Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -5.47 +/- 0.85
+      value: -0.96 +/- 0.13
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:88e0bb1017387bf474eaaed799a0702db2912f58bed7e6b29cb595b961b8e570
-size 108160
+oid sha256:cd1af6a13c30e20fe89ddaef842d7829d53af2650922b0462057ab8b76b921f5
+size 107820

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 0x7fdcb4fffbe0>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f192c445a20>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fdcb5004540>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f192c43ebc0>"
     },
     "verbose": 1,
     "policy_kwargs": {
@@ -19,24 +19,24 @@
             "weight_decay": 0
         }
     },
-    "num_timesteps": 2000000,
-    "_total_timesteps": 2000000,
+    "num_timesteps": 1000000,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1686059710169089392,
-    "learning_rate": 0.0007,
+    "start_time": 1686109309060145479,
+    "learning_rate": 0.0001,
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
-        "achieved_goal": "[[ 0.4733214  -0.04792694  0.6517679 ]\n [ 0.4733214  -0.04792694  0.6517679 ]\n [ 0.4733214  -0.04792694  0.6517679 ]\n [ 0.4733214  -0.04792694  0.6517679 ]]",
-        "desired_goal": "[[-1.6794137  -0.30784553 -1.1741472 ]\n [-1.1624347  -1.5750932  -1.3608663 ]\n [-1.5637478  -1.2830522  -0.5781591 ]\n [-0.29676265 -1.1522322  -0.21134458]]",
-        "observation": "[[ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]\n [ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]\n [ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]\n [ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.3290378  -0.01346603  0.51693213]\n [ 0.3290378  -0.01346603  0.51693213]\n [ 0.3290378  -0.01346603  0.51693213]\n [ 0.3290378  -0.01346603  0.51693213]]",
+        "desired_goal": "[[ 0.32118672  0.15064485  1.4704463 ]\n [-1.452497   -0.8582549   1.2842348 ]\n [ 0.16370349  1.7068591  -1.5523418 ]\n [-1.540527    0.72935754 -1.0273156 ]]",
+        "observation": "[[ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]\n [ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]\n [ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]\n [ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -44,9 +44,9 @@
     },
     "_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": "[[ 0.02865436 -0.04687229  0.12451483]\n [ 0.07604793  0.00076422  0.03780153]\n [-0.05039664  0.14048944  0.14517054]\n [-0.11172372  0.09771094  0.28503856]]",
