Initial commit
Browse files- README.md +1 -1
- a2c-PandaReachDense-v2.zip +2 -2
- 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: -7.75 +/- 1.93
|
| 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:c0ca5b3e5cc116454ab5823f336a6f8739604ce0f5a607a51c2f619d1ec0b586
|
| 3 |
+
size 108063
|
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": "[[
|
| 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:": "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,
|
|
@@ -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 0x7bcaca017910>",
|
| 8 |
"__abstractmethods__": "frozenset()",
|
| 9 |
+
"_abc_impl": "<_abc._abc_data object at 0x7bcaca020480>"
|
| 10 |
},
|
| 11 |
"verbose": 1,
|
| 12 |
"policy_kwargs": {
|
|
|
|
| 24 |
"_num_timesteps_at_start": 0,
|
| 25 |
"seed": null,
|
| 26 |
"action_noise": null,
|
| 27 |
+
"start_time": 1691048232684024790,
|
| 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": "[[0.39329225 0.04135285 0.59164536]\n [0.39329225 0.04135285 0.59164536]\n [0.39329225 0.04135285 0.59164536]\n [0.39329225 0.04135285 0.59164536]]",
|
| 38 |
+
"desired_goal": "[[ 1.3044721 -0.8574187 0.6927346 ]\n [ 1.4345902 -0.15178438 -1.3799636 ]\n [ 1.0767852 -0.95247847 -0.7473735 ]\n [ 1.7298151 0.44143802 1.4457214 ]]",
|
| 39 |
+
"observation": "[[ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]\n [ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]\n [ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]\n [ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]]"
|
| 40 |
},
|
| 41 |
"_last_episode_starts": {
|
| 42 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
|
| 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": "[[ 0.12142542 0.0686857 0.21043752]\n [ 0.00212321 0.13497485 0.05596958]\n [-0.13589033 0.05026526 0.28146484]\n [ 0.12360299 -0.13591366 0.05767013]]",
|
| 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 sha256:3d9c767ed2d6d43d307c2e0df5bfd5ba0b618ac62c08c977ebe2e9978bca400a
|
| 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:b6c318646f97a275b0ed7d55cc7fd04389718fa113bb2d71e6ff26cd8cde7951
|
| 3 |
size 46014
|
a2c-PandaReachDense-v2/system_info.txt
CHANGED
|
@@ -1,4 +1,4 @@
|
|
| 1 |
-
- OS: Linux-5.15.
|
| 2 |
- Python: 3.10.12
|
| 3 |
