Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -4.10 +/- 0.83
+      value: -0.83 +/- 0.23
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:000c4c7f7ca5126dd6d8554f38752ccc8d7483be78aa9d00ccbd0a68372a9dca
-size 107987
+oid sha256:1864e536f85d7c31aff4913d1c8a5a31562aeda1aed53d9b6677cc1e97d8389b
+size 108009

a2c-PandaReachDense-v2/data

@@ -4,9 +4,9 @@
         ":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 0x7f6223831700>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f6805991040>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f622382f540>"
+        "_abc_impl": "<_abc_data object at 0x7f680598c5a0>"
     },
     "verbose": 1,
     "policy_kwargs": {
@@ -41,12 +41,12 @@
         "_np_random": null
     },
     "n_envs": 4,
-    "num_timesteps": 1000000,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 200000,
+    "_total_timesteps": 200000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1677450651583958722,
+    "start_time": 1677504621842411224,
     "learning_rate": 0.0007,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -55,10 +55,10 @@
     },
     "_last_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
-        "achieved_goal": "[[0.44658995 0.01268831 0.61533177]\n [0.44658995 0.01268831 0.61533177]\n [0.44658995 0.01268831 0.61533177]\n [0.44658995 0.01268831 0.61533177]]",
-        "desired_goal": "[[-1.7009639   0.6701067  -0.69615424]\n [ 1.5831363  -0.5661294  -0.801118  ]\n [ 1.1390108   0.65663755  1.3103702 ]\n [ 0.81197417 -0.81317407 -0.76965785]]",
-        "observation": "[[0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]\n [0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]\n [0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]\n [0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]]"
+        ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAcVSzPilUmjzr3wY/cVSzPilUmjzr3wY/cVSzPilUmjzr3wY/cVSzPilUmjzr3wY/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAYlRrvpNovD8ZNKa/dPB7v85i/Dvumsm9rj8Jv+1c0b9lIUg/tzWaP5QNdb9kPsw/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAABxVLM+KVSaPOvfBj/wCHe8MSV7utT1sjtxVLM+KVSaPOvfBj/wCHe8MSV7utT1sjtxVLM+KVSaPOvfBj/wCHe8MSV7utT1sjtxVLM+KVSaPOvfBj/wCHe8MSV7utT1sjuUaA5LBEsGhpRoEnSUUpR1Lg==",
+        "achieved_goal": "[[0.3502536  0.01883896 0.5268542 ]\n [0.3502536  0.01883896 0.5268542 ]\n [0.3502536  0.01883896 0.5268542 ]\n [0.3502536  0.01883896 0.5268542 ]]",
+        "desired_goal": "[[-0.22981408  1.4719414  -1.2984649 ]\n [-0.9841378   0.00770221 -0.09844004]\n [-0.5361279  -1.6356484   0.78175956]\n [ 1.2047642  -0.95723844  1.595654  ]]",
+        "observation": "[[ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]\n [ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]\n [ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]\n [ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,9 +66,9 @@
