Initial commit
Browse files- a2c-PandaPickAndPlace-v3.zip +2 -2
- a2c-PandaPickAndPlace-v3/data +14 -14
- a2c-PandaPickAndPlace-v3/policy.optimizer.pth +1 -1
- a2c-PandaPickAndPlace-v3/policy.pth +1 -1
- config.json +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
- vec_normalize.pkl +1 -1
a2c-PandaPickAndPlace-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 sha256:4367708b20d1943c2a7c979a7f1badd3851b2ece703129537cda58166f19227d
|
| 3 |
+
size 123093
|
a2c-PandaPickAndPlace-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": "[[ 0.
|
| 34 |
-
"desired_goal": "[[-0.
|
| 35 |
-
"observation": "[[ 4.
|
| 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": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00
|
| 47 |
},
|
| 48 |
"_episode_num": 0,
|
| 49 |
"use_sde": false,
|
|
@@ -52,13 +52,13 @@
|
|
| 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":
|
| 62 |
"n_steps": 5,
|
| 63 |
"gamma": 0.99,
|
| 64 |
"gae_lambda": 1.0,
|
|
|
|
| 19 |
"weight_decay": 0
|
| 20 |
}
|
| 21 |
},
|
| 22 |
+
"num_timesteps": 2000000,
|
| 23 |
+
"_total_timesteps": 2000000,
|
| 24 |
"_num_timesteps_at_start": 0,
|
| 25 |
"seed": null,
|
| 26 |
"action_noise": null,
|
| 27 |
+
"start_time": 1695358508554840397,
|
| 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": "[[ 0.27943867 -0.50223935 0.09262488]\n [-0.65368813 -0.918103 0.09264952]\n [ 0.7330626 -0.4211944 0.09264577]\n [-1.1483053 -1.2112871 0.09264577]]",
|
| 34 |
+
"desired_goal": "[[-0.41734922 1.5532274 -0.17318994]\n [ 0.09765653 0.22234255 -0.81221306]\n [-0.83736014 1.6387683 0.10325392]\n [ 0.8413784 1.0437697 0.6682991 ]]",
|
| 35 |
+
"observation": "[[ 4.7529164e-01 1.5539757e+00 7.8063615e-02 1.0876509e-01\n 4.9087822e-01 -1.8850880e+00 1.3214624e+00 2.7943867e-01\n -5.0223935e-01 9.2624880e-02 -4.5729256e-03 1.0426892e-02\n -1.6709143e-02 5.5137649e-02 -3.8833778e-02 4.2263780e-02\n 1.1716510e-02 -2.5196238e-03 -5.1323287e-03]\n [-2.1434356e-01 1.2761227e+00 7.1532214e-01 8.6257273e-01\n 7.3279393e-01 1.2321084e+00 1.3216404e+00 -6.5368813e-01\n -9.1810298e-01 9.2649519e-02 -4.9350108e-03 1.0155034e-02\n -1.6368937e-02 5.5040881e-02 -3.8531434e-02 4.2519927e-02\n 9.8143006e-03 -5.5157249e-03 -5.2686129e-03]\n [-9.5396465e-01 5.5787730e-01 -1.4189730e+00 -1.0004032e+00\n 1.0365970e+00 -2.1395104e-02 1.2899150e+00 7.3306262e-01\n -4.2119440e-01 9.2645772e-02 -4.9677938e-03 1.0463062e-02\n -1.5221706e-02 5.5603258e-02 -3.8460623e-02 4.2263780e-02\n 1.1716532e-02 -2.5196036e-03 -4.6079331e-03]\n [-4.8765489e-01 2.2506919e+00 2.6145527e+00 1.7405173e-01\n 1.4743914e-02 3.3587724e-01 1.3216354e+00 -1.1483053e+00\n -1.2112871e+00 9.2645772e-02 -4.9677910e-03 1.0463066e-02\n -1.5164296e-02 5.5603255e-02 -3.8460627e-02 4.2263780e-02\n 1.1716532e-02 -2.5196036e-03 -4.6079489e-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": "[[-0.03352048 -0.06922895 0.02 ]\n [ 0.09109946 0.10770944 0.02 ]\n [-0.10177349 -0.02230578 0.02 ]\n [ 0.11430038 -0.11581988 0.02 ]]",
|
| 45 |
+
"desired_goal": "[[ 0.08285271 -0.09788374 0.06987323]\n [ 0.02229834 0.09848642 0.12924582]\n [-0.04223283 0.07081998 0.02 ]\n [ 0.12395274 -0.12187909 0.20661643]]",
|
| 46 |
+
"observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00 -3.3520479e-02\n -6.9228947e-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 9.1099456e-02\n 1.0770944e-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 -1.0177349e-01\n -2.2305777e-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 1.1430038e-01\n -1.1581988e-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]]"
|
| 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": 100000,
|
| 62 |
"n_steps": 5,
|
| 63 |
"gamma": 0.99,
|
| 64 |
"gae_lambda": 1.0,
|
a2c-PandaPickAndPlace-v3/policy.optimizer.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 51646
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fb5b78ade50b204b8c72199ea4e23603c39ebf77d0af21db4a06e666a95a7a95
|
| 3 |
size 51646
|
a2c-PandaPickAndPlace-v3/policy.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 52926
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7e850e4e23771a859d7408b53021c6cbb4b1badadc943429835779debed95395
|
| 3 |
size 52926
|
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 0x7d4abfcb8b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d4abfcb1880>"}, "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": 1695355073495098441, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.34446016 1.1610799 0.10746837]\n [-0.2425352 1.0233549 0.10719674]\n [-0.12577438 0.38863453 0.10721506]\n [ 1.1589944 0.165002 0.10722306]]", "desired_goal": "[[-0.05994277 0.69579893 -1.0816103 ]\n [ 0.3763592 -1.3103949 -1.0816103 ]\n [-1.5291167 -0.61145246 -0.51694894]\n [-0.43980634 -1.6513823 -0.04665948]]", "observation": "[[ 4.80215028e-02 -6.40877243e-03 2.56614149e-01 6.15222231e-02\n -5.77490777e-04 3.86989638e-02 -7.68261313e-01 3.44460160e-01\n 1.16107988e+00 1.07468374e-01 -2.14358401e-02 -1.21230441e-04\n -1.17001487e-02 5.09936512e-02 3.19338813e-02 5.07453009e-02\n -1.04581295e-02 -1.07699037e-02 -6.99370541e-03]\n [ 2.68398523e-01 -6.47651777e-02 8.69380593e-01 3.92125547e-01\n 1.21771598e+00 -1.97632587e+00 -7.67073929e-01 -2.42535204e-01\n 1.02335489e+00 1.07196741e-01 -2.11629923e-02 -5.92571923e-05\n -1.20884143e-02 5.07870428e-02 3.19071896e-02 5.07453009e-02\n -1.04581295e-02 -1.07699037e-02 -7.06741121e-03]\n [ 9.20439363e-01 -1.93172082e-01 -1.02791357e+00 