- Stable-Baselines3: 1.8.0
|
| 4 |
- PyTorch: 2.0.1+cu118
|
|
|
|
| 1 |
+
- OS: Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
|
| 2 |
- Python: 3.10.12
|
| 3 |
- Stable-Baselines3: 1.8.0
|
| 4 |
- PyTorch: 2.0.1+cu118
|
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 0x7f8bda7ee5f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f8bda7eb000>"}, "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": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688870218854478903, "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": "[[ 0.42987752 -0.04119119 0.72185564]\n [ 0.42987752 -0.04119119 0.72185564]\n [ 0.42987752 -0.04119119 0.72185564]\n [ 0.42987752 -0.04119119 0.72185564]]", "desired_goal": "[[ 1.6291444 -1.2046227 -0.80983675]\n [ 0.6936555 1.0977286 -0.4221621 ]\n [-0.00390983 -1.5806466 -0.73895806]\n [-0.25780112 0.21010968 -0.24638748]]", "observation": "[[ 0.42987752 -0.04119119 0.72185564 0.00362608 -0.00776813 0.0154424 ]\n [ 0.42987752 -0.04119119 0.72185564 0.00362608 -0.00776813 0.0154424 ]\n [ 0.42987752 -0.04119119 0.72185564 0.00362608 -0.00776813 0.0154424 ]\n [ 0.42987752 -0.04119119 0.72185564 0.00362608 -0.00776813 0.0154424 ]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAP107vbvejr0KLKc94/17PdbJvzzSIOU9+ArgPQD1rD3fw3c+1oV8vaOUAr6nCYA+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[-0.04574322 -0.06976076 0.08162697]\n [ 0.06152142 0.02341167 0.11187901]\n [ 0.10939592 0.08445168 0.24195813]\n [-0.06165107 -0.12752013 0.25007364]]", "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": 100000, "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": "3.10.12", "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 0x7bcaca017910>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bcaca020480>"}, "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": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1691048232684024790, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAml3JPpxhKT0Sdhc/ml3JPpxhKT0Sdhc/ml3JPpxhKT0Sdhc/ml3JPpxhKT0Sdhc/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA8fimP8t/W78OVzE/p6C3P11tG76morC/GdSJP6HVc7/fUz+/lWrdPyoE4j5mDbk/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAACaXck+nGEpPRJ2Fz9px9k7kEwQu9bzuzyaXck+nGEpPRJ2Fz9px9k7kEwQu9bzuzyaXck+nGEpPRJ2Fz9px9k7kEwQu9bzuzyaXck+nGEpPRJ2Fz9px9k7kEwQu9bzuzyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.39329225 