Initial commit
Browse files- A2C-PandaPickAndPlaceDense-v3.zip +2 -2
- A2C-PandaPickAndPlaceDense-v3/data +14 -14
- A2C-PandaPickAndPlaceDense-v3/policy.optimizer.pth +1 -1
- A2C-PandaPickAndPlaceDense-v3/policy.pth +1 -1
- README.md +1 -1
- config.json +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
- vec_normalize.pkl +1 -1
A2C-PandaPickAndPlaceDense-v3.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 sha256:385f1f3cdbadf0366de747fe29f523485f16ba96dd75bdb115b89929d7729aec
|
| 3 |
+
size 124153
|
A2C-PandaPickAndPlaceDense-v3/data
CHANGED
|
@@ -19,31 +19,31 @@
|
|
| 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 |
"_last_obs": {
|
| 31 |
":type:": "<class 'collections.OrderedDict'>",
|
| 32 |
-
":serialized:": "
|
| 33 |
-
"achieved_goal": "[[
|
| 34 |
-
"desired_goal": "[[
|
| 35 |
-
"observation": "[[
|
| 36 |
},
|
| 37 |
"_last_episode_starts": {
|
| 38 |
":type:": "<class 'numpy.ndarray'>",
|
| 39 |
-
":serialized:": "
|
| 40 |
},
|
| 41 |
"_last_original_obs": {
|
| 42 |
":type:": "<class 'collections.OrderedDict'>",
|
| 43 |
-
":serialized:": "
|
| 44 |
-
"achieved_goal": "[[
|
| 45 |
-
"desired_goal": "[[ 0.
|
| 46 |
-
"observation": "[[ 3.
|
| 47 |
},
|
| 48 |
"_episode_num": 0,
|
| 49 |
"use_sde": false,
|
|
@@ -52,14 +52,14 @@
|
|
| 52 |
"_stats_window_size": 100,
|
| 53 |
"ep_info_buffer": {
|
| 54 |
":type:": "<class 'collections.deque'>",
|
| 55 |
-
":serialized:": "
|
| 56 |
},
|
| 57 |
"ep_success_buffer": {
|
| 58 |
":type:": "<class 'collections.deque'>",
|
| 59 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
| 60 |
},
|
| 61 |
"_n_updates": 50,
|
| 62 |
-
"n_steps":
|
| 63 |
"gamma": 0.99,
|
| 64 |
"gae_lambda": 1.0,
|
| 65 |
"ent_coef": 0.0,
|
|
|
|
| 19 |
"weight_decay": 0
|
| 20 |
}
|
| 21 |
},
|
| 22 |
+
"num_timesteps": 10000,
|
| 23 |
+
"_total_timesteps": 10000,
|
| 24 |
"_num_timesteps_at_start": 0,
|
| 25 |
"seed": null,
|
| 26 |
"action_noise": null,
|
| 27 |
+
"start_time": 1714990306878991300,
|
| 28 |
"learning_rate": 0.0007,
|
| 29 |
"tensorboard_log": null,
|
| 30 |
"_last_obs": {
|
| 31 |
":type:": "<class 'collections.OrderedDict'>",
|
| 32 |
+
":serialized:": "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",
|
| 33 |
+
"achieved_goal": "[[ 0.7391509 -0.23592034 0.10686233]\n [ 0.30086112 -0.3836489 0.10686233]\n [ 0.24867271 0.20272198 0.10687134]\n [-0.6089577 -0.08245784 0.10686243]]",
|
| 34 |
+
"desired_goal": "[[-0.37837383 0.13189338 1.6722691 ]\n [ 1.1868069 -0.02152941 -0.42727077]\n [ 1.0584904 -1.5314789 -0.18569696]\n [-0.88660496 -0.6192086 0.6610107 ]]",
|
| 35 |
+
"observation": "[[-1.73777902e+00 1.78974783e+00 -6.42271876e-01 -1.09742045e+00\n 7.90678859e-01 9.72194821e-02 -1.14858091e+00 7.39150882e-01\n -2.35920340e-01 1.06862329e-01 3.57464887e-02 5.49782738e-02\n 2.93509457e-02 8.14501345e-02 5.21532707e-02 6.89410865e-02\n -2.43173297e-02 1.64051738e-03 -2.77465000e-03]\n [ 1.52793992e+00 -1.13085592e+00 -4.29006755e-01 -1.79862067e-01\n 1.27215993e+00 -2.20657778e+00 -1.14821196e+00 3.00861120e-01\n -3.83648902e-01 1.06862329e-01 3.57814729e-02 5.42561449e-02\n 2.95286719e-02 8.14370960e-02 5.23211583e-02 6.89410865e-02\n -2.43173297e-02 1.64051680e-03 -2.77462672e-03]\n [-2.70856142e+00 -8.96828651e-01 -5.63673794e-01 -1.20932385e-01\n -1.85644746e-01 1.09242797e+00 1.17402327e+00 2.48672709e-01\n 2.02721983e-01 1.06871344e-01 3.58377472e-02 5.46674058e-02\n 3.06070633e-02 8.11796263e-02 5.25579900e-02 6.87741637e-02\n -2.62617655e-02 3.91948357e-04 -2.64692097e-03]\n [ 7.21647382e-01 4.23644096e-01 9.94045854e-01 2.61455983e-01\n 1.21068466e+00 -6.16536319e-01 1.17420697e+00 -6.08957708e-01\n -8.24578404e-02 1.06862426e-01 3.57464924e-02 5.49762920e-02\n 2.97134425e-02 8.14518705e-02 5.21532595e-02 6.89396337e-02\n -2.43173316e-02 1.64966739e-03 -2.77460460e-03]]"
|
| 36 |
},
|
| 37 |
"_last_episode_starts": {
|
| 38 |
":type:": "<class 'numpy.ndarray'>",
|
| 39 |
+
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
|
| 40 |
},
|
| 41 |
"_last_original_obs": {
|
| 42 |
":type:": "<class 'collections.OrderedDict'>",
|
| 43 |
+
":serialized:": "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",
|
| 44 |
+
"achieved_goal": "[[-0.09091638 0.06192463 0.02 ]\n [-0.0834527 -0.10402468 0.02 ]\n [-0.02563329 0.12062673 0.02 ]\n [ 0.05256001 -0.01142643 0.02 ]]",
|
| 45 |
+
"desired_goal": "[[ 0.06377005 -0.09002284 0.08995748]\n [ 0.08852211 -0.12603076 0.06923176]\n [ 0.11192548 0.14253761 0.06651619]\n [ 0.01149623 -0.08709088 0.02 ]]",
|
| 46 |
+
"observation": "[[ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -9.09163803e-02\n 6.19246289e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -8.34527016e-02\n -1.04024678e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -2.56332941e-02\n 1.20626725e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 5.25600053e-02\n -1.14264330e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]]"
|
| 47 |
},
|
| 48 |
"_episode_num": 0,
|
| 49 |
"use_sde": false,
|
|
|
|
| 52 |
"_stats_window_size": 100,
|
| 53 |
"ep_info_buffer": {
|
| 54 |
":type:": "<class 'collections.deque'>",
|
| 55 |
+
":serialized:": "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"
|
| 56 |
},
|
| 57 |
"ep_success_buffer": {
|
| 58 |
":type:": "<class 'collections.deque'>",
|
| 59 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
| 60 |
},
|
| 61 |
"_n_updates": 50,
|
| 62 |
+
"n_steps": 50,
|
| 63 |
"gamma": 0.99,
|
| 64 |
"gae_lambda": 1.0,
|
| 65 |
"ent_coef": 0.0,
|
A2C-PandaPickAndPlaceDense-v3/policy.optimizer.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 51951
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:644c6cac8001515e64f291409ada75548bc1e2f372ecd61e774f2802db8856d1
|
| 3 |
size 51951
|
A2C-PandaPickAndPlaceDense-v3/policy.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 53231
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cce1cfd864db0475fc403c7cf12fa40858c27c4a9f9ba815173da99c2c26b5da
|
| 3 |
size 53231
|
README.md
CHANGED
|
@@ -16,7 +16,7 @@ model-index:
|
|
| 16 |
type: PandaPickAndPlaceDense-v3
|
| 17 |
metrics:
|
| 18 |
- type: mean_reward
|
| 19 |
-
value: -11.
