired_goal": "[[
|
50 |
"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]]"
|
51 |
},
|
52 |
"_episode_num": 0,
|
53 |
"use_sde": false,
|
54 |
"sde_sample_freq": -1,
|
55 |
-
"_current_progress_remaining": 0.
|
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,
|
|
|
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 0x7f3e97bc9090>",
|
8 |
"__abstractmethods__": "frozenset()",
|
9 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f3e97bd1440>"
|
10 |
},
|
11 |
"verbose": 1,
|
12 |
"policy_kwargs": {
|
|
|
19 |
"weight_decay": 0
|
20 |
}
|
21 |
},
|
22 |
+
"num_timesteps": 398580,
|
23 |
"_total_timesteps": 1000000,
|
24 |
"_num_timesteps_at_start": 0,
|
25 |
"seed": null,
|
26 |
"action_noise": null,
|
27 |
+
"start_time": 1685238426526340815,
|
28 |
"learning_rate": 0.0007,
|
29 |
"tensorboard_log": null,
|
30 |
"lr_schedule": {
|
|
|
33 |
},
|
34 |
"_last_obs": {
|
35 |
":type:": "<class 'collections.OrderedDict'>",
|
36 |
+
":serialized:": "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",
|
37 |
+
"achieved_goal": "[[-0.7917432 0.03803741 -0.4598822 ]\n [-0.3593167 0.25153124 0.05122437]\n [-0.1393069 -0.10529448 -0.5856322 ]\n [ 0.786882 -0.0484037 -0.755384 ]]",
|
38 |
+
"desired_goal": "[[-1.0225276 -0.11311968 -0.61802536]\n [-0.5885794 0.2863355 -0.2553675 ]\n [-0.34455928 -0.4958089 -1.0230689 ]\n [ 0.9293512 -0.20871052 -1.4284213 ]]",
|
39 |
+
"observation": "[[-0.7917432 0.03803741 -0.4598822 1.4324336 0.90027636 0.12019604]\n [-0.3593167 0.25153124 0.05122437 0.56592625 1.4030783 -0.14862114]\n [-0.1393069 -0.10529448 -0.5856322 -0.98399276 -0.2993722 -0.4350289 ]\n [ 0.786882 -0.0484037 -0.755384 -0.02299824 0.24331403 0.08272691]]"
|
40 |
},
|
41 |
"_last_episode_starts": {
|
42 |
":type:": "<class 'numpy.ndarray'>",
|
43 |
+
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
|
44 |
},
|
45 |
"_last_original_obs": {
|
46 |
":type:": "<class 'collections.OrderedDict'>",
|
47 |
+
":serialized:": "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",
|
48 |
"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]]",
|
49 |
+
"desired_goal": "[[-0.10580213 0.03239889 0.22969934]\n [-0.04433484 -0.00617912 0.09831697]\n [-0.02869451 -0.00102089 0.10868603]\n [ 0.14143941 -0.01827629 0.22064818]]",
|
50 |
"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]]"
|
51 |
},
