xaeroq commited on
Commit
1c94c37
·
1 Parent(s): f31c9c3

Initial commit

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
- value: -4.53 +/- 2.05
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -7.02 +/- 1.68
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:f1fbe93a96a4feb4784b4758fdf8fdbed7abb154552113954d114218f8e3e5fd
3
  size 108024
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:64ce39c6c705841e94bf60d13d9047ab57ea4bfb8451f0a9df9f48ee2c80a18f
3
  size 108024
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 0x7f4de623e3a0>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc_data object at 0x7f4de6238a80>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
@@ -41,12 +41,12 @@
41
  "_np_random": null
42
  },
43
  "n_envs": 4,
44
- "num_timesteps": 2000000,
45
- "_total_timesteps": 2000000,
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
- "start_time": 1677857788438794729,
50
  "learning_rate": 0.0007,
51
  "tensorboard_log": null,
52
  "lr_schedule": {
@@ -55,10 +55,10 @@
55
  },
56
  "_last_obs": {
57
  ":type:": "<class 'collections.OrderedDict'>",
58
- ":serialized:": "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",
59
- "achieved_goal": "[[ 0.4294525 -0.03713895 0.47747174]\n [ 0.4294525 -0.03713895 0.47747174]\n [ 0.4294525 -0.03713895 0.47747174]\n [ 0.4294525 -0.03713895 0.47747174]]",
60
- "desired_goal": "[[ 1.0690753 1.0014292 1.06238 ]\n [ 1.451435 -0.27171326 -1.0944291 ]\n [-1.4046277 0.88951224 1.4048245 ]\n [ 0.95129913 -0.40849248 -0.38766178]]",
61
- "observation": "[[ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]\n [ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]\n [ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]\n [ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]]"
62
  },
63
  "_last_episode_starts": {
64
  ":type:": "<class 'numpy.ndarray'>",
@@ -66,9 +66,9 @@
66
  },
67
  "_last_original_obs": {
68
  ":type:": "<class 'collections.OrderedDict'>",
69
- ":serialized:": "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",
70
  "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]]",
71
- "desired_goal": "[[ 0.04787081 0.04199878 0.19365026]\n [ 0.09933884 -0.0218574 0.09626509]\n [-0.14177327 -0.08077914 0.24229862]\n [ 0.10212301 -0.00977324 0.07329365]]",
72
  "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]]"
73
  },
74
  "_episode_num": 0,
@@ -77,13 +77,13 @@
77
  "_current_progress_remaining": 0.0,
78
  "ep_info_buffer": {
79
  ":type:": "<class 'collections.deque'>",
80
- ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIZ7eWyXAcBMCUhpRSlIwBbJRLMowBdJRHQLlt8CjUNKB1fZQoaAZoCWgPQwhSSDKrd/gSwJSGlFKUaBVLMmgWR0C5bc0SElE7dX2UKGgGaAloD0MI9fOmIhWmDcCUhpRSlGgVSzJoFkdAuW2p4dIXj3V9lChoBmgJaA9DCEyOO6WDVRjAlIaUUpRoFUsyaBZHQLlthQO4G2V1fZQoaAZoCWgPQwirWWd8X0wQwJSGlFKUaBVLMmgWR0C5bowvpQk5dX2UKGgGaAloD0MIuTZUjPPHEMCUhpRSlGgVSzJoFkdAuW5orupjt3V9lChoBmgJaA9DCEuwOJz5ZRDAlIaUUpRoFUsyaBZHQLluRPFvQ4V1fZQoaAZoCWgPQwiRgNHlzXERwJSGlFKUaBVLMmgWR0C5biB6fJ3gdX2UKGgGaAloD0MINCxGXWtvGcCUhpRSlGgVSzJoFkdAuW8jqUu+RHV9lChoBmgJaA9DCFSQn41chxPAlIaUUpRoFUsyaBZHQLlvACF9KEp1fZQoaAZoCWgPQwjzVIfcDGcXwJSGlFKUaBVLMmgWR0C5btx2nsLOdX2UKGgGaAloD0MIkloomZz6BMCUhpRSlGgVSzJoFkdAuW63okiUxHV9lChoBmgJaA9DCF9dFajF4B7AlIaUUpRoFUsyaBZHQLlvwUDuBtl1fZQoaAZoCWgPQwiismFNZUkhwJSGlFKUaBVLMmgWR0C5b53LaEi/dX2UKGgGaAloD0MIiEfi5el8D8CUhpRSlGgVSzJoFkdAuW96hwl0HXV9lChoBmgJaA9DCDBMpgpG5QrAlIaUUpRoFUsyaBZHQLlvVaiKziV1fZQoaAZoCWgPQwjXpNsSuVAdwJSGlFKUaBVLMmgWR0C5cGpUxVQzdX2UKGgGaAloD0MIYWu28pKvFcCUhpRSlGgVSzJoFkdAuXBHbO/tY3V9lChoBmgJaA9DCKmkTkATERLAlIaUUpRoFUsyaBZHQLlwJFt8/lh1fZQoaAZoCWgPQwhGs7J9yLsUwJSGlFKUaBVLMmgWR0C5b/9+b3GodX2UKGgGaAloD0MIGoums5OBC8CUhpRSlGgVSzJoFkdAuXD8SIxgzHV9lChoBmgJaA9DCE5DVOHPAB3AlIaUUpRoFUsyaBZHQLlw2Mm4RVZ1fZQoaAZoCWgPQwi7YHDNHX0cwJSGlFKUaBVLMmgWR0C5cLUQkHD8dX2UKGgGaAloD0MIlbvP8dECD8CUhpRSlGgVSzJoFkdAuXCQN8VpK3V9lChoBmgJaA9DCNLj9zb9uQ7AlIaUUpRoFUsyaBZHQLlxlVJtix51fZQoaAZoCWgPQwhOgGH5800OwJSGlFKUaBVLMmgWR0C5cXHwPRRedX2UKGgGaAloD0MIdej0vBu7JcCUhpRSlGgVSzJoFkdAuXFOVJL/THV9lChoBmgJaA9DCPusMlNaLxDAlIaUUpRoFUsyaBZHQLlxKenAIpp1fZQoaAZoCWgPQwj8pUV9kisUwJSGlFKUaBVLMmgWR0C5ckKh6By0dX2UKGgGaAloD0MID167tOFwB8CUhpRSlGgVSzJoFkdAuXIfjDKoynV9lChoBmgJaA9DCFLUmXtI6BHAlIaUUpRoFUsyaBZHQLlx+/WDpTx1fZQoaAZoCWgPQwgzbf/KSvMJwJSGlFKUaBVLMmgWR0C5cdd4eLeidX2UKGgGaAloD0MIIlM+BFVDG8CUhpRSlGgVSzJoFkdAuXLexkd3jnV9lChoBmgJaA9DCCqMLQQ5qBrAlIaUUpRoFUsyaBZHQLlyu0gKWs11fZQoaAZoCWgPQwjF/x1RofoGwJSGlFKUaBVLMmgWR0C5cpgGGEf1dX2UKGgGaAloD0MIvB+3Xz75DMCUhpRSlGgVSzJoFkdAuXJzKp1ifHV9lChoBmgJaA9DCI+mejL/qAbAlIaUUpRoFUsyaBZHQLlzdNR3u/l1fZQoaAZoCWgPQwhmMbH5uLYFwJSGlFKUaBVLMmgWR0C5c1HARChOdX2UKGgGaAloD0MIIywq4nTSHcCUhpRSlGgVSzJoFkdAuXMuD8LronV9lChoBmgJaA9DCAHdlzPbRRLAlIaUUpRoFUsyaBZHQLlzCVfeDWd1fZQoaAZoCWgPQwgm++dpwMANwJSGlFKUaBVLMmgWR0C5c/r04BFNdX2UKGgGaAloD0MIkgiNYOPKFsCUhpRSlGgVSzJoFkdAuXPXicXm/3V9lChoBmgJaA9DCJfiqrLv6hTAlIaUUpRoFUsyaBZHQLlzs+WGATZ1fZQoaAZoCWgPQwhd3bHYJlUVwJSGlFKUaBVLMmgWR0C5c48N2C/XdX2UKGgGaAloD0MIqvQTzm7tC8CUhpRSlGgVSzJoFkdAuXSFZs9B8nV9lChoBmgJaA9DCAbVBieiPxHAlIaUUpRoFUsyaBZHQLl0YdI5HVh1fZQoaAZoCWgPQwj+mxcnvpoXwJSGlFKUaBVLMmgWR0C5dD4y9EkTdX2UKGgGaAloD0MIdZMYBFZOGMCUhpRSlGgVSzJoFkdAuXQZYuCf6HV9lChoBmgJaA9DCNGxg0pcJxjAlIaUUpRoFUsyaBZHQLl1MjG1hLJ1fZQoaAZoCWgPQwg7Oq5GdpUWwJSGlFKUaBVLMmgWR0C5dQ8cIZ62dX2UKGgGaAloD0MI6s9+pIicIMCUhpRSlGgVSzJoFkdAuXTrkq+ajXV9lChoBmgJaA9DCAorFVRU/RXAlIaUUpRoFUsyaBZHQLl0xxlg+hZ1fZQoaAZoCWgPQwgVONkG7kASwJSGlFKUaBVLMmgWR0C5deQkPczqdX2UKGgGaAloD0MIDag3o+Y7F8CUhpRSlGgVSzJoFkdAuXXAscyWRnV9lChoBmgJaA9DCEq2upwScArAlIaUUpRoFUsyaBZHQLl1nZ0Syt51fZQoaAZoCWgPQwhy3ZTyWmkIwJSGlFKUaBVLMmgWR0C5dXjhLoOhdX2UKGgGaAloD0MIxQCJJlDkF8CUhpRSlGgVSzJoFkdAuXZ8Wac7Q3V9lChoBmgJaA9DCBR5knTNdBvAlIaUUpRoFUsyaBZHQLl2WOgQHzJ1fZQoaAZoCWgPQwhjKCfaVQgPwJSGlFKUaBVLMmgWR0C5djVx0dR0dX2UKGgGaAloD0MIuTXptkTuEcCUhpRSlGgVSzJoFkdAuXYQjW07bXV9lChoBmgJaA9DCCofgqrRKxLAlIaUUpRoFUsyaBZHQLl3Mqxkd3l1fZQoaAZoCWgPQwghOgSOBKoawJSGlFKUaBVLMmgWR0C5dw86RyOrdX2UKGgGaAloD0MI9YO6SKFsDcCUhpRSlGgVSzJoFkdAuXbsIv8IiXV9lChoBmgJaA9DCJtZSwFpPw3AlIaUUpRoFUsyaBZHQLl2x7TDwYt1fZQoaAZoCWgPQwieRIR/EbQMwJSGlFKUaBVLMmgWR0C5eBf6CUX6dX2UKGgGaAloD0MIopdRLLdkF8CUhpRSlGgVSzJoFkdAuXf1KkEcKnV9lChoBmgJaA9DCC17Etic8xTAlIaUUpRoFUsyaBZHQLl30cFhXsB1fZQoaAZoCWgPQwiJJ7uZ0Z8QwJSGlFKUaBVLMmgWR0C5d63IuGsWdX2UKGgGaAloD0MI7tCwGHUtCsCUhpRSlGgVSzJoFkdAuXkt+OOsDHV9lChoBmgJaA9DCIAqbtxi3hbAlIaUUpRoFUsyaBZHQLl5CuV5a/11fZQoaAZoCWgPQwi6vDlcq50TwJSGlFKUaBVLMmgWR0C5eOeEh7mddX2UKGgGaAloD0MIhlrTvOMUF8CUhpRSlGgVSzJoFkdAuXjDywwCbXV9lChoBmgJaA9DCHwOLEfIYA3AlIaUUpRoFUsyaBZHQLl6E9kjHGV1fZQoaAZoCWgPQwjQe2MIAA4SwJSGlFKUaBVLMmgWR0C5efDcIqsmdX2UKGgGaAloD0MIH73hPnK7FMCUhpRSlGgVSzJoFkdAuXnNzySV4XV9lChoBmgJaA9DCK685H/yBxvAlIaUUpRoFUsyaBZHQLl5qSvC/Gl1fZQoaAZoCWgPQwgvTny1o3gUwJSGlFKUaBVLMmgWR0C5ev6Jyhi9dX2UKGgGaAloD0MIMuauJeQDDMCUhpRSlGgVSzJoFkdAuXrbcZccEXV9lChoBmgJaA9DCC5ZFeEmoxbAlIaUUpRoFUsyaBZHQLl6uBTXJ5p1fZQoaAZoCWgPQwhprWhznIsZwJSGlFKUaBVLMmgWR0C5epOVopQUdX2UKGgGaAloD0MIOnZQiesIG8CUhpRSlGgVSzJoFkdAuXwn83uNP3V9lChoBmgJaA9DCH+jHTf8zgvAlIaUUpRoFUsyaBZHQLl8BRceKbd1fZQoaAZoCWgPQwjZQLrYtBIQwJSGlFKUaBVLMmgWR0C5e+LEtNBXdX2UKGgGaAloD0MIw0gvavf7EcCUhpRSlGgVSzJoFkdAuXu/PLPldXV9lChoBmgJaA9DCKuzWmCPqRnAlIaUUpRoFUsyaBZHQLl9CBYmsvJ1fZQoaAZoCWgPQwjVXkTbMbUTwJSGlFKUaBVLMmgWR0C5fOSncclxdX2UKGgGaAloD0MIlnoWhPLeGsCUhpRSlGgVSzJoFkdAuXzA+Sr5qXV9lChoBmgJaA9DCCBhGLDkqhPAlIaUUpRoFUsyaBZHQLl8nEKE3851fZQoaAZoCWgPQwhYAFMGDrgRwJSGlFKUaBVLMmgWR0C5fZA5zYEodX2UKGgGaAloD0MIt+171F/vHMCUhpRSlGgVSzJoFkdAuX1sz67/XHV9lChoBmgJaA9DCChEwCFU6RXAlIaUUpRoFUsyaBZHQLl9SVHnU2F1fZQoaAZoCWgPQwiAETRmEpUIwJSGlFKUaBVLMmgWR0C5fSRkRSP2dX2UKGgGaAloD0MIF0UPfAzWAMCUhpRSlGgVSzJoFkdAuX4otXgccXV9lChoBmgJaA9DCM3qHW6HlhTAlIaUUpRoFUsyaBZHQLl+BSCOFQF1fZQoaAZoCWgPQwiXAtL+B4gfwJSGlFKUaBVLMmgWR0C5feGe6I3zdX2UKGgGaAloD0MIk4rG2t+JEsCUhpRSlGgVSzJoFkdAuX28ysS00HV9lChoBmgJaA9DCC5ZFeEmgxnAlIaUUpRoFUsyaBZHQLl+sehwl0J1fZQoaAZoCWgPQwg2dR4V/4cVwJSGlFKUaBVLMmgWR0C5fo5imVJMdX2UKGgGaAloD0MI2o0+5gMSG8CUhpRSlGgVSzJoFkdAuX5qt3fQ8nV9lChoBmgJaA9DCEjcY+lD9wHAlIaUUpRoFUsyaBZHQLl+ReLehwl1ZS4="
81
  },
82
  "ep_success_buffer": {
83
  ":type:": "<class 'collections.deque'>",
84
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
85
  },
86
- "_n_updates": 100000,
87
  "n_steps": 5,
88
  "gamma": 0.99,
89
  "gae_lambda": 1.0,
 
4
  ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
5
  "__module__": "stable_baselines3.common.policies",
6
  "__doc__": "\n MultiInputActorClass policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space (Tuple)\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Uses the CombinedExtractor\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ",
7
+ "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f55418d54c0>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc_data object at 0x7f554194bb10>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
 
41
  "_np_random": null
42
  },
43
  "n_envs": 4,
44
+ "num_timesteps": 3500000,
45
+ "_total_timesteps": 3500000,
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
+ "start_time": 1678065742746143950,
50
  "learning_rate": 0.0007,
51
  "tensorboard_log": null,
52
  "lr_schedule": {
 
55
  },
56
  "_last_obs": {
57
  ":type:": "<class 'collections.OrderedDict'>",
58
+ ":serialized:": "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",
59
+ "achieved_goal": "[[ 0.28912368 -0.03099578 0.9072719 ]\n [ 0.28912368 -0.03099578 0.9072719 ]\n [ 0.28912368 -0.03099578 0.9072719 ]\n [ 0.28912368 -0.03099578 0.9072719 ]]",
60
+ "desired_goal": "[[-1.3625802 -0.72980684 1.4486005 ]\n [-0.6914591 -1.2221434 1.100603 ]\n [-0.5403931 -1.3413442 -0.8084952 ]\n [ 1.7080245 1.1955264 0.93565965]]",
61