|
| 20 |
name: mean_reward
|
| 21 |
verified: false
|
| 22 |
---
|
|
|
|
| 16 |
type: PandaPickAndPlaceDense-v3
|
| 17 |
metrics:
|
| 18 |
- type: mean_reward
|
| 19 |
+
value: -11.08 +/- 2.93
|
| 20 |
name: mean_reward
|
| 21 |
verified: false
|
| 22 |
---
|
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 0x0000021C7CE91620>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x0000021C7CE8A580>"}, "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": 1000, "_total_timesteps": 1000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1714989079990673900, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 1.3044112 0.7683268 0.12032255]\n [-0.66273177 -0.3659164 0.12032255]\n [ 0.6235068 -0.47585195 0.12032255]\n [-0.24543248 0.64232 0.12032255]]", "desired_goal": "[[ 1.8122001 1.5443218 -1.3811198 ]\n [ 0.879466 1.1630942 1.6339891 ]\n [-0.3728456 -1.1283029 1.804592 ]\n [-0.8088598 -0.37469706 -1.3811198 ]]", "observation": "[[ 0.5842109 -0.4916305 1.4156107 0.09762286 -0.02797361 0.11328804\n -1.0602591 1.3044112 0.7683268 0.12032255 -0.03702876 0.2058336\n 0.03976776 0.14498791 0.08506173 0.07189737 -0.07872247 -0.00202583\n 0.08094105]\n [ 0.5842109 -0.4916305 1.4156107 0.09762286 -0.02797361 0.11328804\n -1.0602591 -0.66273177 -0.3659164 0.12032255 -0.03702876 0.2058336\n 0.03976776 0.14498791 0.08506173 0.07189737 -0.07872247 -0.00202583\n 0.08094105]\n [ 0.5842109 -0.4916305 1.4156107 0.09762286 -0.02797361 0.11328804\n -1.0602591 0.6235068 -0.47585195 0.12032255 -0.03702876 0.2058336\n 0.03976776 0.14498791 0.08506173 0.07189737 -0.07872247 -0.00202583\n 0.08094105]\n [ 0.5842109 -0.4916305 1.4156107 0.09762286 -0.02797361 0.11328804\n -1.0602591 -0.24543248 0.64232 0.12032255 -0.03702876 0.2058336\n 0.03976776 0.14498791 0.08506173 0.07189737 -0.07872247 -0.00202583\n 0.08094105]]"}, "_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": "[[ 0.0130892 0.08121299 0.02 ]\n [ 0.14785513 -0.12772149 0.02 ]\n [-0.01175001 0.06614772 0.02 ]\n [-0.12554659 -0.03553248 0.02 ]]", "desired_goal": "[[ 0.05189816 0.12413325 0.04368898]\n [ 0.10917693 0.13059723 0.15760759]\n [-0.09292272 0.10585882 0.20478475]\n [ 0.04563163 -0.11165731 0.09937657]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00 1.3089203e-02\n 8.1212990e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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 