5.16011536e-01\n -8.14401329e-01 9.07977104e-01 -7.68261611e-01 -1.25774384e-01\n 3.88634533e-01 1.07215062e-01 -2.14937199e-02 -3.08158960e-05\n -1.12283248e-02 5.11991382e-02 3.22109722e-02 5.07453009e-02\n -1.04581090e-02 -1.07698869e-02 -6.64708018e-03]\n [ 1.00904512e+00 4.70365763e-01 -1.15584731e+00 -2.78146006e-02\n 7.01058507e-01 5.87395392e-02 -7.68238902e-01 1.15899444e+00\n 1.65002003e-01 1.07223056e-01 -2.14356352e-02 -1.21838522e-04\n -1.23054180e-02 5.09944558e-02 3.19343954e-02 5.07466383e-02\n -1.04609737e-02 -1.07650124e-02 -6.99370541e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.08691656 0.03541376 0.02 ]\n [-0.14331397 0.14339195 0.02 ]\n [ 0.08548099 0.13155396 0.02 ]\n [ 0.04994603 0.00697491 0.02 ]]", "desired_goal": "[[-0.14219901 0.0648561 0.09366149]\n [ 0.14041977 0.10900348 0.1604932 ]\n [ 0.00942462 -0.05547956 0.02 ]\n [ 0.04217019 -0.02838418 0.2114229 ]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00 8.6916558e-02\n 3.5413757e-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 -1.4331397e-01\n 1.4339195e-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 8.5480988e-02\n 1.3155396e-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 4.9946025e-02\n 6.9749062e-03 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": 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 '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": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
|
|
|
|
| 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 0x7d4abfcb8b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d4abfcb1880>"}, "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": 1695358508554840397, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.27943867 -0.50223935 0.09262488]\n [-0.65368813 -0.918103 0.09264952]\n [ 0.7330626 -0.4211944 0.09264577]\n [-1.1483053 -1.2112871 0.09264577]]", "desired_goal": "[[-0.41734922 1.5532274 -0.17318994]\n [ 0.09765653 0.22234255 -0.81221306]\n [-0.83736014 1.6387683 0.10325392]\n [ 0.8413784 1.0437697 0.6682991 ]]", "observation": "[[ 4.7529164e-01 1.5539757e+00 7.8063615e-02 1.0876509e-01\n 4.9087822e-01 -1.8850880e+00 1.3214624e+00 2.7943867e-01\n -5.0223935e-01 9.2624880e-02 -4.5729256e-03 1.0426892e-02\n -1.6709143e-02 5.5137649e-02 -3.8833778e-02 4.2263780e-02\n 1.1716510e-02 -2.5196238e-03 -5.1323287e-03]\n [-2.1434356e-01 1.2761227e+00 7.1532214e-01 8.6257273e-01\n 7.3279393e-01 1.2321084e+00 1.3216404e+00 -6.5368813e-01\n -9.1810298e-01 9.2649519e-02 -4.9350108e-03 1.0155034e-02\n -1.6368937e-02 5.5040881e-02 -3.8531434e-02 4.2519927e-02\n 9.8143006e-03 -5.5157249e-03 -5.2686129e-03]\n [-9.5396465e-01 5.5787730e-01 -1.4189730e+00 -1.0004032e+00\n 1.0365970e+00 -2.1395104e-02 1.2899150e+00 7.3306262e-01\n -4.2119440e-01 9.2645772e-02 -4.9677938e-03 1.0463062e-02\n -1.5221706e-02 5.5603258e-02 -3.8460623e-02 4.2263780e-02\n 1.1716532e-02 -2.5196036e-03 -4.6079331e-03]\n [-4.8765489e-01 2.2506919e+00 2.6145527e+00 1.7405173e-01\n 1.4743914e-02 3.3587724e-01 1.3216354e+00 -1.1483053e+00\n -1.2112871e+00 9.2645772e-02 -4.9677910e-03 1.0463066e-02\n -1.5164296e-02 5.5603255e-02 -3.8460627e-02 4.2263780e-02\n 1.1716532e-02 -2.5196036e-03 -4.6079489e-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": "[[-0.03352048 -0.06922895 0.02 ]\n [ 0.09109946 0.10770944 0.02 ]\n [-0.10177349 -0.02230578 0.02 ]\n [ 0.11430038 -0.11581988 0.02 ]]", "desired_goal": "[[ 0.08285271 -0.09788374 0.06987323]\n [ 0.02229834 0.09848642 0.12924582]\n [-0.04223283 0.07081998 0.02 ]\n [ 0.12395274 -0.12187909 0.20661643]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00 0.0000000e+00 -3.3520479e-02\n -6.9228947e-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 9.1099456e-02\n 1.0770944e-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 -1.0177349e-01\n -2.2305777e-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 1.1430038e-01\n -1.1581988e-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]]"}, "_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:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwEkAAAAAAACMAWyUSzKMAXSUR0C0rqnIyTIOdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0rqqrq+rVdX2UKGgGRwAAAAAAAAAAaAdLAWgIR0C0rq5K8L8adX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0rpHIyTIOdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0rue8kD6ndX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ryvES/TLdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0rzPTLGJfdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0rxfMwDeTdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0r28Wj45+dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0r7JtvXK9dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0r8Z+DvmYdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0r6rxVhkRdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sAik43m3dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sFw5Jbt7dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sIKfFrEcdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sGgzDXOGdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sMXA6+36dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sRCjYZl4dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sRvZmI0qdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sQBK6FufdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sVhW912adX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sZ8qvvBrdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