+ "observation": "[[ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]\n [ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]\n [ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]\n [ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]]"
62
  },
63
  "_last_episode_starts": {
64
  ":type:": "<class 'numpy.ndarray'>",
 
66
  },
67
  "_last_original_obs": {
68
  ":type:": "<class 'collections.OrderedDict'>",
69
+ ":serialized:": "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",
70
  "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]]",
71
+ "desired_goal": "[[-0.10200333 -0.1217196 0.01118304]\n [ 0.07699643 0.11512369 0.1696345 ]\n [ 0.02600976 0.04465018 0.1498927 ]\n [ 0.09552518 -0.0409553 0.14654645]]",
72
  "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]]"
73
  },
74
  "_episode_num": 0,
 
77
  "_current_progress_remaining": 0.0,
78
  "ep_info_buffer": {
79
  ":type:": "<class 'collections.deque'>",
80
+ ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIEqW9wRdGIMCUhpRSlIwBbJRLMowBdJRHQMOyeu2qkuZ1fZQoaAZoCWgPQwgdrP9zmI8MwJSGlFKUaBVLMmgWR0DDsmlTm4iHdX2UKGgGaAloD0MI/WmjOh34FcCUhpRSlGgVSzJoFkdAw7JYZWJaaHV9lChoBmgJaA9DCDEKgse3lw3AlIaUUpRoFUsyaBZHQMOyO9a2Wpt1fZQoaAZoCWgPQwgujPSidk8RwJSGlFKUaBVLMmgWR0DDsrblgc94dX2UKGgGaAloD0MILZYi+Uo4IcCUhpRSlGgVSzJoFkdAw7KlPrv9cnV9lChoBmgJaA9DCLddaK7T+B/AlIaUUpRoFUsyaBZHQMOylFKTSst1fZQoaAZoCWgPQwi4A3XKo6scwJSGlFKUaBVLMmgWR0DDsnfG+9J0dX2UKGgGaAloD0MImZ8bmrLzFMCUhpRSlGgVSzJoFkdAw7LxbILgGnV9lChoBmgJaA9DCMqLTMCvcSLAlIaUUpRoFUsyaBZHQMOy38HGCI11fZQoaAZoCWgPQwicjCrDuPMhwJSGlFKUaBVLMmgWR0DDss7V4HHFdX2UKGgGaAloD0MIXK5+bJL/BsCUhpRSlGgVSzJoFkdAw7KyV8kUsXV9lChoBmgJaA9DCCIbSBebFhDAlIaUUpRoFUsyaBZHQMOzLZfUnXx1fZQoaAZoCWgPQwgWpYRgVX0QwJSGlFKUaBVLMmgWR0DDsxvxe9i+dX2UKGgGaAloD0MI4ZnQJLFECsCUhpRSlGgVSzJoFkdAw7MLBInSfHV9lChoBmgJaA9DCE9cjlcgaiHAlIaUUpRoFUsyaBZHQMOy7nd43WF1fZQoaAZoCWgPQwisOUAwR28QwJSGlFKUaBVLMmgWR0DDs2wWpIczdX2UKGgGaAloD0MITMPwETH1FcCUhpRSlGgVSzJoFkdAw7NabedkKHV9lChoBmgJaA9DCNnNjH40XBLAlIaUUpRoFUsyaBZHQMOzSYEnssx1fZQoaAZoCWgPQwhh+8kYH2YMwJSGlFKUaBVLMmgWR0DDsyz0Bfa6dX2UKGgGaAloD0MISzs1lxu8IcCUhpRSlGgVSzJoFkdAw7OpEIgNgHV9lChoBmgJaA9DCIUIOIQqtQzAlIaUUpRoFUsyaBZHQMOzl24d6s11fZQoaAZoCWgPQwjn/1VHjrQXwJSGlFKUaBVLMmgWR0DDs4aErXlKdX2UKGgGaAloD0MIT8x6MZQzEsCUhpRSlGgVSzJoFkdAw7Np9deIEnV9lChoBmgJaA9DCMwollta/RjAlIaUUpRoFUsyaBZHQMOz4wSi/PB1fZQoaAZoCWgPQwj0TZoGRdMcwJSGlFKUaBVLMmgWR0DDs9FW+49YdX2UKGgGaAloD0MICmXh62u9IcCUhpRSlGgVSzJoFkdAw7PAZssQNHV9lChoBmgJaA9DCG/zxklhPh3AlIaUUpRoFUsyaBZHQMOzo9a2Wpt1fZQoaAZoCWgPQwhcd/NUh7wjwJSGlFKUaBVLMmgWR0DDtB2Y6XBydX2UKGgGaAloD0MIo5BkVu/4IMCUhpRSlGgVSzJoFkdAw7QL8aXKKnV9lChoBmgJaA9DCCEeiZen8wvAlIaUUpRoFUsyaBZHQMOz+wM6RyR1fZQoaAZoCWgPQwiOdAZGXsYXwJSGlFKUaBVLMmgWR0DDs96E12q2dX2UKGgGaAloD0MICisVVFStGMCUhpRSlGgVSzJoFkdAw7RYZtNzsHV9lChoBmgJaA9DCPw2xHjN6xPAlIaUUpRoFUsyaBZHQMO0RsHB1tB1fZQoaAZoCWgPQwgFGJY/3yYTwJSGlFKUaBVLMmgWR0DDtDXVkMCtdX2UKGgGaAloD0MIxxNBnIdDG8CUhpRSlGgVSzJoFkdAw7QZR0EHMXV9lChoBmgJaA9DCGKjrN9MbCLAlIaUUpRoFUsyaBZHQMO0liNCJGh1fZQoaAZoCWgPQwiWXwZjRLIQwJSGlFKUaBVLMmgWR0DDtIR6fJ3gdX2UKGgGaAloD0MImGpmLQWEEcCUhpRSlGgVSzJoFkdAw7Rzj0cwQHV9lChoBmgJaA9DCByXcVMD3STAlIaUUpRoFUsyaBZHQMO0VwEQoTh1fZQoaAZoCWgPQwh96IL6lhkbwJSGlFKUaBVLMmgWR0DDtNHt2LYPdX2UKGgGaAloD0MI2NR5VPwfF8CUhpRSlGgVSzJoFkdAw7TARsdkrnV9lChoBmgJaA9DCGBXk6esthLAlIaUUpRoFUsyaBZHQMO0r14X40x1fZQoaAZoCWgPQwhxdQDEXa0WwJSGlFKUaBVLMmgWR0DDtJLRa5f/dX2UKGgGaAloD0MI4dIx5xlbDMCUhpRSlGgVSzJoFkdAw7ULuv2XcHV9lChoBmgJaA9DCKyMRj6vuA7AlIaUUpRoFUsyaBZHQMO0+hPbfxd1fZQoaAZoCWgPQwiTVnxD4RMGwJSGlFKUaBVLMmgWR0DDtOkiKR+0dX2UKGgGaAloD0MIGr/wSpJXGsCUhpRSlGgVSzJoFkdAw7TMlkYoAnV9lChoBmgJaA9DCKkR+pl6jRXAlIaUUpRoFUsyaBZHQMO1SOeJ53V1fZQoaAZoCWgPQwiILNLEOwAbwJSGlFKUaBVLMmgWR0DDtTc8mrsCdX2UKGgGaAloD0MIBr6iW68JEMCUhpRSlGgVSzJoFkdAw7UmTYdyUHV9lChoBmgJaA9DCH4czZGV1yXAlIaUUpRoFUsyaBZHQMO1CcE/0NB1fZQoaAZoCWgPQwjoEg69xYMbwJSGlFKUaBVLMmgWR0DDtYKAJ9iMdX2UKGgGaAloD0MItoR80LPJFMCUhpRSlGgVSzJoFkdAw7Vw1WsBAHV9lChoBmgJaA9DCBOZucDl8RXAlIaUUpRoFUsyaBZHQMO1X+xwAEN1fZQoaAZoCWgPQwhgdHlzuKYRwJSGlFKUaBVLMmgWR0DDtUNj3EhrdX2UKGgGaAloD0MI9PkoIy5gFMCUhpRSlGgVSzJoFkdAw7W+mj0tiHV9lChoBmgJaA9DCCRHOgMjLyDAlIaUUpRoFUsyaBZHQMO1rQ40dil1fZQoaAZoCWgPQwikpl1MM30NwJSGlFKUaBVLMmgWR0DDtZxLZi/gdX2UKGgGaAloD0MIIuAQqtSMG8CUhpRSlGgVSzJoFkdAw7V/0btJF3V9lChoBmgJaA9DCBLZB1kWLAvAlIaUUpRoFUsyaBZHQMO1+5gXuVp1fZQoaAZoCWgPQwjJ6ev5mqUXwJSGlFKUaBVLMmgWR0DDtenzasZHdX2UKGgGaAloD0MIqyNHOgMrJsCUhpRSlGgVSzJoFkdAw7XZCzC1qnV9lChoBmgJaA9DCADjGTT0DyfAlIaUUpRoFUsyaBZHQMO1vIZQ53l1fZQoaAZoCWgPQwig/N07aqwHwJSGlFKUaBVLMmgWR0DDtjkWfseGdX2UKGgGaAloD0MIn+V5cHcmI8CUhpRSlGgVSzJoFkdAw7YncW0qpnV9lChoBmgJaA9DCIcx6e+lMB3AlIaUUpRoFUsyaBZHQMO2FoyCWeJ1fZQoaAZoCWgPQwgrildZ2yQQwJSGlFKUaBVLMmgWR0DDtfoDzRQadX2UKGgGaAloD0MIkLxzKENlFMCUhpRSlGgVSzJoFkdAw7Z0GpuMuXV9lChoBmgJaA9DCIoCfSJPUhvAlIaUUpRoFUsyaBZHQMO2YpO32El1fZQoaAZoCWgPQwjgTbfsEJ8bwJSGlFKUaBVLMmgWR0DDtlGhPCVKdX2UKGgGaAloD0MIgsr49xlnHcCUhpRSlGgVSzJoFkdAw7Y1EaVD8nV9lChoBmgJaA9DCPD6zFmfMgzAlIaUUpRoFUsyaBZHQMO2rv9kz411fZQoaAZoCWgPQwhXlX1XBE8RwJSGlFKUaBVLMmgWR0DDtp1VaOghdX2UKGgGaAloD0MIQUZAhSOIIsCUhpRSlGgVSzJoFkdAw7aMaP0ZnHV9lChoBmgJaA9DCBwKn62DMxjAlIaUUpRoFUsyaBZHQMO2b98Rcu91fZQoaAZoCWgPQwhRMGMK1hgJwJSGlFKUaBVLMmgWR0DDtvNFDv3KdX2UKGgGaAloD0MIhleSPNcXDcCUhpRSlGgVSzJoFkdAw7bhze40/HV9lChoBmgJaA9DCDrMlxdgtyHAlIaUUpRoFUsyaBZHQMO20R/ustF1fZQoaAZoCWgPQwhxrIvbaFAZwJSGlFKUaBVLMmgWR0DDtrS7TUiIdX2UKGgGaAloD0MIDoP5K2SuEMCUhpRSlGgVSzJoFkdAw7dR5qM3qHV9lChoBmgJaA9DCOJWQQx0jRTAlIaUUpRoFUsyaBZHQMO3QHOB19x1fZQoaAZoCWgPQwjMQ6Z8COoOwJSGlFKUaBVLMmgWR0DDty+/DcdpdX2UKGgGaAloD0MIoG0164w/HsCUhpRSlGgVSzJoFkdAw7cTV6NVBHV9lChoBmgJaA9DCOKuXkVGpwfAlIaUUpRoFUsyaBZHQMO3r7dadMF1fZQoaAZoCWgPQwjRWzy850AZwJSGlFKUaBVLMmgWR0DDt548W9DhdX2UKGgGaAloD0MI9dvXgXO2EcCUhpRSlGgVSzJoFkdAw7eNfv4M4XV9lChoBmgJaA9DCILHt3cN2hbAlIaUUpRoFUsyaBZHQMO3cSh8IAx1fZQoaAZoCWgPQwg+lGjJ40kVwJSGlFKUaBVLMmgWR0DDuAy3EyckdX2UKGgGaAloD0MIBYiCGVNYIcCUhpRSlGgVSzJoFkdAw7f7O9FnZnV9lChoBmgJaA9DCA73kVuTfhjAlIaUUpRoFUsyaBZHQMO36nf/FR51fZQoaAZoCWgPQwhJgJpatjYRwJSGlFKUaBVLMmgWR0DDt84aP0ZndX2UKGgGaAloD0MI8KKvIM3oH8CUhpRSlGgVSzJoFkdAw7hwqWkadnV9lChoBmgJaA9DCKyNsRNe8hDAlIaUUpRoFUsyaBZHQMO4XyhBZ6l1fZQoaAZoCWgPQwiY+KOoM9cWwJSGlFKUaBVLMmgWR0DDuE6WTot+dX2UKGgGaAloD0MIgZTYtb2dEsCUhpRSlGgVSzJoFkdAw7gyNlRP43V9lChoBmgJaA9DCCL/zCA+8BjAlIaUUpRoFUsyaBZHQMO406BI4ER1fZQoaAZoCWgPQwhsCmR2Fg0YwJSGlFKUaBVLMmgWR0DDuMIgNgBtdX2UKGgGaAloD0MIIEWduYfsJcCUhpRSlGgVSzJoFkdAw7ixWgezU3V9lChoBmgJaA9DCJBKsaNxyArAlIaUUpRoFUsyaBZHQMO4lRhDw6R1ZS4="
81
  },
82
  "ep_success_buffer": {
83
  ":type:": "<class 'collections.deque'>",
84
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