0.0000000e+00 1.4785513e-01\n -1.2772149e-01 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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 0.0000000e+00 -1.1750007e-02\n 6.6147722e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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 0.0000000e+00 -1.2554659e-01\n -3.5532482e-02 2.0000000e-02 0.0000000e+00 -0.0000000e+00\n 0.0000000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00\n 0.0000000e+00 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": 50, "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 'gymnasium.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, (19,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Windows-10-10.0.22631-SP0 10.0.22631", "Python": "3.11.9", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.0", "GPU Enabled": "False", "Numpy": "1.24.3", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}
|
|
|
|
| 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 0x0000021C7CE91620>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x0000021C7CE8A580>"}, "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": 10000, "_total_timesteps": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1714990306878991300, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWViwIAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA/jg9PxqVcb6j2to9eAqaPqFtxL6j2to9D6R+PlqWTz5d39o9p+Qbv6jfqL2w2to9lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAN7rBvg8PBz7qDNY/SumXP3FesLw8w9q+nXyHP4AHxL9YJz6+i/hiv3SEHr//Nyk/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWMAEAAAAAAACLb96/dRblP+5rJL9GeIy/7mlKPwIbxz2zBJO//jg9PxqVcb6j2to96WoSPeYwYT1lcfA8VM+mPaueVT38MI09IzXHvKEG1zrn1jW7iZPDP+O/kL/Gptu+wy04viPWoj+SOA3AnPiSv3gKmj6hbcS+o9raPZiPEj2xO149HebxPH7Ipj22TlY9/DCNPSM1x7ycBtc6g9Y1uxJZLcCQlmW/7UwQv2ar972oGT6+rtSLP2VGlj8PpH4+WpZPPl3f2j2ayhI97upfPaq7+jyBQaY9DEdXPXjZjD3qIte8a37NOfd3LbvivTg/4efYPsp5fj+P3YU+t/eaP1PVHb9qTJY/p+Qbv6jfqL2w2to96moSPdIuYT2bafM8PdCmPaieVT05MI09JDXHvKc52Dok1jW7lGgOSwRLE4aUaBJ0lFKUdS4=", "achieved_goal": "[[ 0.7391509 -0.23592034 0.10686233]\n [ 0.30086112 -0.3836489 0.10686233]\n [ 0.24867271 0.20272198 0.10687134]\n [-0.6089577 -0.08245784 0.10686243]]", "desired_goal": "[[-0.37837383 0.13189338 1.6722691 ]\n [ 1.1868069 -0.02152941 -0.42727077]\n [ 1.0584904 -1.5314789 -0.18569696]\n [-0.88660496 -0.6192086 