sbR6OYICdX2UKGgGRwAAAAAAAAAAaAdLAWgIR0C0sbdfsu3+dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sZi6+WWydX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sfRYRujzdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sjwW8AaOdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0skJc1O0tdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0siPllsgudX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0snyhSLqEdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ssJFCswMdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ssyBkI5YdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0sq3qu8sddX2UKGgGRwAAAAAAAAAAaAdLAWgIR0C0ss921UlzdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0swRWYF7ldX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0s0UzCUHIdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0syzLB9CvdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0s04na37UdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0s4Qxi5NHdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0s8leOXE7dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0s8R1PnB+dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0s+Y2sJY1dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tCBtUGVzdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tGVwxWT5dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tFMMEzO5dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tHSL/CIldX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tKsMVk+YdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tPBInSfEdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tOJ3cHnmdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tQPB7/n4dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tTo+nqFAdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tX8J6Y3OdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tW2nfl6rdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tY77oB7vdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tcaAnUlSdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tg3Mt9QXdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tgKHwgDBdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tiQ3DNyHdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tl3tjTa1dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tqH58BuGdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tpRe9i+ddX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0trZKJ2t/dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tu/0dzXCdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tzyUcGTtdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0tzmcSXdCdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0t1s3qAz6dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0t5iEtdzGdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0t/bFfiPydX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uASd8RcvdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uCb+xW1ddX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uGJsGgSOdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uKfQjUutdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uJbVz6rOdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uLhA8jiXdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uO8jzI3jdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uTDpLVWkdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uRpcPe54dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uTvr0J4TdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uXLAgxJvdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ubZX+2mYdX2UKGgGRwAAAAAAAAAAaAdLAWgIR0C0ubjIq9XcdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uZ1SflIVdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ub6y4Wk8dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ufSY1He8dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ujx0p3HJdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uiJHqeK9dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ukPqcEvCdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uno6nzg/dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0ur+rlvIfdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uqvGVAzIdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0us118stkdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uwT9S/CZdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0u05RoAXEdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0uz6STyJ9dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0u2BYFJQMdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0u5cVk+X7dX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0u+AeNkvsdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0u9BS1maqdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0u/GsijcmdX2UKGgGR8BJAAAAAAAAaAdLMmgIR0C0vCcb3oLYdWUu"}, "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 '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": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
|
replay.mp4
CHANGED
|
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
|
results.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"mean_reward": -50.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-09-
|
|
|
|
| 1 |
+
{"mean_reward": -50.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-09-22T06:23:40.417359"}
|
vec_normalize.pkl
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3013
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c6d92c5ca2dbdc70daf1e34f40ca221d72fc75236f064b98c918366996a35e56
|
| 3 |
size 3013
|