85
  },
86
+ "_n_updates": 175000,
87
  "n_steps": 5,
88
  "gamma": 0.99,
89
  "gae_lambda": 1.0,
a2c-PandaReachDense-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:dea13d117971283f808758bb474e12e661b4b408f98da03452aa617e7ab02dc5
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:62249ee93b80b380cffd1e9689bb21acf65585c9429d413c829c7d06ed8fe46d
3
  size 44734
a2c-PandaReachDense-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3b3d8122d850227f90629699842fae997e44e236a0a0e4449d5d23410c50a86f
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4073fa02350401c6640328ea06669f7c6af8600df1e3a574491557416af88caf
3
  size 46014
config.json CHANGED
@@ -1 +1 @@
1
- {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n MultiInputActorClass policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space (Tuple)\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Uses the CombinedExtractor\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f4de623e3a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f4de6238a80>"}, "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}}, "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, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677857788438794729, "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": "[[ 0.4294525 -0.03713895 0.47747174]\n [ 0.4294525 -0.03713895 0.47747174]\n [ 0.4294525 -0.03713895 0.47747174]\n [ 0.4294525 -0.03713895 0.47747174]]", "desired_goal": "[[ 1.0690753 1.0014292 1.06238 ]\n [ 1.451435 -0.27171326 -1.0944291 ]\n [-1.4046277 0.88951224 1.4048245 ]\n [ 0.95129913 -0.40849248 -0.38766178]]", "observation": "[[ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]\n [ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]\n [ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]\n [ 0.4294525 -0.03713895 0.47747174 0.02030658 -0.00232174 0.01086124]]"}, "_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": "[[ 0.04787081 0.04199878 0.19365026]\n [ 0.09933884 -0.0218574 0.09626509]\n [-0.14177327 -0.08077914 0.24229862]\n [ 0.10212301 -0.00977324 0.07329365]]", "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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIZ7eWyXAcBMCUhpRSlIwBbJRLMowBdJRHQLlt8CjUNKB1fZQoaAZoCWgPQwhSSDKrd/gSwJSGlFKUaBVLMmgWR0C5bc0SElE7dX2UKGgGaAloD0MI9fOmIhWmDcCUhpRSlGgVSzJoFkdAuW2p4dIXj3V9lChoBmgJaA9DCEyOO6WDVRjAlIaUUpRoFUsyaBZHQLlthQO4G2V1fZQoaAZoCWgPQwirWWd8X0wQwJSGlFKUaBVLMmgWR0C5bowvpQk5dX2UKGgGaAloD0MIuTZUjPPHEMCUhpRSlGgVSzJoFkdAuW5orupjt3V9lChoBmgJaA9DCEuwOJz5ZRDAlIaUUpRoFUsyaBZHQLluRPFvQ4V1fZQoaAZoCWgPQwiRgNHlzXERwJSGlFKUaBVLMmgWR0C5biB6fJ3gdX2UKGgGaAloD0MINCxGXWtvGcCUhpRSlGgVSzJoFkdAuW8jqUu+RHV9lChoBmgJaA9DCFSQn41chxPAlIaUUpRoFUsyaBZHQLlvACF9KEp1fZQoaAZoCWgPQwjzVIfcDGcXwJSGlFKUaBVLMmgWR0C5btx2nsLOdX2UKGgGaAloD0MIkloomZz6BMCUhpRSlGgVSzJoFkdAuW63okiUxHV9lChoBmgJaA9DCF9dFajF4B7AlIaUUpRoFUsyaBZHQLlvwUDuBtl1fZQoaAZoCWgPQwiismFNZUkhwJSGlFKUaBVLMmgWR0C5b53LaEi/dX2UKGgGaAloD0MIiEfi5el8D8CUhpRSlGgVSzJoFkdAuW96hwl0HXV9lChoBmgJaA9DCDBMpgpG5QrAlIaUUpRoFUsyaBZHQLlvVaiKziV1fZQoaAZoCWgPQwjXpNsSuVAdwJSGlFKUaBVLMmgWR0C5cGpUxVQzdX2UKGgGaAloD0MIYWu28pKvFcCUhpRSlGgVSzJoFkdAuXBHbO/tY3V9lChoBmgJaA9DCKmkTkATERLAlIaUUpRoFUsyaBZHQLlwJFt8/lh1fZQoaAZoCWgPQwhGs7J9yLsUwJSGlFKUaBVLMmgWR0C5b/9+b3GodX2UKGgGaAloD0MIGoums5OBC8CUhpRSlGgVSzJoFkdAuXD8SIxgzHV9lChoBmgJaA9DCE5DVOHPAB3AlIaUUpRoFUsyaBZHQLlw2Mm4RVZ1fZQoaAZoCWgPQwi7YHDNHX0cwJSGlFKUaBVLMmgWR0C5cLUQkHD8dX2UKGgGaAloD0MIlbvP8dECD8CUhpRSlGgVSzJoFkdAuXCQN8VpK3V9lChoBmgJaA9DCNLj9zb9uQ7AlIaUUpRoFUsyaBZHQLlxlVJtix51fZQoaAZoCWgPQwhOgGH5800OwJSGlFKUaBVLMmgWR0C5cXHwPRRedX2UKGgGaAloD0MIdej0vBu7JcCUhpRSlGgVSzJoFkdAuXFOVJL/THV9lChoBmgJaA9DCPusMlNaLxDAlIaUUpRoFUsyaBZHQLlxKenAIpp1fZQoaAZoCWgPQwj8pUV9kisUwJSGlFKUaBVLMmgWR0C5ckKh6By0dX2UKGgGaAloD0MID167tOFwB8CUhpRSlGgVSzJoFkdAuXIfjDKoynV9lChoBmgJaA9DCFLUmXtI6BHAlIaUUpRoFUsyaBZHQLlx+/WDpTx1fZQoaAZoCWgPQwgzbf/KSvMJwJSGlFKUaBVLMmgWR0C5cdd4eLeidX2UKGgGaAloD0MIIlM+BFVDG8CUhpRSlGgVSzJoFkdAuXLexkd3jnV9lChoBmgJaA9DCCqMLQQ5qBrAlIaUUpRoFUsyaBZHQLlyu0gKWs11fZQoaAZoCWgPQwjF/x1RofoGwJSGlFKUaBVLMmgWR0C5cpgGGEf1dX2UKGgGaAloD0MIvB+3Xz75DMCUhpRSlGgVSzJoFkdAuXJzKp1ifHV9lChoBmgJaA9DCI+mejL/qAbAlIaUUpRoFUsyaBZHQLlzdNR3u/l1fZQoaAZoCWgPQwhmMbH5uLYFwJSGlFKUaBVLMmgWR0C5c1HARChOdX2UKGgGaAloD0MIIywq4nTSHcCUhpRSlGgVSzJoFkdAuXMuD8LronV9lChoBmgJaA9DCAHdlzPbRRLAlIaUUpRoFUsyaBZHQLlzCVfeDWd1fZQoaAZoCWgPQwgm++dpwMANwJSGlFKUaBVLMmgWR0C5c/r04BFNdX2UKGgGaAloD0MIkgiNYOPKFsCUhpRSlGgVSzJoFkdAuXPXicXm/3V9lChoBmgJaA9DCJfiqrLv6hTAlIaUUpRoFUsyaBZHQLlzs+WGATZ1fZQoaAZoCWgPQwhd3bHYJlUVwJSGlFKUaBVLMmgWR0C5c48N2C/XdX2UKGgGaAloD0MIqvQTzm7tC8CUhpRSlGgVSzJoFkdAuXSFZs9B8nV9lChoBmgJaA9DCAbVBieiPxHAlIaUUpRoFUsyaBZHQLl0YdI5HVh1fZQoaAZoCWgPQwj+mxcnvpoXwJSGlFKUaBVLMmgWR0C5dD4y9EkTdX2UKGgGaAloD0MIdZMYBFZOGMCUhpRSlGgVSzJoFkdAuXQZYuCf6HV9lChoBmgJaA9DCNGxg0pcJxjAlIaUUpRoFUsyaBZHQLl1MjG1hLJ1fZQoaAZoCWgPQwg7Oq5GdpUWwJSGlFKUaBVLMmgWR0C5dQ8cIZ62dX2UKGgGaAloD0MI6s9+pIicIMCUhpRSlGgVSzJoFkdAuXTrkq+ajXV9lChoBmgJaA9DCAorFVRU/RXAlIaUUpRoFUsyaBZHQLl0xxlg+hZ1fZQoaAZoCWgPQwgVONkG7kASwJSGlFKUaBVLMmgWR0C5deQkPczqdX2UKGgGaAloD0MIDag3o+Y7F8CUhpRSlGgVSzJoFkdAuXXAscyWRnV9lChoBmgJaA9DCEq2upwScArAlIaUUpRoFUsyaBZHQLl1nZ0Syt51fZQoaAZoCWgPQwhy3ZTyWmkIwJSGlFKUaBVLMmgWR0C5dXjhLoOhdX2UKGgGaAloD0MIxQCJJlDkF8CUhpRSlGgVSzJoFkdAuXZ8Wac7Q3V9lChoBmgJaA9DCBR5knTNdBvAlIaUUpRoFUsyaBZHQLl2WOgQHzJ1fZQoaAZoCWgPQwhjKCfaVQgPwJSGlFKUaBVLMmgWR0C5djVx0dR0dX2UKGgGaAloD0MIuTXptkTuEcCUhpRSlGgVSzJoFkdAuXYQjW07bXV9lChoBmgJaA9DCCofgqrRKxLAlIaUUpRoFUsyaBZHQLl3Mqxkd3l1fZQoaAZoCWgPQwghOgSOBKoawJSGlFKUaBVLMmgWR0C5dw86RyOrdX2UKGgGaAloD0MI9YO6SKFsDcCUhpRSlGgVSzJoFkdAuXbsIv8IiXV9lChoBmgJaA9DCJtZSwFpPw3AlIaUUpRoFUsyaBZHQLl2x7TDwYt1fZQoaAZoCWgPQwieRIR/EbQMwJSGlFKUaBVLMmgWR0C5eBf6CUX6dX2UKGgGaAloD0MIopdRLLdkF8CUhpRSlGgVSzJoFkdAuXf1KkEcKnV9lChoBmgJaA9DCC17Etic8xTAlIaUUpRoFUsyaBZHQLl30cFhXsB1fZQoaAZoCWgPQwiJJ7uZ0Z8QwJSGlFKUaBVLMmgWR0C5d63IuGsWdX2UKGgGaAloD0MI7tCwGHUtCsCUhpRSlGgVSzJoFkdAuXkt+OOsDHV9lChoBmgJaA9DCIAqbtxi3hbAlIaUUpRoFUsyaBZHQLl5CuV5a/11fZQoaAZoCWgPQwi6vDlcq50TwJSGlFKUaBVLMmgWR0C5eOeEh7mddX2UKGgGaAloD0MIhlrTvOMUF8CUhpRSlGgVSzJoFkdAuXjDywwCbXV9lChoBmgJaA9DCHwOLEfIYA3AlIaUUpRoFUsyaBZHQLl6E9kjHGV1fZQoaAZoCWgPQwjQe2MIAA4SwJSGlFKUaBVLMmgWR0C5efDcIqsmdX2UKGgGaAloD0MIH73hPnK7FMCUhpRSlGgVSzJoFkdAuXnNzySV4XV9lChoBmgJaA9DCK685H/yBxvAlIaUUpRoFUsyaBZHQLl5qSvC/Gl1fZQoaAZoCWgPQwgvTny1o3gUwJSGlFKUaBVLMmgWR0C5ev6Jyhi9dX2UKGgGaAloD0MIMuauJeQDDMCUhpRSlGgVSzJoFkdAuXrbcZccEXV9lChoBmgJaA9DCC5ZFeEmoxbAlIaUUpRoFUsyaBZHQLl6uBTXJ5p1fZQoaAZoCWgPQwhprWhznIsZwJSGlFKUaBVLMmgWR0C5epOVopQUdX2UKGgGaAloD0MIOnZQiesIG8CUhpRSlGgVSzJoFkdAuXwn83uNP3V9lChoBmgJaA9DCH+jHTf8zgvAlIaUUpRoFUsyaBZHQLl8BRceKbd1fZQoaAZoCWgPQwjZQLrYtBIQwJSGlFKUaBVLMmgWR0C5e+LEtNBXdX2UKGgGaAloD0MIw0gvavf7EcCUhpRSlGgVSzJoFkdAuXu/PLPldXV9lChoBmgJaA9DCKuzWmCPqRnAlIaUUpRoFUsyaBZHQLl9CBYmsvJ1fZQoaAZoCWgPQwjVXkTbMbUTwJSGlFKUaBVLMmgWR0C5fOSncclxdX2UKGgGaAloD0MIlnoWhPLeGsCUhpRSlGgVSzJoFkdAuXzA+Sr5qXV9lChoBmgJaA9DCCBhGLDkqhPAlIaUUpRoFUsyaBZHQLl8nEKE3851fZQoaAZoCWgPQwhYAFMGDrgRwJSGlFKUaBVLMmgWR0C5fZA5zYEodX2UKGgGaAloD0MIt+171F/vHMCUhpRSlGgVSzJoFkdAuX1sz67/XHV9lChoBmgJaA9DCChEwCFU6RXAlIaUUpRoFUsyaBZHQLl9SVHnU2F1fZQoaAZoCWgPQwiAETRmEpUIwJSGlFKUaBVLMmgWR0C5fSRkRSP2dX2UKGgGaAloD0MIF0UPfAzWAMCUhpRSlGgVSzJoFkdAuX4otXgccXV9lChoBmgJaA9DCM3qHW6HlhTAlIaUUpRoFUsyaBZHQLl+BSCOFQF1fZQoaAZoCWgPQwiXAtL+B4gfwJSGlFKUaBVLMmgWR0C5feGe6I3zdX2UKGgGaAloD0MIk4rG2t+JEsCUhpRSlGgVSzJoFkdAuX28ysS00HV9lChoBmgJaA9DCC5ZFeEmgxnAlIaUUpRoFUsyaBZHQLl+sehwl0J1fZQoaAZoCWgPQwg2dR4V/4cVwJSGlFKUaBVLMmgWR0C5fo5imVJMdX2UKGgGaAloD0MI2o0+5gMSG8CUhpRSlGgVSzJoFkdAuX5qt3fQ8nV9lChoBmgJaA9DCEjcY+lD9wHAlIaUUpRoFUsyaBZHQLl+ReLehwl1ZS4="}, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "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 0x7f55418d54c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f554194bb10>"}, "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}}, "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, "num_timesteps": 3500000, "_total_timesteps": 3500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678065742746143950, "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": "[[ 0.28912368 -0.03099578 0.9072719 ]\n [ 0.28912368 -0.03099578 0.9072719 ]\n [ 0.28912368 -0.03099578 0.9072719 ]\n [ 0.28912368 -0.03099578 0.9072719 ]]", "desired_goal": "[[-1.3625802 -0.72980684 1.4486005 ]\n [-0.6914591 -1.2221434 1.100603 ]\n [-0.5403931 -1.3413442 -0.8084952 ]\n [ 1.7080245 1.1955264 0.93565965]]", "observation": "[[ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]\n [ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]\n [ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]\n [ 0.28912368 -0.03099578 0.9072719 0.03138408 -0.00980784 0.03731506]]"}, "_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": "[[-0.10200333 -0.1217196 0.01118304]\n [ 0.07699643 0.11512369 0.1696345 ]\n [ 0.02600976 0.04465018 0.1498927 ]\n [ 0.09552518 -0.0409553 0.14654645]]", "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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 175000, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "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": -4.533770785015077, "std_reward": 2.047509176464814, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-03T17:25:19.169473"}
 
1
+ {"mean_reward": -7.021584820188582, "std_reward": 1.6769376111040981, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-06T04:22:37.750577"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:76dda43b0c9fb764aa99581a5d20444591646ac5bcbfa85d83eb4dc4c3d13f7e
3
  size 3056
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:db44155f606ccfc0bb80490d6c6fe860ec1b5cb46f4b2bef1f2611cf0b011952
3
  size 3056