     },
     "_last_original_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
+        ":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": "[[-0.09064643 -0.08556265  0.20701161]\n [ 0.04067855 -0.04399592  0.14200535]\n [ 0.0306814   0.06955864  0.12126099]\n [-0.10914285  0.06688796  0.0155292 ]]",
+        "desired_goal": "[[ 0.13009407 -0.11506713  0.2179114 ]\n [-0.08969056  0.04131708  0.28805128]\n [-0.12902425  0.06372954  0.17278488]\n [-0.02625789  0.07794904  0.24368332]]",
         "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,
@@ -77,13 +77,13 @@
     "_current_progress_remaining": 0.0,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIeXQjLCoi+b+UhpRSlIwBbJRLMowBdJRHQIF27ThHbyp1fZQoaAZoCWgPQwiV7q6zIf/3v5SGlFKUaBVLMmgWR0CBdfeMQ2/BdX2UKGgGaAloD0MIeR7cnbUb9b+UhpRSlGgVSzJoFkdAgXUG0u14PnV9lChoBmgJaA9DCBIXgEbp0vW/lIaUUpRoFUsyaBZHQIF0BjSXt0F1fZQoaAZoCWgPQwipiNNJtnr1v5SGlFKUaBVLMmgWR0CBfaKVpsXSdX2UKGgGaAloD0MIOslWl1OC9L+UhpRSlGgVSzJoFkdAgXyuTibUgHV9lChoBmgJaA9DCG9FYoIavvC/lIaUUpRoFUsyaBZHQIF7uz8gpz91fZQoaAZoCWgPQwhkkpGzsKfwv5SGlFKUaBVLMmgWR0CBeroX9BKMdX2UKGgGaAloD0MIc51GWiov87+UhpRSlGgVSzJoFkdAgYRC9h7VrnV9lChoBmgJaA9DCFgczvxqjva/lIaUUpRoFUsyaBZHQIGDTfzjFQ51fZQoaAZoCWgPQwgCnN7F+7H2v5SGlFKUaBVLMmgWR0CBglvBrN4adX2UKGgGaAloD0MIEqPnFrqS+L+UhpRSlGgVSzJoFkdAgYFbhWHUMHV9lChoBmgJaA9DCMXkDTDzHfK/lIaUUpRoFUsyaBZHQIGKHHPu5SZ1fZQoaAZoCWgPQwjZI9QMqWL3v5SGlFKUaBVLMmgWR0CBiSSaEzwddX2UKGgGaAloD0MIMCx/vi3Y8r+UhpRSlGgVSzJoFkdAgYgvPC2tuHV9lChoBmgJaA9DCLQ9esN95O+/lIaUUpRoFUsyaBZHQIGHK+evpyJ1fZQoaAZoCWgPQwihLHx9rYvxv5SGlFKUaBVLMmgWR0CBjfzzVc2SdX2UKGgGaAloD0MIFQDjGTQ08b+UhpRSlGgVSzJoFkdAgY0FPacqfHV9lChoBmgJaA9DCD22ZcBZCvG/lIaUUpRoFUsyaBZHQIGMD8rI5o51fZQoaAZoCWgPQwj75v7qcR/zv5SGlFKUaBVLMmgWR0CBiwyyD7IldX2UKGgGaAloD0MIRS+jWG6p8L+UhpRSlGgVSzJoFkdAgZHuM2m52HV9lChoBmgJaA9DCM+7saAwaPe/lIaUUpRoFUsyaBZHQIGQ9awD/2l1fZQoaAZoCWgPQwhdcAZ/v1jxv5SGlFKUaBVLMmgWR0CBj//iHZbqdX2UKGgGaAloD0MIsky/RLz177+UhpRSlGgVSzJoFkdAgY782rGR3nV9lChoBmgJaA9DCM2wUdZvpu6/lIaUUpRoFUsyaBZHQIGV35N47ih1fZQoaAZoCWgPQwigxr35DZP2v5SGlFKUaBVLMmgWR0CBlOdDpkf+dX2UKGgGaAloD0MImFDB4QUR9b+UhpRSlGgVSzJoFkdAgZPzKkl/pnV9lChoBmgJaA9DCO1imuleJ/G/lIaUUpRoFUsyaBZHQIGS76rNnoR1fZQoaAZoCWgPQwjxDYXP1sHuv5SGlFKUaBVLMmgWR0CBmbkwvg3tdX2UKGgGaAloD0MIaOxLNh4s8b+UhpRSlGgVSzJoFkdAgZjA8B+4LHV9lChoBmgJaA9DCOJ4PgPqze2/lIaUUpRoFUsyaBZHQIGXy2+fywx1fZQoaAZoCWgPQwgxsmSO5R3yv5SGlFKUaBVLMmgWR0CBlsjdHlOodX2UKGgGaAloD0MI66f/rPmx87+UhpRSlGgVSzJoFkdAgZ2KkM1CPnV9lChoBmgJaA9DCLcKYqBrH/a/lIaUUpRoFUsyaBZHQIGck+HJtBR1fZQoaAZoCWgPQwhIwOjy5vDzv5SGlFKUaBVLMmgWR0CBm6A3kxREdX2UKGgGaAloD0MIwR4TKc3m8L+UhpRSlGgVSzJoFkdAgZqciW3Sa3V9lChoBmgJaA9DCGFsIchBCfS/lIaUUpRoFUsyaBZHQIGhYnSfDk51fZQoaAZoCWgPQwgAyAkTRrP1v5SGlFKUaBVLMmgWR0CBoGpQ1rIpdX2UKGgGaAloD0MIbJih8USQ9b+UhpRSlGgVSzJoFkdAgZ92cz67/XV9lChoBmgJaA9DCOUpq+l6YvO/lIaUUpRoFUsyaBZHQIGecytV7yB1fZQoaAZoCWgPQwiXPJ6WHzj0v5SGlFKUaBVLMmgWR0CBpVEjxCpndX2UKGgGaAloD0MIfPKwUGua8L+UhpRSlGgVSzJoFkdAgaRYhllK9XV9lChoBmgJaA9DCPzepj/70fC/lIaUUpRoFUsyaBZHQIGjY5Lh73R1fZQoaAZoCWgPQwhQ/u4dNabzv5SGlFKUaBVLMmgWR0CBomDYAbQ1dX2UKGgGaAloD0MIgIKLFTUY8r+UhpRSlGgVSzJoFkdAgakgpSaVlnV9lChoBmgJaA9DCCjXFMjsrPG/lIaUUpRoFUsyaBZHQIGoKBAfMfR1fZQoaAZoCWgPQwhJ10y+2Sbwv5SGlFKUaBVLMmgWR0CBpzJ17pmmdX2UKGgGaAloD0MId/UqMjpg8L+UhpRSlGgVSzJoFkdAgaYu4gA6uHV9lChoBmgJaA9DCDcclgZ+VPa/lIaUUpRoFUsyaBZHQIGtAmqo60Z1fZQoaAZoCWgPQwiDiNS0i+nwv5SGlFKUaBVLMmgWR0CBrAoS+QEIdX2UKGgGaAloD0MICFkWTPzR87+UhpRSlGgVSzJoFkdAgasUjLSuyXV9lChoBmgJaA9DCLLZkeo7//K/lIaUUpRoFUsyaBZHQIGqEjs2NvR1fZQoaAZoCWgPQwj8cma7Qp/1v5SGlFKUaBVLMmgWR0CBsPZ00WM1dX2UKGgGaAloD0MII0p7gy+M97+UhpRSlGgVSzJoFkdAga/90aIeo3V9lChoBmgJaA9DCGyU9ZuJ6fW/lIaUUpRoFUsyaBZHQIGvCRdQfp51fZQoaAZoCWgPQwhw0clS6330v5SGlFKUaBVLMmgWR0CBrgXa8Hv+dX2UKGgGaAloD0MI0qqWdJSD8r+UhpRSlGgVSzJoFkdAgbTsV+I/JXV9lChoBmgJaA9DCGzp0VRP5va/lIaUUpRoFUsyaBZHQIGz9CiRGMJ1fZQoaAZoCWgPQwih20sao7X1v5SGlFKUaBVLMmgWR0CBsv5cC5mRdX2UKGgGaAloD0MI8PlhhPBo8b+UhpRSlGgVSzJoFkdAgbH7rkbPyHV9lChoBmgJaA9DCEc9RKM7yPO/lIaUUpRoFUsyaBZHQIG459mYjSp1fZQoaAZoCWgPQwhTQrCqXv7wv5SGlFKUaBVLMmgWR0CBt+/W1+iKdX2UKGgGaAloD0MIUwd5PZgU8L+UhpRSlGgVSzJoFkdAgbb7gsK9f3V9lChoBmgJaA9DCDF72XbaGva/lIaUUpRoFUsyaBZHQIG1+FHrhR91fZQoaAZoCWgPQwhuTiUDQBXwv5SGlFKUaBVLMmgWR0CBvNQoCuEFdX2UKGgGaAloD0MIGEFjJlGv7r+UhpRSlGgVSzJoFkdAgbvdeyAxz3V9lChoBmgJaA9DCNoc5zbh3vW/lIaUUpRoFUsyaBZHQIG667oSteV1fZQoaAZoCWgPQwgPRYE+kafuv5SGlFKUaBVLMmgWR0CBuepVjqfOdX2UKGgGaAloD0MIjX+fceEA8L+UhpRSlGgVSzJoFkdAgcC14gRsdnV9lChoBmgJaA9DCCOe7GZGP/W/lIaUUpRoFUsyaBZHQIG/vlGPPs11fZQoaAZoCWgPQwiJYBxcOibxv5SGlFKUaBVLMmgWR0CBvsoUBXCCdX2UKGgGaAloD0MI3nTLDvGP8r+UhpRSlGgVSzJoFkdAgb3Gpda+vnV9lChoBmgJaA9DCE/qy9JOzfC/lIaUUpRoFUsyaBZHQIHEf6XSjQB1fZQoaAZoCWgPQwhkrgyqDc7tv5SGlFKUaBVLMmgWR0CBw4f4AS39dX2UKGgGaAloD0MITRB1H4DU8b+UhpRSlGgVSzJoFkdAgcKT/ZM+NnV9lChoBmgJaA9DCNCYSdQLPve/lIaUUpRoFUsyaBZHQIHBkh7mdRR1fZQoaAZoCWgPQwjPnsvUJLj1v5SGlFKUaBVLMmgWR0CByDtRekYXdX2UKGgGaAloD0MIf6KyYU3l9b+UhpRSlGgVSzJoFkdAgcdHaN+9anV9lChoBmgJaA9DCMi0No3t9fO/lIaUUpRoFUsyaBZHQIHGVnscABF1fZQoaAZoCWgPQwjlm21uTM/xv5SGlFKUaBVLMmgWR0CBxVU83dbgdX2UKGgGaAloD0MI5X0czZEV87+UhpRSlGgVSzJoFkdAgcxb+T/yXnV9lChoBmgJaA9DCHfaGhGMA/e/lIaUUpRoFUsyaBZHQIHLY/3WWhR1fZQoaAZoCWgPQwjHKTqSy7/wv5SGlFKUaBVLMmgWR0CBym8ox59mdX2UKGgGaAloD0MIXwt6bwxB97+UhpRSlGgVSzJoFkdAgclszVMEinV9lChoBmgJaA9DCFRvDWyVIPa/lIaUUpRoFUsyaBZHQIHQqTdLxqh1fZQoaAZoCWgPQwgHP3EA/f71v5SGlFKUaBVLMmgWR0CBz7IwM6RydX2UKGgGaAloD0MI/8726A337b+UhpRSlGgVSzJoFkdAgc68scyWRnV9lChoBmgJaA9DCLkZbsDnh/O/lIaUUpRoFUsyaBZHQIHNufdyksV1fZQoaAZoCWgPQwi4rMJmgMvzv5SGlFKUaBVLMmgWR0CB1PTFVDKHdX2UKGgGaAloD0MIYADhQ4lW9L+UhpRSlGgVSzJoFkdAgdP/R/mT1XV9lChoBmgJaA9DCBMPKJtyBfe/lIaUUpRoFUsyaBZHQIHTCdSVGCt1fZQoaAZoCWgPQwj5EFSNXk3xv5SGlFKUaBVLMmgWR0CB0gY5T6zmdX2UKGgGaAloD0MID0bsE0Bx8L+UhpRSlGgVSzJoFkdAgdk1lXiiqXV9lChoBmgJaA9DCGgJMgIq3PK/lIaUUpRoFUsyaBZHQIHYQNiH6/J1fZQoaAZoCWgPQwhz275H/XXzv5SGlFKUaBVLMmgWR0CB11CgsbvPdX2UKGgGaAloD0MIG70aoDTU87+UhpRSlGgVSzJoFkdAgdZRW912aHV9lChoBmgJaA9DCIAomDEFq/O/lIaUUpRoFUsyaBZHQIHffoouwot1fZQoaAZoCWgPQwgdylAVU+nzv5SGlFKUaBVLMmgWR0CB3ojIq9XcdX2UKGgGaAloD0MIUIvBw7Tv+r+UhpRSlGgVSzJoFkdAgd2aBy0a63V9lChoBmgJaA9DCLu5+NueoPG/lIaUUpRoFUsyaBZHQIHcmN5t3wF1ZS4="