|
52 |
"_episode_num": 0,
|
53 |
"use_sde": false,
|
54 |
"sde_sample_freq": -1,
|
55 |
+
"_current_progress_remaining": 0.6014200000000001,
|
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": 19928,
|
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 44734
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6bb338d20f98c725a38c498d974fd979170954d81dbebdc284654a883262a189
|
3 |
size 44734
|
a2c-PandaReachDense-v2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 46014
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4436006cb3c9a12cf31c9f596c2b78985cb72a34230a93e27daecef1286cd77a
|
3 |
size 46014
|
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 0x7f2283106050>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f2283102d00>"}, "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": 1685230866076228767, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuCQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz9G8AaNuLrHhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.33388168 -0.04672938 0.547645 ]\n [ 0.33388168 -0.04672938 0.547645 ]\n [ 0.33388168 -0.04672938 0.547645 ]\n [ 0.33388168 -0.04672938 0.547645 ]]", "desired_goal": "[[-1.5351527 0.49413338 0.18646215]\n [-0.75861937 0.08183311 0.6897201 ]\n [ 0.09106077 -1.3508042 0.45501223]\n [-1.474033 -1.186071 -0.284798 ]]", "observation": "[[ 0.33388168 -0.04672938 0.547645 -0.01581281 -0.00568701 -0.00290259]\n [ 0.33388168 -0.04672938 0.547645 -0.01581281 -0.00568701 -0.00290259]\n [ 0.33388168 -0.04672938 0.547645 -0.01581281 -0.00568701 -0.00290259]\n [ 0.33388168 -0.04672938 0.547645 -0.01581281 -0.00568701 -0.00290259]]"}, "_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 -2.1944723e-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": "[[ 0.10915751 -0.09646974 0.13011518]\n [ 0.06328911 -0.05896574 0.1291463 ]\n [ 0.04809224 -0.03873277 0.29037142]\n [-0.08281411 -0.07237207 0.19026269]]", "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:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMImbfqOlRTAcCUhpRSlIwBbJRLMowBdJRHQKc3TmCiAUd1fZQoaAZoCWgPQwi86gHzkEkFwJSGlFKUaBVLMmgWR0CnNxRx95QhdX2UKGgGaAloD0MIMuauJeRD/7+UhpRSlGgVSzJoFkdApzbb+NtIkXV9lChoBmgJaA9DCJLn+j4cpALAlIaUUpRoFUsyaBZHQKc2aaFVT751fZQoaAZoCWgPQwgsYthhTPr5v5SGlFKUaBVLMmgWR0CnOF1HOKO1dX2UKGgGaAloD0MIzqeOVUoPCsCUhpRSlGgVSzJoFkdApzgjp3X7L3V9lChoBmgJaA9DCD86deWzfP2/lIaUUpRoFUsyaBZHQKc362qkuYh1fZQoaAZoCWgPQwi1+1WA77b+v5SGlFKUaBVLMmgWR0CnN3lFDv3KdX2UKGgGaAloD0MIk/3zNGDwAMCUhpRSlGgVSzJoFkdApzlLDdgv13V9lChoBmgJaA9DCI1donprAAnAlIaUUpRoFUsyaBZHQKc5EOf/WDp1fZQoaAZoCWgPQwirz9VW7C/+v5SGlFKUaBVLMmgWR0CnONh2OhkBdX2UKGgGaAloD0MIh8PSwI/qAMCUhpRSlGgVSzJoFkdApzhl+NLlFXV9lChoBmgJaA9DCN4+q8yU1gHAlIaUUpRoFUsyaBZHQKc6OKZ2IO91fZQoaAZoCWgPQwhYjpCBPHsHwJSGlFKUaBVLMmgWR0CnOf7TtsvadX2UKGgGaAloD0MIUvNV8rFbDcCUhpRSlGgVSzJoFkdApznGQp4KQnV9lChoBmgJaA9DCLIrLSP1fgTAlIaUUpRoFUsyaBZHQKc5U7cO9WZ1fZQoaAZoCWgPQwikx+9t+rMBwJSGlFKUaBVLMmgWR0CnOyeF10T2dX2UKGgGaAloD0MICkrRyr1gAMCUhpRSlGgVSzJoFkdApzrtW4mTknV9lChoBmgJaA9DCBuDTggdtPu/lIaUUpRoFUsyaBZHQKc6tMTviLl1fZQoaAZoCWgPQwhbCd0lcTYBwJSGlFKUaBVLMmgWR0CnOkJqqOtGdX2UKGgGaAloD0MIgCvZsREIAsCUhpRSlGgVSzJoFkdApzwaKiwjdHV9lChoBmgJaA9DCErrbwnAf/q/lIaUUpRoFUsyaBZHQKc74Elme191fZQoaAZoCWgPQwiXb31Yb1QHwJSGlFKUaBVLMmgWR0CnO6fIjnmrdX2UKGgGaAloD0MII04n2eoSCcCUhpRSlGgVSzJoFkdApzs1lf7aZnV9lChoBmgJaA9DCM10r5P6cv6/lIaUUpRoFUsyaBZHQKc9CoXsPat1fZQoaAZoCWgPQwgUd7zJbxEHwJSGlFKUaBVLMmgWR0CnPNCa7VawdX2UKGgGaAloD0MI8tO4N7+hB8CUhpRSlGgVSzJoFkdApzyYA80UGnV9lChoBmgJaA9DCFZ9rrZifwTAlIaUUpRoFUsyaBZHQKc8JYtg8bJ1fZQoaAZoCWgPQwhTBg5o6UoJwJSGlFKUaBVLMmgWR0CnPf3Y+Sr6dX2UKGgGaAloD0MIeAq5Us/CCMCUhpRSlGgVSzJoFkdApz3ECA+Y+nV9lChoBmgJaA9DCBXhJqPKsP+/lIaUUpRoFUsyaBZHQKc9i2iL2pR1fZQoaAZoCWgPQwjaHr3hPlIBwJSGlFKUaBVLMmgWR0CnPRjwx33YdX2UKGgGaAloD0MIwJSBA1r6AsCUhpRSlGgVSzJoFkdApz87IV/MGHV9lChoBmgJaA9DCDVFgNO7OAXAlIaUUpRoFUsyaBZHQKc/ActoSL91fZQoaAZoCWgPQwjJcad0sP4EwJSGlFKUaBVLMmgWR0CnPsk8ifQKdX2UKGgGaAloD0MIiLg5lQyABcCUhpRSlGgVSzJoFkdApz5XoHLRr3V9lChoBmgJaA9DCH3ogvqW+QTAlIaUUpRoFUsyaBZHQKdAa3BpHqh1fZQoaAZoCWgPQwjmXfWAeegFwJSGlFKUaBVLMmgWR0CnQDIaDPGAdX2UKGgGaAloD0MIPKQYINGEBMCUhpRSlGgVSzJoFkdApz/5e/pMYnV9lChoBmgJaA9DCAckYd9OYgLAlIaUUpRoFUsyaBZHQKc/hx0dRzl1fZQoaAZoCWgPQwhmTwKbc5AKwJSGlFKUaBVLMmgWR0CnQVaVD8cddX2UKGgGaAloD0MIxsTm49owA8CUhpRSlGgVSzJoFkdAp0EciUxEfHV9lChoBmgJaA9DCHQoQ1VMpfu/lIaUUpRoFUsyaBZHQKdA5AvcrRV1fZQoaAZoCWgPQwilvFZCd4kEwJSGlFKUaBVLMmgWR0CnQHGO+7DmdX2UKGgGaAloD0MIlbVN8bioA8CUhpRSlGgVSzJoFkdAp0JqQ7tAs3V9lChoBmgJaA9DCGyzsRLzjAfAlIaUUpRoFUsyaBZHQKdCMBfa6Bl1fZQoaAZoCWgPQwgMeJlhoywFwJSGlFKUaBVLMmgWR0CnQfhU70WedX2UKGgGaAloD0MIC3+GN2uQBcCUhpRSlGgVSzJoFkdAp0GGB4D9wXV9lChoBmgJaA9DCHF1AMRdHQbAlIaUUpRoFUsyaBZHQKdDf1B+nZV1fZQoaAZoCWgPQwhPWriswoYAwJSGlFKUaBVLMmgWR0CnQ0UhmoR7dX2UKGgGaAloD0MIsBwhA3lWCcCUhpRSlGgVSzJoFkdAp0MMnJDE33V9lChoBmgJaA9DCMtN1NLcCgfAlIaUUpRoFUsyaBZHQKdCml0HQhR1fZQoaAZoCWgPQwgzNJ4I4pwIwJSGlFKUaBVLMmgWR0CnRIOn/DLsdX2UKGgGaAloD0MIs9E5P8URBsCUhpRSlGgVSzJoFkdAp0RJvFWGRHV9lChoBmgJaA9DCIe/JmvUIwPAlIaUUpRoFUsyaBZHQKdEEQfZElV1fZQoaAZoCWgPQwgmAP+UKjEFwJSGlFKUaBVLMmgWR0CnQ56Ieo1ldX2UKGgGaAloD0MIRQ4RN6dSAsCUhpRSlGgVSzJoFkdAp0VrEm6XjXV9lChoBmgJaA9DCPewFwrYDgDAlIaUUpRoFUsyaBZHQKdFMPeYUnJ1fZQoaAZoCWgPQwic3sX7cVsOwJSGlFKUaBVLMmgWR0CnRPh2GIsRdX2UKGgGaAloD0MIp0HRPIDlBMCUhpRSlGgVSzJoFkdAp0SF9fCyhXV9lChoBmgJaA9DCJdTAmIS7gjAlIaUUpRoFUsyaBZHQKdGa1YQrc11fZQoaAZoCWgPQwifIoeImxMAwJSGlFKUaBVLMmgWR0CnRjE9U0emdX2UKGgGaAloD0MIGXCWkuXUEcCUhpRSlGgVSzJoFkdAp0X440dilXV9lChoBmgJaA9DCOWzPA/uLgXAlIaUUpRoFUsyaBZHQKdFhpqREF51fZQoaAZoCWgPQwjZCMTr+gX9v5SGlFKUaBVLMmgWR0CnR3YsVclgdX2UKGgGaAloD0MI4j0HliOk/b+UhpRSlGgVSzJoFkdAp0c8M7U5MnV9lChoBmgJaA9DCMqpnWFqywLAlIaUUpRoFUsyaBZHQKdHA80UGml1fZQoaAZoCWgPQwj4ONOE7ecGwJSGlFKUaBVLMmgWR0CnRpIpQUHqdX2UKGgGaAloD0MIGH0FacaCBsCUhpRSlGgVSzJoFkdAp0hbHp8neHV9lChoBmgJaA9DCLPNjekJiwTAlIaUUpRoFUsyaBZHQKdIIPjn3cp1fZQoaAZoCWgPQwgqyM9GrpsEwJSGlFKUaBVLMmgWR0CnR+hXKbKBdX2UKGgGaAloD0MIHy457pSO/b+UhpRSlGgVSzJoFkdAp0d125hBq3V9lChoBmgJaA9DCE65wrtcpALAlIaUUpRoFUsyaBZHQKdJYR7JGON1fZQoaAZoCWgPQwgkfzDw3NsHwJSGlFKUaBVLMmgWR0CnSScBltj1dX2UKGgGaAloD0MI9L9cixYgAMCUhpRSlGgVSzJoFkdAp0jucriEQHV9lChoBmgJaA9DCKGi6lc6PwLAlIaUUpRoFUsyaBZHQKdIfACW/rV1fZQoaAZoCWgPQwh5dY4B2QsHwJSGlFKUaBVLMmgWR0CnSk6Mir1edX2UKGgGaAloD0MIbK8FvTemB8CUhpRSlGgVSzJoFkdAp0oUZUDMeXV9lChoBmgJaA9DCOJWQQx0bQbAlIaUUpRoFUsyaBZHQKdJ289Oh011fZQoaAZoCWgPQwgDBkmfVpEKwJSGlFKUaBVLMmgWR0CnSWlE7W/bdX2UKGgGaAloD0MI9mIoJ9r1BsCUhpRSlGgVSzJoFkdAp0uVbs4T9XV9lChoBmgJaA9DCIjVH2EYMP2/lIaUUpRoFUsyaBZHQKdLW9lEqlR1fZQoaAZoCWgPQwjVXdkFgwsDwJSGlFKUaBVLMmgWR0CnSyO3MINWdX2UKGgGaAloD0MIiudsAaH1A8CUhpRSlGgVSzJoFkdAp0qxwGW2PXV9lChoBmgJaA9DCJFgqpm1NAXAlIaUUpRoFUsyaBZHQKdNEki2Ujd1fZQoaAZoCWgPQwhhM8AF2dIHwJSGlFKUaBVLMmgWR0CnTNim/FisdX2UKGgGaAloD0MITrNAu0PKCcCUhpRSlGgVSzJoFkdAp0ygr1/UfHV9lChoBmgJaA9DCAqGcw0zNP+/lIaUUpRoFUsyaBZHQKdMLsmfGuN1fZQoaAZoCWgPQwguymyQSQb+v5SGlFKUaBVLMmgWR0CnTpBwl0HRdX2UKGgGaAloD0MI0QX1LXOaDMCUhpRSlGgVSzJoFkdAp05W9+PRzHV9lChoBmgJaA9DCDuoxHWMa/q/lIaUUpRoFUsyaBZHQKdOHy/bj951fZQoaAZoCWgPQwhNMJxrmKEDwJSGlFKUaBVLMmgWR0CnTa07r9l3dX2UKGgGaAloD0MIQYF38ukxDMCUhpRSlGgVSzJoFkdAp1Azlo11n3V9lChoBmgJaA9DCLUaEvdY+v+/lIaUUpRoFUsyaBZHQKdP+o+fRNR1fZQoaAZoCWgPQwgJM23/ysr7v5SGlFKUaBVLMmgWR0CnT8KrBCUpdX2UKGgGaAloD0MIAhHiytl7A8CUhpRSlGgVSzJoFkdAp09RYDDCQHV9lChoBmgJaA9DCLx4P26/XADAlIaUUpRoFUsyaBZHQKdSHbaAWi11fZQoaAZoCWgPQwjtR4rIsEr+v5SGlFKUaBVLMmgWR0CnUeR1X/5tdX2UKGgGaAloD0MIforjwKuFAMCUhpRSlGgVSzJoFkdAp1GsfJV81HV9lChoBmgJaA9DCFWKHY1DnQvAlIaUUpRoFUsyaBZHQKdROys0YTF1ZS4="}, "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. -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, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
|
|
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 0x7f3e97bc9090>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3e97bd1440>"}, "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": 398580, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685238426526340815, "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": "[[-0.7917432 0.03803741 -0.4598822 ]\n [-0.3593167 0.25153124 0.05122437]\n [-0.1393069 -0.10529448 -0.5856322 ]\n [ 0.786882 -0.0484037 -0.755384 ]]", "desired_goal": "[[-1.0225276 -0.11311968 -0.61802536]\n [-0.5885794 0.2863355 -0.2553675 ]\n [-0.34455928 -0.4958089 -1.0230689 ]\n [ 0.9293512 -0.20871052 -1.4284213 ]]", "observation": "[[-0.7917432 0.03803741 -0.4598822 1.4324336 0.90027636 0.12019604]\n [-0.3593167 0.25153124 0.05122437 0.56592625 1.4030783 -0.14862114]\n [-0.1393069 -0.10529448 -0.5856322 -0.98399276 -0.2993722 -0.4350289 ]\n [ 0.786882 -0.0484037 -0.755384 -0.02299824 0.24331403 0.08272691]]"}, "_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": "[[-0.10580213 0.03239889 0.22969934]\n [-0.04433484 -0.00617912 0.09831697]\n [-0.02869451 -0.00102089 0.10868603]\n [ 0.14143941 -0.01827629 0.22064818]]", "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": 0.6014200000000001, "_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": 19928, "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. -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, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward": -2.
|
|
|
1 |
+
{"mean_reward": -2.6901352528482674, "std_reward": 1.0320701849363325, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-28T02:07:05.112147"}
|
vec_normalize.pkl
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 2387
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0a9a63c88d2d7520ef529986cc7a1c30a1fdd52746c32910d137ccc481989de2
|
3 |
size 2387
|