0.6610107 ]]", "observation": "[[-1.73777902e+00 1.78974783e+00 -6.42271876e-01 -1.09742045e+00\n 7.90678859e-01 9.72194821e-02 -1.14858091e+00 7.39150882e-01\n -2.35920340e-01 1.06862329e-01 3.57464887e-02 5.49782738e-02\n 2.93509457e-02 8.14501345e-02 5.21532707e-02 6.89410865e-02\n -2.43173297e-02 1.64051738e-03 -2.77465000e-03]\n [ 1.52793992e+00 -1.13085592e+00 -4.29006755e-01 -1.79862067e-01\n 1.27215993e+00 -2.20657778e+00 -1.14821196e+00 3.00861120e-01\n -3.83648902e-01 1.06862329e-01 3.57814729e-02 5.42561449e-02\n 2.95286719e-02 8.14370960e-02 5.23211583e-02 6.89410865e-02\n -2.43173297e-02 1.64051680e-03 -2.77462672e-03]\n [-2.70856142e+00 -8.96828651e-01 -5.63673794e-01 -1.20932385e-01\n -1.85644746e-01 1.09242797e+00 1.17402327e+00 2.48672709e-01\n 2.02721983e-01 1.06871344e-01 3.58377472e-02 5.46674058e-02\n 3.06070633e-02 8.11796263e-02 5.25579900e-02 6.87741637e-02\n -2.62617655e-02 3.91948357e-04 -2.64692097e-03]\n [ 7.21647382e-01 4.23644096e-01 9.94045854e-01 2.61455983e-01\n 1.21068466e+00 -6.16536319e-01 1.17420697e+00 -6.08957708e-01\n -8.24578404e-02 1.06862426e-01 3.57464924e-02 5.49762920e-02\n 2.97134425e-02 8.14518705e-02 5.21532595e-02 6.89396337e-02\n -2.43173316e-02 1.64966739e-03 -2.77460460e-03]]"}, "_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": "[[-0.09091638 0.06192463 0.02 ]\n [-0.0834527 -0.10402468 0.02 ]\n [-0.02563329 0.12062673 0.02 ]\n [ 0.05256001 -0.01142643 0.02 ]]", "desired_goal": "[[ 0.06377005 -0.09002284 0.08995748]\n [ 0.08852211 -0.12603076 0.06923176]\n [ 0.11192548 0.14253761 0.06651619]\n [ 0.01149623 -0.08709088 0.02 ]]", "observation": "[[ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -9.09163803e-02\n 6.19246289e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -8.34527016e-02\n -1.04024678e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -2.56332941e-02\n 1.20626725e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 5.25600053e-02\n -1.14264330e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+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:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwCU3hbW3BpKMAWyUSzKMAXSUR0AmjXCj1wo9dX2UKGgGR8AsEIEbHZK4aAdLMmgIR0AmiuCf6Gg0dX2UKGgGR8AvKskIHC40aAdLMmgIR0AnxgtOEdvLdX2UKGgGR8AK6S/0ulGgaAdLMmgIR0Anmv8qFyq/dX2UKGgGR8AbLKJVKf4AaAdLMmgIR0AnaMZxaPjodX2UKGgGR8AsCxj8UEgXaAdLMmgIR0AnalANXo1UdX2UKGgGR8Aa9sj3