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 50000,
+    "_n_updates": 10000,
     "n_steps": 5,
     "gamma": 0.99,
     "gae_lambda": 1.0,

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:005939625fc1bab3f48aea5abe1ed68f7c0056fe93f13d013485fcc5c61b3b32
+oid sha256:b4171e50a3dbdf5a8f4740ec7f2533618592cd6a5deeddb26a7ce7af33c9dc2f
 size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d9a71b10a4a33b8266bc20544df4f4851b47be7cfd9121e539fca9558e137f4e
+oid sha256:32e60d0fa10cbc9a0ba5330552e0e246875c8e906fb81595af7aab224e9d47b4
 size 46014

config.json

@@ -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 0x7f6223831700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f622382f540>"}, "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": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677450651583958722, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAcKfkPqXiTzxihh0/cKfkPqXiTzxihh0/cKfkPqXiTzxihh0/cKfkPqXiTzxihh0/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAL7nZvx2MKz8qNzK/NqTKP9vtEL8SFk2/G8uRP2YZKD82uqc/it1PPy0sUL9MCEW/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAABwp+Q+peJPPGKGHT8W+cU8kGVNO50l8Dxwp+Q+peJPPGKGHT8W+cU8kGVNO50l8Dxwp+Q+peJPPGKGHT8W+cU8kGVNO50l8Dxwp+Q+peJPPGKGHT8W+cU8kGVNO50l8DyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.44658995 0.01268831 0.61533177]\n [0.44658995 0.01268831 0.61533177]\n [0.44658995 0.01268831 0.61533177]\n [0.44658995 0.01268831 0.61533177]]", "desired_goal": "[[-1.7009639   0.6701067  -0.69615424]\n [ 1.5831363  -0.5661294  -0.801118  ]\n [ 1.1390108   0.65663755  1.3103702 ]\n [ 0.81197417 -0.81317407 -0.76965785]]", "observation": "[[0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]\n [0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]\n [0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]\n [0.44658995 0.01268831 0.61533177 0.02416662 0.00313411 0.02931481]]"}, "_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": "[[-0.09064643 -0.08556265  0.20701161]\n [ 0.04067855 -0.04399592  0.14200535]\n [ 0.0306814   0.06955864  0.12126099]\n [-0.10914285  0.06688796  0.0155292 ]]", "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": 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, "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"}}