0.04135285 0.59164536]\n [0.39329225 0.04135285 0.59164536]\n [0.39329225 0.04135285 0.59164536]\n [0.39329225 0.04135285 0.59164536]]", "desired_goal": "[[ 1.3044721 -0.8574187 0.6927346 ]\n [ 1.4345902 -0.15178438 -1.3799636 ]\n [ 1.0767852 -0.95247847 -0.7473735 ]\n [ 1.7298151 0.44143802 1.4457214 ]]", "observation": "[[ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]\n [ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]\n [ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]\n [ 0.39329225 0.04135285 0.59164536 0.00664609 -0.00220183 0.02294342]]"}, "_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": "[[ 0.12142542 0.0686857 0.21043752]\n [ 0.00212321 0.13497485 0.05596958]\n [-0.13589033 0.05026526 0.28146484]\n [ 0.12360299 -0.13591366 0.05767013]]", "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////9LAHSUYkMIUInrGFeMFcCUhpRSlIwBbJRLMowBdJRHQLZlDva11GN1fZQoaAZoCWgPQwgK+DWSBKEUwJSGlFKUaBVLMmgWR0C2ZO6kM1CPdX2UKGgGaAloD0MIQkEpWrkHGsCUhpRSlGgVSzJoFkdAtmTN6iTMaHV9lChoBmgJaA9DCFLVBFH3gRfAlIaUUpRoFUsyaBZHQLZkrSzgMtt1fZQoaAZoCWgPQwjAsPz5tlASwJSGlFKUaBVLMmgWR0C2ZYPHDJlrdX2UKGgGaAloD0MIJ4V5jzP9E8CUhpRSlGgVSzJoFkdAtmVjgR9PUXV9lChoBmgJaA9DCIPfhhivmQvAlIaUUpRoFUsyaBZHQLZlQq+8Gs51fZQoaAZoCWgPQwjXM4RjlvUgwJSGlFKUaBVLMmgWR0C2ZSHhjvuxdX2UKGgGaAloD0MIeedQhqpYFMCUhpRSlGgVSzJoFkdAtmYOtKZlWnV9lChoBmgJaA9DCNds5SX/AxbAlIaUUpRoFUsyaBZHQLZl7nJ1aGJ1fZQoaAZoCWgPQwiuZMdGIM4QwJSGlFKUaBVLMmgWR0C2Zc4msvIwdX2UKGgGaAloD0MI/WfNj78UCsCUhpRSlGgVSzJoFkdAtmWtV5rxiHV9lChoBmgJaA9DCIPcRZii/BfAlIaUUpRoFUsyaBZHQLZmhy7PIGR1fZQoaAZoCWgPQwjXh/VGrfgiwJSGlFKUaBVLMmgWR0C2ZmbVOKwZdX2UKGgGaAloD0MIb2dfeZCOGcCUhpRSlGgVSzJoFkdAtmZF8CxNZnV9lChoBmgJaA9DCLH4TWGlYiHAlIaUUpRoFUsyaBZHQLZmJSjQAuJ1fZQoaAZoCWgPQwg1DB8RU5IfwJSGlFKUaBVLMmgWR0C2ZvpkbxVidX2UKGgGaAloD0MIfbPNjekZFcCUhpRSlGgVSzJoFkdAtmbaDaoMrnV9lChoBmgJaA9DCIif/x681gvAlIaUUpRoFUsyaBZHQLZmuTV2A5J1fZQoaAZoCWgPQwizeLEwRF4XwJSGlFKUaBVLMmgWR0C2Zph0+1SgdX2UKGgGaAloD0MIkGYsms6OFsCUhpRSlGgVSzJoFkdAtmeI4MnZ03V9lChoBmgJaA9DCNtrQe+N4RPAlIaUUpRoFUsyaBZHQLZnaIf8uSR1fZQoaAZoCWgPQwhy3ZTyWtkRwJSGlFKUaBVLMmgWR0C2Z0gl0HQhdX2UKGgGaAloD0MI+grSjEV7IMCUhpRSlGgVSzJoFkdAtmcnVz6rNnV9lChoBmgJaA9DCHeiJCTSxhDAlIaUUpRoFUsyaBZHQLZn/8XvYvp1fZQoaAZoCWgPQwj61RwgmBMRwJSGlFKUaBVLMmgWR0C2Z9+MMqjKdX2UKGgGaAloD0MIlG3gDtRJE8CUhpRSlGgVSzJoFkdAtme+t/4Ir3V9lChoBmgJaA9DCEIkQ46tBxPAlIaUUpRoFUsyaBZHQLZnnfdAPd51fZQoaAZoCWgPQwjX3TzVITcVwJSGlFKUaBVLMmgWR0C2aHV8CxNZdX2UKGgGaAloD0MI6L8Hr10qEMCUhpRSlGgVSzJoFkdAtmhVKbrkbXV9lChoBmgJaA9DCHuFBfcDDhzAlIaUUpRoFUsyaBZHQLZoNEi+tbN1fZQoaAZoCWgPQwjBG9KowFkawJSGlFKUaBVLMmgWR0C2aBOVgQYldX2UKGgGaAloD0MIgoyACkcAF8CUhpRSlGgVSzJoFkdAtmj8Bfa6BnV9lChoBmgJaA9DCDbLZaNz3grAlIaUUpRoFUsyaBZHQLZo3BbOeJ51fZQoaAZoCWgPQwjOVIhH4pUTwJSGlFKUaBVLMmgWR0C2aLs495hSdX2UKGgGaAloD0MI6IcRwqOtFMCUhpRSlGgVSzJoFkdAtmiadpZfUnV9lChoBmgJaA9DCAGjy5vDhRTAlIaUUpRoFUsyaBZHQLZpbzd1uBN1fZQoaAZoCWgPQwijA5Kwb6cXwJSGlFKUaBVLMmgWR0C2aU7fHggpdX2UKGgGaAloD0MIbD6uDRUTFcCUhpRSlGgVSzJoFkdAtmkuDRMN+nV9lChoBmgJaA9DCBEY6xuY/BHAlIaUUpRoFUsyaBZHQLZpDVdX1ap1fZQoaAZoCWgPQwjvx+2XT0YTwJSGlFKUaBVLMmgWR0C2affwqiGndX2UKGgGaAloD0MIdH6K48ArBcCUhpRSlGgVSzJoFkdAtmnYF3Y+S3V9lChoBmgJaA9DCLGmsijsgh7AlIaUUpRoFUsyaBZHQLZpt1VHWjJ1fZQoaAZoCWgPQwhVouwt5bwYwJSGlFKUaBVLMmgWR0C2aZa7ROUMdX2UKGgGaAloD0MIoMTnTrB/EcCUhpRSlGgVSzJoFkdAtmp2dQO4G3V9lChoBmgJaA9DCC0FpP0PkBHAlIaUUpRoFUsyaBZHQLZqVkpZwGZ1fZQoaAZoCWgPQwh+calKW3wawJSGlFKUaBVLMmgWR0C2ajVtTDO1dX2UKGgGaAloD0MI7kCd8uhGIMCUhpRSlGgVSzJoFkdAtmoUpe/pMnV9lChoBmgJaA9DCBR2UfTAFyLAlIaUUpRoFUsyaBZHQLZq7r6tT1l1fZQoaAZoCWgPQwiIhVrTvOMcwJSGlFKUaBVLMmgWR0C2as6Zc9nsdX2UKGgGaAloD0MILlbUYBq2FsCUhpRSlGgVSzJoFkdAtmqtwNsnA3V9lChoBmgJaA9DCAd+VMN+vxfAlIaUUpRoFUsyaBZHQLZqjQOnVG11fZQoaAZoCWgPQwg7GRwlr14SwJSGlFKUaBVLMmgWR0C2a3ewTufFdX2UKGgGaAloD0MIEHnL1Y8NH8CUhpRSlGgVSzJoFkdAtmtXzQNTcnV9lChoBmgJaA9DCLCvdakRGhTAlIaUUpRoFUsyaBZHQLZrNv0AcT91fZQoaAZoCWgPQwjeHRmrza8QwJSGlFKUaBVLMmgWR0C2axZE2HcldX2UKGgGaAloD0MIBb8NMV6DHMCUhpRSlGgVSzJoFkdAtmvkZzgdfnV9lChoBmgJaA9DCIfFqGvtvRjAlIaUUpRoFUsyaBZHQLZrxCTlkpZ1fZQoaAZoCWgPQwiufmySH2EUwJSGlFKUaBVLMmgWR0C2a6NQ40djdX2UKGgGaAloD0MIkiOdgZFHFcCUhpRSlGgVSzJoFkdAtmuCjgydnXV9lChoBmgJaA9DCAPso1NXfhLAlIaUUpRoFUsyaBZHQLZsXmKZUkx1fZQoaAZoCWgPQwgyryMO2eATwJSGlFKUaBVLMmgWR0C2bD4QJ5VwdX2UKGgGaAloD0MIWeAruvXqF8CUhpRSlGgVSzJoFkdAtmwdRceKbnV9lChoBmgJaA9DCLWoT3KH7RrAlIaUUpRoFUsyaBZHQLZr/JIDoyN1fZQoaAZoCWgPQwh3gv3XubkTwJSGlFKUaBVLMmgWR0C2bNcTFl06dX2UKGgGaAloD0MIQkP/BBfLGcCUhpRSlGgVSzJoFkdAtmy2v5gw5HV9lChoBmgJaA9DCLUy4Zf6ASDAlIaUUpRoFUsyaBZHQLZslevpyIZ1fZQoaAZoCWgPQwjtKM5RR3cTwJSGlFKUaBVLMmgWR0C2bHUofCAMdX2UKGgGaAloD0MIc9cS8kH/FsCUhpRSlGgVSzJoFkdAtm1Lyz5XVHV9lChoBmgJaA9DCEzirIiaeBjAlIaUUpRoFUsyaBZHQLZtK4OMERt1fZQoaAZoCWgPQwifIRyz7GkdwJSGlFKUaBVLMmgWR0C2bQqrzXjEdX2UKGgGaAloD0MIUg37PbHOFMCUhpRSlGgVSzJoFkdAtmzp7D2rXHV9lChoBmgJaA9DCNIA3gIJShXAlIaUUpRoFUsyaBZHQLZtwUIcBEN1fZQoaAZoCWgPQwihv9AjRr8VwJSGlFKUaBVLMmgWR0C2baD2rXDndX2UKGgGaAloD0MINlfNc0QuKMCUhpRSlGgVSzJoFkdAtm2AGHHmzXV9lChoBmgJaA9DCF5jl6jeihTAlIaUUpRoFUsyaBZHQLZtX18b70p1fZQoaAZoCWgPQwg7GRwlr54ewJSGlFKUaBVLMmgWR0C2bjgs9SuRdX2UKGgGaAloD0MIH54lyAjgIcCUhpRSlGgVSzJoFkdAtm4X36AOKHV9lChoBmgJaA9DCIhM+RBUXR7AlIaUUpRoFUsyaBZHQLZt929L6DZ1fZQoaAZoCWgPQwijyjDuBiEYwJSGlFKUaBVLMmgWR0C2bdacNH6NdX2UKGgGaAloD0MImrUUkPbfC8CUhpRSlGgVSzJoFkdAtm7zps41g3V9lChoBmgJaA9DCGXkLOxpVxfAlIaUUpRoFUsyaBZHQLZu089wFTx1fZQoaAZoCWgPQwj0biwoDGoWwJSGlFKUaBVLMmgWR0C2brOj/MnrdX2UKGgGaAloD0MIZf1mYrrgHMCUhpRSlGgVSzJoFkdAtm6TFglWwXV9lChoBmgJaA9DCOZbH9YbJRLAlIaUUpRoFUsyaBZHQLZvucpb2UV1fZQoaAZoCWgPQwgGS3UBL9MYwJSGlFKUaBVLMmgWR0C2b5nDvVmSdX2UKGgGaAloD0MI3+F2aFiUIcCUhpRSlGgVSzJoFkdAtm95RCQcP3V9lChoBmgJaA9DCBy0Vx8PTRjAlIaUUpRoFUsyaBZHQLZvWL0jC551fZQoaAZoCWgPQwgJwap6+X0WwJSGlFKUaBVLMmgWR0C2cHZIlMRIdX2UKGgGaAloD0MIc7hWe9j7HsCUhpRSlGgVSzJoFkdAtnBWb5M10nV9lChoBmgJaA9DCN/7G7RXPxjAlIaUUpRoFUsyaBZHQLZwNlsxfv51fZQoaAZoCWgPQwjOwTOhSaIXwJSGlFKUaBVLMmgWR0C2cBX27FsIdX2UKGgGaAloD0MIeCefHtsCIMCUhpRSlGgVSzJoFkdAtnE5ODaoM3V9lChoBmgJaA9DCE7udygKxBfAlIaUUpRoFUsyaBZHQLZxGUoKD011fZQoaAZoCWgPQwiWBn5Uw/4XwJSGlFKUaBVLMmgWR0C2cPjd1uBMdX2UKGgGaAloD0MI2Lyqs1ogIcCUhpRSlGgVSzJoFkdAtnDYiUxEfHV9lChoBmgJaA9DCH/4+e/Bmx/AlIaUUpRoFUsyaBZHQLZx7vZyuIR1fZQoaAZoCWgPQwi+ZrlsdO4ZwJSGlFKUaBVLMmgWR0C2cc6yv9tNdX2UKGgGaAloD0MI8KKvIM0IFsCUhpRSlGgVSzJoFkdAtnGt0gbIcXV9lChoBmgJaA9DCHAJwD+l0iLAlIaUUpRoFUsyaBZHQLZxjSUC7sh1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 100000, "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "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": -7.753159415535629, "std_reward": 1.9323980692626028, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-03T09:34:58.767445"}
|
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 sha256:4409f6c783d19441f66c4ee8cec87472e42778148a55b619a15893a0d8c2e80c
|
| 3 |
size 2387
|