Commit
•
ed5b554
1
Parent(s):
69e946f
Second commit - 2M ts
Browse files- README.md +1 -1
- a2c-PandaReachDense-v2.zip +1 -1
- a2c-PandaReachDense-v2/data +10 -10
- a2c-PandaReachDense-v2/policy.optimizer.pth +1 -1
- a2c-PandaReachDense-v2/policy.pth +1 -1
- a2c-PandaReachDense-v2/system_info.txt +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: -
|
| 20 |
name: mean_reward
|
| 21 |
verified: false
|
| 22 |
---
|
|
|
|
| 16 |
type: PandaReachDense-v2
|
| 17 |
metrics:
|
| 18 |
- type: mean_reward
|
| 19 |
+
value: -3.22 +/- 1.37
|
| 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 108075
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ed448b97dbc42e375f52169c68b1acc227fd9bff093b1980dee47a00a76e36b4
|
| 3 |
size 108075
|
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": {
|
|
@@ -24,7 +24,7 @@
|
|
| 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": "[[
|
| 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:": "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": "[[ 0.
|
| 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,
|
|
@@ -56,7 +56,7 @@
|
|
| 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'>",
|
|
|
|
| 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 0x7f25530d0e50>",
|
| 8 |
"__abstractmethods__": "frozenset()",
|
| 9 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f25530c6240>"
|
| 10 |
},
|
| 11 |
"verbose": 1,
|
| 12 |
"policy_kwargs": {
|
|
|
|
| 24 |
"_num_timesteps_at_start": 0,
|
| 25 |
"seed": null,
|
| 26 |
"action_noise": null,
|
| 27 |
+
"start_time": 1684959987658271354,
|
| 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": "[[ 0.37271252 -0.00131458 0.5936312 ]\n [ 0.37271252 -0.00131458 0.5936312 ]\n [ 0.37271252 -0.00131458 0.5936312 ]\n [ 0.37271252 -0.00131458 0.5936312 ]]",
|
| 38 |
+
"desired_goal": "[[ 1.4499166 -0.31920213 0.8988662 ]\n [-0.14948227 -1.6009928 -0.5299277 ]\n [ 1.0999999 1.4198424 1.5894455 ]\n [-0.10941627 -1.3784939 -0.59898233]]",
|
| 39 |
+
"observation": "[[ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]\n [ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]\n [ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]\n [ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]]"
|
| 40 |
},
|
| 41 |
"_last_episode_starts": {
|
| 42 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
|
| 44 |
},
|
| 45 |
"_last_original_obs": {
|
| 46 |
":type:": "<class 'collections.OrderedDict'>",
|
| 47 |
+
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAkazeO+db0rxEmQI+xmYjPZAcBj7WL308Wm6mvKVDsrxfWlo9xuD7PXTI0T3FDGs+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==",
|
| 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": "[[ 0.00679547 -0.02567859 0.12753779]\n [ 0.03989293 0.13096833 0.0154533 ]\n [-0.02031629 -0.02176077 0.05330884]\n [ 0.12298732 0.10243312 0.2295409 ]]",
|
| 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,
|
|
|
|
| 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'>",
|
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 sha256:936af21c5ad03ba2db60b50d45b427d50804f995df6311c3531d27e8f49eb575
|
| 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:d6c556ca781e659b4d178e19472685a69dfba8f4aad320c41c6e170b9294e655
|
| 3 |
size 46014
|
a2c-PandaReachDense-v2/system_info.txt
CHANGED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
- OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
|
| 2 |
- Python: 3.10.11
|
| 3 |
- Stable-Baselines3: 1.8.0
|
| 4 |
-
- PyTorch: 2.0.