+{"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 0x7f6805991040>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f680598c5a0>"}, "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:": "gAWVUgMAAAAAAACMD2d5bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwOZ3ltLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUaBCTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowGX3NoYXBllEsDhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFUsDhZSMAUOUdJRSlIwEaGlnaJRoHSiWDAAAAAAAAAAAACBBAAAgQQAAIEGUaBVLA4WUaCB0lFKUjA1ib3VuZGVkX2JlbG93lGgdKJYDAAAAAAAAAAEBAZRoEowCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZRoIHSUUpSMDWJvdW5kZWRfYWJvdmWUaB0olgMAAAAAAAAAAQEBlGgsSwOFlGggdJRSlIwKX25wX3JhbmRvbZROdWKMDGRlc2lyZWRfZ29hbJRoDSmBlH2UKGgQaBVoGEsDhZRoGmgdKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFUsDhZRoIHSUUpRoI2gdKJYMAAAAAAAAAAAAIEEAACBBAAAgQZRoFUsDhZRoIHSUUpRoKGgdKJYDAAAAAAAAAAEBAZRoLEsDhZRoIHSUUpRoMmgdKJYDAAAAAAAAAAEBAZRoLEsDhZRoIHSUUpRoN051YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgVaBhLBoWUaBpoHSiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBVLBoWUaCB0lFKUaCNoHSiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBVLBoWUaCB0lFKUaChoHSiWBgAAAAAAAAABAQEBAQGUaCxLBoWUaCB0lFKUaDJoHSiWBgAAAAAAAAABAQEBAQGUaCxLBoWUaCB0lFKUaDdOdWJ1aBhOaBBOaDdOdWIu", "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": 200000, "_total_timesteps": 200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677504621842411224, "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": "[[0.3502536  0.01883896 0.5268542 ]\n [0.3502536  0.01883896 0.5268542 ]\n [0.3502536  0.01883896 0.5268542 ]\n [0.3502536  0.01883896 0.5268542 ]]", "desired_goal": "[[-0.22981408  1.4719414  -1.2984649 ]\n [-0.9841378   0.00770221 -0.09844004]\n [-0.5361279  -1.6356484   0.78175956]\n [ 1.2047642  -0.95723844  1.595654  ]]", "observation": "[[ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]\n [ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]\n [ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]\n [ 0.3502536   0.01883896  0.5268542  -0.01507781 -0.00095804  0.00546143]]"}, "_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": "[[ 0.13009407 -0.11506713  0.2179114 ]\n [-0.08969056  0.04131708  0.28805128]\n [-0.12902425  0.06372954  0.17278488]\n [-0.02625789  0.07794904  0.24368332]]", "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": 10000, "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"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -4.100366414431482, "std_reward": 0.8294140467028109, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-26T23:23:56.061705"}
+{"mean_reward": -0.8293697612709365, "std_reward": 0.23121755715613185, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-27T13:52:22.211364"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6dcbfe8bf2c3c353c534b723da011cb98e65f6999e01cbf7a487632706360b54
+oid sha256:03880c440e918f0b1e971ab716ea2f9a61503cc86c226f0bcba9ccef5eff1da3
 size 3056