VTaTaAdLMmgIR0AoqbVBlcyFdX2UKGgGR8AlXusLfDUFaAdLMmgIR0AofaLXL/0edX2UKGgGR8AUWDh99c8laAdLMmgIR0AoS+0w8GLUdX2UKGgGR8AhRnjhky1vaAdLMmgIR0AoSubqhUR4dX2UKGgGR8ArMOI68xsVaAdLMmgIR0AphY5ksjFAdX2UKGgGR8AR/0Dlo11oaAdLMmgIR0ApWXvYvnKXdX2UKGgGR8AlnFUhmoR7aAdLMmgIR0ApJ0MgEEDAdX2UKGgGR8AbXHWBjFyaaAdLMmgIR0ApIqZtvXK9dX2UKGgGR8ArZHvMKTjeaAdLMmgIR0AqWC3gDRtxdX2UKGgGR8AWP4YaYNRWaAdLMmgIR0AqLBt1p0wKdX2UKGgGR8AVvzd1uBMBaAdLMmgIR0Ap+eK8+RozdX2UKGgGR8ATST6i0v4/aAdLMmgIR0Ap99XtBv74dX2UKGgGR8AXZ/G2kSElaAdLMmgIR0ArLNpM6BAfdX2UKGgGR8AQEdlum78OaAdLMmgIR0ArAOmR/3FldX2UKGgGR8AYB/3FkxyoaAdLMmgIR0AqzrDZUT+OdX2UKGgGR8AlLKzRhMJyaAdLMmgIR0AqyhQm/nGLdX2UKGgGR8Aq+tV7x/d7aAdLMmgIR0AsEg6EJ0GNdX2UKGgGR8AmvT3IuGsWaAdLMmgIR0Ar54W1twaSdX2UKGgGR8ApuzzmOlwcaAdLMmgIR0ArtdAPd2xIdX2UKGgGR8AsDlQMx46faAdLMmgIR0ArtUzbeuV5dX2UKGgGR8AeYKUmlZX/aAdLMmgIR0As9JEH+qBFdX2UKGgGR8AnQIrOJLuhaAdLMmgIR0AsyYUFjd56dX2UKGgGR8Ao7XyRSxZ/aAdLMmgIR0AsmFKTSsr/dX2UKGgGR8Am/Tho/RmcaAdLMmgIR0AsmVj7Q9iddX2UKGgGR8AkmtpVS4vwaAdLMmgIR0At2BnzxwyZdX2UKGgGR8Ao4SfUWl/IaAdLMmgIR0AtrQ3xWkrPdX2UKGgGR8AwVAHE/B3zaAdLMmgIR0AtetU4rBj4dX2UKGgGR8AmocTakAPvaAdLMmgIR0Ate3kxREWqdX2UKGgGR8Az8TxG2CumaAdLMmgIR0AuvdB0IToMdX2UKGgGR7+ie2/i5uqFaAdLAWgIR0AuxHn2ZiNLdX2UKGgGR8AghN3W4EwGaAdLMmgIR0AukkE9t/FzdX2UKGgGR8AkXzr/sE7oaAdLMmgIR0AuYAiFCb+cdX2UKGgGR8AgZHPNVzZIaAdLMmgIR0AuXn7pFCswdX2UKGgGR8AnhlUZNwiraAdLMmgIR0AvmamXPZ7HdX2UKGgGR8AhdlCCz1K5aAdLMmgIR0AvZ3Dej2zwdX2UKGgGR8Aqb7qIJqqPaAdLMmgIR0AvNTgEU0vXdX2UKGgGR8ApKsLfDUExaAdLMmgIR0AvNTgEU0vXdX2UKGgGR7+RzijtXxOMaAdLAWgIR0AvOlfqoqCpdX2UKGgGR7/8FT3qRlpXaAdLIWgIR0Av1JiAlOXWdX2UKGgGR8AoVI/7iyY5aAdLMmgIR0AwQCLMs6JZdX2UKGgGR8AlIFhXr+o+aAdLMmgIR0AwJwZwXIludX2UKGgGR8Aphggow22oaAdLMmgIR0AwDeoUBXCCdX2UKGgGR8AnPr1M/QjVaAdLMmgIR0AwWhKUVzp5dX2UKGgGR8Aqcsny/bj+aAdLMmgIR0Awr+kgwGnodX2UKGgGR8ApJ78ejmCAaAdLMmgIR0AwlsyzollcdX2UKGgGR8Af/0btJFspaAdLMmgIR0AwffHxSYPYdX2UKGgGR8AYlfkWAPNFaAdLMmgIR0AwxvitJWeZdX2UKGgGR8AuUfYBeXzEaAdLMmgIR0AxHAp8WsRydX2UKGgGR8A1OBmwqy4XaAdLMmgIR0AxAu4PPLPldX2UKGgGR8APsnmaH9FXaAdLMmgIR0Aw6dGy5Zr6dX2UKGgGR7/hgeA/cFhYaAdLCGgIR0AxEUdq+JxedX2UKGgGR8AjP2vB7/n4aAdLMmgIR0AxLmReTmnwdX2UKGgGR8AzZ7BwdbPhaAdLMmgIR0Axg/lQuVX4dX2UKGgGR8AnT0QK8cuKaAdLMmgIR0AxUcCYCyQgdX2UKGgGR8AlLNorWiDeaAdLMmgIR0Axer/sE7nxdX2UKGgGR8AlT238XN1RaAdLMmgIR0AxmAWznieedX2UKGgGR8AgOD7IkqtpaAdLMmgIR0Ax7ReC04R3dX2UKGgGR8AYReE7GNrCaAdLMmgIR0AxuyBTXJ5ndX2UKGgGR8ApBG5MDfWMaAdLMmgIR0Ax5B+nZTQ3dX2UKGgGR8AuXzreIl+maAdLMmgIR