|
| 5 |
- GPU Enabled: True
|
| 6 |
- Numpy: 1.22.4
|
| 7 |
- Gym: 0.21.0
|
|
|
|
| 1 |
- OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
|
| 2 |
- Python: 3.10.11
|
| 3 |
- Stable-Baselines3: 1.8.0
|
| 4 |
+
- PyTorch: 2.0.1+cu118
|
| 5 |
- GPU Enabled: True
|
| 6 |
- Numpy: 1.22.4
|
| 7 |
- Gym: 0.21.0
|
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 0x7efde1aab2e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efde1aa33c0>"}, "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": 1684364131418704565, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA8frSPvYIu7xN7Ak/8frSPvYIu7xN7Ak/8frSPvYIu7xN7Ak/8frSPvYIu7xN7Ak/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAbp63v6n9PL4fi0q/GvWTvw8ySD9yclC+CZWbv+WbsL84wky/+d2dvxKhRL8c68k/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADx+tI+9gi7vE3sCT8lJg28VoG0uxksorzx+tI+9gi7vE3sCT8lJg28VoG0uxksorzx+tI+9gi7vE3sCT8lJg28VoG0uxksorzx+tI+9gi7vE3sCT8lJg28VoG0uxksoryUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[ 0.41207078 -0.02283142 0.5387619 ]\n [ 0.41207078 -0.02283142 0.5387619 ]\n [ 0.41207078 -0.02283142 0.5387619 ]\n [ 0.41207078 -0.02283142 0.5387619 ]]", "desired_goal": "[[-1.4345224 -0.18456139 -0.7911853 ]\n [-1.1559174 0.78201383 -0.20356157]\n [-1.2154857 -1.3797575 -0.79983854]\n [-1.2333366 -0.76808274 1.5774875 ]]", "observation": "[[ 0.41207078 -0.02283142 0.5387619 -0.00861505 -0.00550858 -0.01979642]\n [ 0.41207078 -0.02283142 0.5387619 -0.00861505 -0.00550858 -0.01979642]\n [ 0.41207078 -0.02283142 0.5387619 -0.00861505 -0.00550858 -0.01979642]\n [ 0.41207078 -0.02283142 0.5387619 -0.00861505 -0.00550858 -0.01979642]]"}, "_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": "[[ 0.00598914 -0.10426455 0.06216688]\n [ 0.01177075 -0.0703738 0.14957182]\n [-0.12384964 0.00580514 0.2545865 ]\n [ 0.1462399 0.10175581 0.27821288]]", "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 '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": "2.0.0+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 0x7f25530d0e50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f25530c6240>"}, "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": 1684959987658271354, "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": "[[ 0.37271252 -0.00131458 0.5936312 ]\n [ 0.37271252 -0.00131458 0.5936312 ]\n [ 0.37271252 -0.00131458 0.5936312 ]\n [ 0.37271252 -0.00131458 0.5936312 ]]", "desired_goal": "[[ 1.4499166 -0.31920213 0.8988662 ]\n [-0.14948227 -1.6009928 -0.5299277 ]\n [ 1.0999999 1.4198424 1.5894455 ]\n [-0.10941627 -1.3784939 -0.59898233]]", "observation": "[[ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]\n [ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]\n [ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]\n [ 0.37271252 -0.00131458 0.5936312 -0.0082049 0.00135293 0.00128543]]"}, "_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": "[[ 0.00679547 -0.02567859 0.12753779]\n [ 0.03989293 0.13096833 0.0154533 ]\n [-0.02031629 -0.02176077 0.05330884]\n [ 0.12298732 0.10243312 0.2295409 ]]", "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 'gym.spaces.dict.Dict'>", ":serialized:": "gAWVWAMAAAAAAACMD2d5bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwOZ3ltLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowGX3NoYXBllEsDhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZSMAUOUdJRSlIwEaGlnaJRoHiiWDAAAAAAAAAAAACBBAAAgQQAAIEGUaBZLA4WUaCF0lFKUjA1ib3VuZGVkX2JlbG93lGgeKJYDAAAAAAAAAAEBAZRoE4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZRoIXSUUpSMDWJvdW5kZWRfYWJvdmWUaB4olgMAAAAAAAAAAQEBlGgtSwOFlGghdJRSlIwKX25wX3JhbmRvbZROdWKMDGRlc2lyZWRfZ29hbJRoDSmBlH2UKGgQaBZoGUsDhZRoG2geKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZRoIXSUUpRoJGgeKJYMAAAAAAAAAAAAIEEAACBBAAAgQZRoFksDhZRoIXSUUpRoKWgeKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoM2geKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoOE51YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgWaBlLBoWUaBtoHiiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBZLBoWUaCF0lFKUaCRoHiiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBZLBoWUaCF0lFKUaCloHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDNoHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDhOdWJ1aBlOaBBOaDhOdWIu", "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": -
|
|
|
|
| 1 |
+
{"mean_reward": -3.2230469621252267, "std_reward": 1.3743468145456417, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-24T21:13:56.071632"}
|
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:c414f56a138e003a5db6e644a31bc31feef6488144a315fb724eca93330bc67f
|
| 3 |
size 2387
|