+        "desired_goal": "[[-0.03811824 -0.12841372  0.26661316]\n [ 0.10937514 -0.08015183  0.01882749]\n [ 0.02355029 -0.01248805  0.1263911 ]\n [ 0.10665847 -0.09319272  0.13469197]]",
         "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,
@@ -56,13 +56,13 @@
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 100000,
+    "_n_updates": 50000,
     "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:dac3e7b17761b7bb114371027c3d51c6055085892eaec6469bc1bbe3b7978881
-size 44734
+oid sha256:300fbebe19f1ffc81037be5da1ddd500f03356317b7119daa3c64b564963ea30
+size 44606

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b570780a051bb962536113d470f50f614e346170676a417ec9319e88882472b1
-size 46014
+oid sha256:3b31ddf999cfee2a7be1bfe4bf4c32be8052af7563ede7d17ae77513c2095ab5
+size 45886

a2c-PandaReachDense-v2/system_info.txt

@@ -2,6 +2,6 @@
 - Python: 3.10.11
 - Stable-Baselines3: 1.8.0
 - PyTorch: 2.0.1+cu118
-- GPU Enabled: True
+- GPU Enabled: False
 - Numpy: 1.22.4
 - Gym: 0.21.0

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 0x7fdcb4fffbe0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fdcb5004540>"}, "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": 1686059710169089392, "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": "[[ 0.4733214  -0.04792694  0.6517679 ]\n [ 0.4733214  -0.04792694  0.6517679 ]\n [ 0.4733214  -0.04792694  0.6517679 ]\n [ 0.4733214  -0.04792694  0.6517679 ]]", "desired_goal": "[[-1.6794137  -0.30784553 -1.1741472 ]\n [-1.1624347  -1.5750932  -1.3608663 ]\n [-1.5637478  -1.2830522  -0.5781591 ]\n [-0.29676265 -1.1522322  -0.21134458]]", "observation": "[[ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]\n [ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]\n [ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]\n [ 4.7332141e-01 -4.7926936e-02  6.5176791e-01 -4.7534666e-04\n  -1.4468644e-02  1.5766110e-02]]"}, "_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": "[[ 0.02865436 -0.04687229  0.12451483]\n [ 0.07604793  0.00076422  0.03780153]\n [-0.05039664  0.14048944  0.14517054]\n [-0.11172372  0.09771094  