0AyAyC4BmwrdX2UKGgGR8ARVc4YJmdzaAdLMmgIR0AyWLWqcVgydX2UKGgGR8ATJ3wCr92paAdLMmgIR0AyJnzg/C66dX2UKGgGR8AuF45cTrVwaAdLMmgIR0AyUUdq+JxedX2UKGgGR8ArJWattALRaAdLMmgIR0Ayc50r9VFQdX2UKGgGR8AfGBH09QoDaAdLMmgIR0AyyYbsF+uvdX2UKGgGR8AiTdiUgSvlaAdLMmgIR0Ayl04iosI3dX2UKGgGR8AjzI7NjbztaAdLMmgIR0AywAvcrRShdX2UKGgGR8AlH8iwB5ooaAdLMmgIR0Ay3dilSCOFdX2UKGgGR8AXFt0mtyPuaAdLMmgIR0AzM68xsVL0dX2UKGgGR8AZkKXv6TGHaAdLMmgIR0AzAXZoPCl8dX2UKGgGR8Af2lhw2l2vaAdLMmgIR0AzKzp5eJHidX2UKGgGR8Ak3JXhfjS5aAdLMmgIR0AzTO2RaHKwdX2UKGgGR8Awgwpe/pMYaAdLMmgIR0Azof9P1tfpdX2UKGgGR8Aqik8A7xNJaAdLMmgIR0Azb8aXKKYRdX2UKGgGR8AehIZqEeySaAdLMmgIR0AzmUkOZssQdX2UKGgGR8AXnWXkYGdJaAdLMmgIR0Azu11GLDQ7dX2UKGgGR8AskqxTsIE9aAdLMmgIR0A0EPI4lyBDdX2UKGgGR8Amt24d6sySaAdLMmgIR0Az3rl/6O5sdX2UKGgGR7+mn2qT8pCsaAdLAWgIR0A0E0CRwIdEdX2UKGgGR8AoFgbZOBUaaAdLMmgIR0A0CH2RJVbSdX2UKGgGR8Am3YlpoK2KaAdLMmgIR0A0I4C6pYLcdX2UKGgGR8AUc0P6KtPpaAdLMmgIR0A0RptJnQIEdX2UKGgGR8AuXPnjhky2aAdLMmgIR0A0eyJsO5J9dX2UKGgGR8AmeOJ+DvmYaAdLMmgIR0A0cB3Roh6jdX2UKGgGR8AP5GhEjPfLaAdLMmgIR0A0knOSntOVdX2UKGgGR8AtInuy/sVtaAdLMmgIR0A0tc/MW43FdX2UKGgGR8Aq0rFwT/Q0aAdLMmgIR0A06lbu+h4/dX2UKGgGR8ApglN1yNn5aAdLMmgIR0A035PuXu3MdX2UKGgGR8Ab9TisGPgfaAdLMmgIR0A0/taIN3GGdX2UKGgGR8AmuRxtHhCMaAdLMmgIR0A1IfEn9ehPdX2UKGgGR8ALMMZxaPjoaAdLMmgIR0A1VnhKlHjIdX2UKGgGR7+KTnq3VkMDaAdLAWgIR0A1JD+BH09RdX2UKGgGR8BCxwqAjIJaaAdLMmgIR0A1S3Ov+wTudX2UKGgGR8ApB6w+t8u0aAdLMmgIR0A1bD/lyR0VdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 50, "n_steps": 50, "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 'gymnasium.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, (19,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Windows-10-10.0.22631-SP0 10.0.22631", "Python": "3.11.9", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.0", "GPU Enabled": "False", "Numpy": "1.24.3", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}
|
replay.mp4
CHANGED
|
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
|
results.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"mean_reward": -11.
|
|
|
|
| 1 |
+
{"mean_reward": -11.083601682633162, "std_reward": 2.926646697837276, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-06T12:19:46.349595"}
|
vec_normalize.pkl
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 2953
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:044382a304066894ef44d806bda7e3bcbb2e5d8506dcac13bb1d56b87934e97b
|
| 3 |
size 2953
|