0.28503856]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIXhPSGoMOHcCUhpRSlIwBbJRLMowBdJRHQLmANkbgjyF1fZQoaAZoCWgPQwhssdtnlckTwJSGlFKUaBVLMmgWR0C5gBQ9ic5KdX2UKGgGaAloD0MIcr9DUaD/EMCUhpRSlGgVSzJoFkdAuX/x9iMHbHV9lChoBmgJaA9DCBlYx/FDBQ/AlIaUUpRoFUsyaBZHQLl/0dkJ8fF1fZQoaAZoCWgPQwgZ48PsZVsTwJSGlFKUaBVLMmgWR0C5gLEjcEeRdX2UKGgGaAloD0MItFa0Oc7tFsCUhpRSlGgVSzJoFkdAuYCO5VfeDXV9lChoBmgJaA9DCBJQ4QhSSQvAlIaUUpRoFUsyaBZHQLmAbPci4ax1fZQoaAZoCWgPQwipvvOLErQSwJSGlFKUaBVLMmgWR0C5gEzmr8zidX2UKGgGaAloD0MItcAeEylNGcCUhpRSlGgVSzJoFkdAuYEob961LXV9lChoBmgJaA9DCFSsGoS5jRrAlIaUUpRoFUsyaBZHQLmBBir1dxB1fZQoaAZoCWgPQwgewCK/fhgTwJSGlFKUaBVLMmgWR0C5gOPiLl3hdX2UKGgGaAloD0MIB7e1heeFIsCUhpRSlGgVSzJoFkdAuYDDwpe/pXV9lChoBmgJaA9DCCGsxhLWZhvAlIaUUpRoFUsyaBZHQLmBpMB6rvN1fZQoaAZoCWgPQwibyqKwiwIOwJSGlFKUaBVLMmgWR0C5gYJ+DvmYdX2UKGgGaAloD0MIXDrmPGMPFMCUhpRSlGgVSzJoFkdAuYFgOskpqnV9lChoBmgJaA9DCC0LJv4ociHAlIaUUpRoFUsyaBZHQLmBQB3iaRZ1fZQoaAZoCWgPQwiQv7SoT8IUwJSGlFKUaBVLMmgWR0C5gh5C8e0YdX2UKGgGaAloD0MIEk2giEUMF8CUhpRSlGgVSzJoFkdAuYH8BmwqzHV9lChoBmgJaA9DCM12hT5Y5hzAlIaUUpRoFUsyaBZHQLmB2cTJyQx1fZQoaAZoCWgPQwgy6ITQQbcIwJSGlFKUaBVLMmgWR0C5gbmjfvWpdX2UKGgGaAloD0MI9mIoJ9oFGMCUhpRSlGgVSzJoFkdAuYKfH4oJA3V9lChoBmgJaA9DCEFHq1rSsQfAlIaUUpRoFUsyaBZHQLmCfNA1Nxl1fZQoaAZoCWgPQwib5h2n6IgJwJSGlFKUaBVLMmgWR0C5glrojfNzdX2UKGgGaAloD0MI9rUuNUJ/C8CUhpRSlGgVSzJoFkdAuYI6x6fJ3nV9lChoBmgJaA9DCKVo5V5g1iDAlIaUUpRoFUsyaBZHQLmDGUGFBY51fZQoaAZoCWgPQwjPTDCcaxgXwJSGlFKUaBVLMmgWR0C5gvb9/BnBdX2UKGgGaAloD0MINbQB2IBID8CUhpRSlGgVSzJoFkdAuYLUu6ErXnV9lChoBmgJaA9DCM5xbhPuFQvAlIaUUpRoFUsyaBZHQLmCtKwY+B91fZQoaAZoCWgPQwhFgNO7eF8LwJSGlFKUaBVLMmgWR0C5g5qxC6YmdX2UKGgGaAloD0MIZr/udOdxIMCUhpRSlGgVSzJoFkdAuYN4c1fmcXV9lChoBmgJaA9DCC7HKxA9WRTAlIaUUpRoFUsyaBZHQLmDVkoWpId1fZQoaAZoCWgPQwhZUYNpGC4QwJSGlFKUaBVLMmgWR0C5gzYuoP07dX2UKGgGaAloD0MI/pyC/GyEI8CUhpRSlGgVSzJoFkdAuYQZPVNHpnV9lChoBmgJaA9DCMri/iPTUSPAlIaUUpRoFUsyaBZHQLmD9v8qFyt1fZQoaAZoCWgPQwh4QxoVOLkJwJSGlFKUaBVLMmgWR0C5g9UpEx7BdX2UKGgGaAloD0MI1EZ1OpCFGMCUhpRSlGgVSzJoFkdAuYO1Gsmv4nV9lChoBmgJaA9DCOCBAYQPdRDAlIaUUpRoFUsyaBZHQLmEl0tAcDN1fZQoaAZoCWgPQwjw/Q3aq88VwJSGlFKUaBVLMmgWR0C5hHUNz8xcdX2UKGgGaAloD0MImj+mtWncHsCUhpRSlGgVSzJoFkdAuYRSwnpjc3V9lChoBmgJaA9DCE8kmGpmfRHAlIaUUpRoFUsyaBZHQLmEMq7iADt1fZQoaAZoCWgPQwigxVIkX/kQwJSGlFKUaBVLMmgWR0C5hRDlLeyidX2UKGgGaAloD0MIy9jQzf5gHMCUhpRSlGgVSzJoFkdAuYTuuuA7P3V9lChoBmgJaA9DCKpFRDF5IwfAlIaUUpRoFUsyaBZHQLmEzHim2st1fZQoaAZoCWgPQwhuaMpOPwgOwJSGlFKUaBVLMmgWR0C5hKxfrrxBdX2UKGgGaAloD0MIhqqYSj8RF8CUhpRSlGgVSzJoFkdAuYWKXY150XV9lChoBmgJaA9DCEvmWN5VPxHAlIaUUpRoFUsyaBZHQLmFaA6uGK11fZQoaAZoCWgPQwiGcqJdhWQUwJSGlFKUaBVLMmgWR0C5hUW+TNdJdX2UKGgGaAloD0MIYhBYObRIIMCUhpRSlGgVSzJoFkdAuYUltj0+T3V9lChoBmgJaA9DCBK8IY0KVCDAlIaUUpRoFUsyaBZHQLmGA69CeEt1fZQoaAZoCWgPQwh9QKAzaZMWwJSGlFKUaBVLMmgWR0C5heFyFPBSdX2UKGgGaAloD0MIrvIEwk5RFcCUhpRSlGgVSzJoFkdAuYW/Nqxkd3V9lChoBmgJaA9DCNfCLLRzegzAlIaUUpRoFUsyaBZHQLmFnxZMcp91fZQoaAZoCWgPQwgkXp7OFcUZwJSGlFKUaBVLMmgWR0C5hn67/XGwdX2UKGgGaAloD0MIvmiPF9IBD8CUhpRSlGgVSzJoFkdAuYZchEBsAXV9lChoBmgJaA9DCM7eGW1VohDAlIaUUpRoFUsyaBZHQLmGOkNFz+51fZQoaAZoCWgPQwiEgHwJFYwgwJSGlFKUaBVLMmgWR0C5hho+r2g4dX2UKGgGaAloD0MIg4k/ijrLJcCUhpRSlGgVSzJoFkdAuYdKU1Q663V9lChoBmgJaA9DCBL5LqUuuQ3AlIaUUpRoFUsyaBZHQLmHKFTNt651fZQoaAZoCWgPQwiMvoI0Y3EMwJSGlFKUaBVLMmgWR0C5hwZkkKNRdX2UKGgGaAloD0MIBK+WOzOxIMCUhpRSlGgVSzJoFkdAuYbmjFhod3V9lChoBmgJaA9DCIsaTMPwCSDAlIaUUpRoFUsyaBZHQLmIEl/6O5t1fZQoaAZoCWgPQwgrptJPOEsSwJSGlFKUaBVLMmgWR0C5h/BlcyFgdX2UKGgGaAloD0MITtAmh0/KEcCUhpRSlGgVSzJoFkdAuYfOX1J173V9lChoBmgJaA9DCMTt0LAYDSPAlIaUUpRoFUsyaBZHQLmHro/zJ6p1fZQoaAZoCWgPQwjizRq8rxoQwJSGlFKUaBVLMmgWR0C5iNlQqI8AdX2UKGgGaAloD0MIhh+cTx1rEMCUhpRSlGgVSzJoFkdAuYi3gHeJpHV9lChoBmgJaA9DCNBGrptSjhjAlIaUUpRoFUsyaBZHQLmIlZh8Yyh1fZQoaAZoCWgPQwh1riglBGMgwJSGlFKUaBVLMmgWR0C5iHXKnvUjdX2UKGgGaAloD0MIyHxAoDM5EsCUhpRSlGgVSzJoFkdAuYmsudwvQHV9lChoBmgJaA9DCLIPsiyYKBLAlIaUUpRoFUsyaBZHQLmJivvjOs11fZQoaAZoCWgPQwjN5nEYzN8PwJSGlFKUaBVLMmgWR0C5iWkAT7EYdX2UKGgGaAloD0MIiSgmb4AJHcCUhpRSlGgVSzJoFkdAuYlJOvdM03V9lChoBmgJaA9DCPIJ2XkbuxPAlIaUUpRoFUsyaBZHQLmKhNVBD5V1fZQoaAZoCWgPQwhZ3lUPmGcWwJSGlFKUaBVLMmgWR0C5imMWoFV1dX2UKGgGaAloD0MIoiqm0k/4DcCUhpRSlGgVSzJoFkdAuYpBJe3QU3V9lChoBmgJaA9DCDWaXIyBlSLAlIaUUpRoFUsyaBZHQLmKIWtlqah1fZQoaAZoCWgPQwgsKAzKNEobwJSGlFKUaBVLMmgWR0C5i1j3dsSCdX2UKGgGaAloD0MIFwyuuaN/CcCUhpRSlGgVSzJoFkdAuYs3IikftHV9lChoBmgJaA9DCO5cGOlF7RHAlIaUUpRoFUsyaBZHQLmLFZeRgZ11fZQoaAZoCWgPQwi5wVCHFW4NwJSGlFKUaBVLMmgWR0C5ivXkPtladX2UKGgGaAloD0MI7u4Bui9XEsCUhpRSlGgVSzJoFkdAuYw2WqtHQXV9lChoBmgJaA9DCPomTYOiiRTAlIaUUpRoFUsyaBZHQLmMFHObAk91fZQoaAZoCWgPQwiKrgs/OE8lwJSGlFKUaBVLMmgWR0C5i/KtYB/7dX2UKGgGaAloD0MIyTmxh/ZxDcCUhpRSlGgVSzJoFkdAuYvS7tiQT3V9lChoBmgJaA9DCDpcqz3spRLAlIaUUpRoFUsyaBZHQLmM40JWvKV1fZQoaAZoCWgPQwjv4ZLjTskRwJSGlFKUaBVLMmgWR0C5jMD+ee4DdX2UKGgGaAloD0MILC6Oyk0UCMCUhpRSlGgVSzJoFkdAuYyewRoRI3V9lChoBmgJaA9DCNRhhVs+0h3AlIaUUpRoFUsyaBZHQLmMfrPMSsd1fZQoaAZoCWgPQwj6RQn6C30gwJSGlFKUaBVLMmgWR0C5jV91p0wKdX2UKGgGaAloD0MI1eqrqwLVDMCUhpRSlGgVSzJoFkdAuY09LEk0JnV9lChoBmgJaA9DCKvoD808OQbAlIaUUpRoFUsyaBZHQLmNGtjkMkR1fZQoaAZoCWgPQwi7nX3lQSoRwJSGlFKUaBVLMmgWR0C5jPrSRbKSdX2UKGgGaAloD0MIQMIwYMn1GcCUhpRSlGgVSzJoFkdAuY3e4TbnHXV9lChoBmgJaA9DCBMNUvAUIhrAlIaUUpRoFUsyaBZHQLmNvKB/Zuh1fZQoaAZoCWgPQwjmllZD4j4PwJSGlFKUaBVLMmgWR0C5jZpgssg/dX2UKGgGaAloD0MIoKhsWFM5CsCUhpRSlGgVSzJoFkdAuY16VUuL8HV9lChoBmgJaA9DCO8dNSbEbCXAlIaUUpRoFUsyaBZHQLmOWK/Efkp1fZQoaAZoCWgPQwiA12fO+tQFwJSGlFKUaBVLMmgWR0C5jjaUu+RHdX2UKGgGaAloD0MIC3pvDAEgEcCUhpRSlGgVSzJoFkdAuY4UUdq+J3V9lChoBmgJaA9DCEIj2Lj+DSDAlIaUUpRoFUsyaBZHQLmN9DVH4Gl1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 100000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVcwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaAtLA4WUjAFDlHSUUpSMBGhpZ2iUaBMolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgLSwOFlGgWdJRSlIwNYm91bmRlZF9iZWxvd5RoEyiWAwAAAAAAAAABAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBZ0lFKUjA1ib3VuZGVkX2Fib3ZllGgTKJYDAAAAAAAAAAEBAZRoIksDhZRoFnSUUpSMCl9ucF9yYW5kb22UTnViLg==", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "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 0x7f192c445a20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f192c43ebc0>"}, "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": 1686109309060145479, "learning_rate": 0.0001, "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": "[[ 0.3290378  -0.01346603  0.51693213]\n [ 0.3290378  -0.01346603  0.51693213]\n [ 0.3290378  -0.01346603  0.51693213]\n [ 0.3290378  -0.01346603  0.51693213]]", "desired_goal": "[[ 0.32118672  0.15064485  1.4704463 ]\n [-1.452497   -0.8582549   1.2842348 ]\n [ 0.16370349  1.7068591  -1.5523418 ]\n [-1.540527    0.72935754 -1.0273156 ]]", "observation": "[[ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]\n [ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]\n [ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]\n [ 0.3290378  -0.01346603  0.51693213 -0.00882417 -0.00228929  0.00818743]]"}, "_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": "[[-0.03811824 -0.12841372  0.26661316]\n [ 0.10937514 -0.08015183  0.01882749]\n [ 0.02355029 -0.01248805  0.1263911 ]\n [ 0.10665847 -0.09319272  0.13469197]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 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 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "False", "Numpy": "1.22.4", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -5.471117044053972, "std_reward": 0.8480662834687988, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-06T16:06:06.172482"}
+{"mean_reward": -0.9569692626129835, "std_reward": 0.12952724545196445, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-07T04:36:59.784481"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2065888223fb59a60be2b46cc2f78cfa944df3dbcb1d47cddd378ec129d42841
+oid sha256:a8268b555e2a4089f9256e6137f318bdd149edc24999f55d979cb2bfc90cf42a
 size 2387