Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -4.38 +/- 1.29
+      value: -0.66 +/- 0.21
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cb07fa183eab3aa7b7b81a58374f493fa0c13158d39841823bd14aba6c57a270
-size 108028
+oid sha256:3322e18499e4e7e15e31ee814a8df261250f7a973afa59135b449cb80c617949
+size 109501

a2c-PandaReachDense-v2/data

@@ -4,14 +4,16 @@
         ":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 0x7f2e7128f820>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7fcfa3bf8b80>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f2e7128ec00>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fcfa3bf9ac0>"
     },
     "verbose": 1,
     "policy_kwargs": {
         ":type:": "<class 'dict'>",
-        ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
+        ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
+        "log_std_init": -2,
+        "ortho_init": false,
         "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
         "optimizer_kwargs": {
             "alpha": 0.99,
@@ -46,19 +48,19 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1680201971250299735,
-    "learning_rate": 0.0007,
+    "start_time": 1680282458086409927,
+    "learning_rate": 0.00096,
     "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": "[[ 0.42889756 -0.06043423  0.31509554]\n [ 0.42889756 -0.06043423  0.31509554]\n [ 0.42889756 -0.06043423  0.31509554]\n [ 0.42889756 -0.06043423  0.31509554]]",
-        "desired_goal": "[[-1.2011048  -0.43764248 -0.88138664]\n [ 1.2676928   1.3567592  -0.7148049 ]\n [ 0.8714302  -1.0127459   0.23623775]\n [-1.3287811  -0.16301253 -1.6784117 ]]",
-        "observation": "[[ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]\n [ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]\n [ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]\n [ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[0.32232818 0.01129354 0.5564006 ]\n [0.32232818 0.01129354 0.5564006 ]\n [0.32232818 0.01129354 0.5564006 ]\n [0.32232818 0.01129354 0.5564006 ]]",
+        "desired_goal": "[[-0.9240797  -0.70447314  0.04596613]\n [ 0.9363505  -1.3622799  -1.0687758 ]\n [-0.32586157  1.6560825   0.18086194]\n [ 0.11705303 -1.2692024   1.441783  ]]",
+        "observation": "[[0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]\n [0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]\n [0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]\n [0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,29 +68,29 @@
     },
     "_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": "[[ 0.03355864  0.12091567  0.27472517]\n [ 0.10758366  0.0232089   0.16032615]\n [ 0.04164385  0.11734229  0.23751265]\n [ 0.05972347 -0.02929075  0.2036308 ]]",
+        "desired_goal": "[[-0.06135782  0.00773126  0.03225705]\n [-0.11843164  0.01567101  0.1969178 ]\n [ 0.09844923  0.13372304  0.02439113]\n [ 0.05442555  0.06172934  0.2538309 ]]",
         "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,
+    "use_sde": true,
     "sde_sample_freq": -1,
     "_current_progress_remaining": 0.0,
     "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": 50000,
-    "n_steps": 5,
+    "_n_updates": 31250,
+    "n_steps": 8,
     "gamma": 0.99,
-    "gae_lambda": 1.0,
+    "gae_lambda": 0.9,
     "ent_coef": 0.0,
-    "vf_coef": 0.5,
+    "vf_coef": 0.4,
     "max_grad_norm": 0.5,
     "normalize_advantage": false
 }

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e27702b4d8dc953deec1faaf377f8c1d69f05f9d1326c7c32b5823087fec4a88
-size 44734
+oid sha256:a31ad55aae9ad4ba1d56daba90ae77b8fa7e7aa9ec82969a11c8f33cbe166eae
+size 45438

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:922cbe256eef200c26154c7499fa96b878e6c0f91cad491b1aeed4408008a1dc
-size 46014
+oid sha256:ad7202918e3933fc73b934a6c75d399e882b994be75de8266ee4641ed78d5f3b
+size 46718

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 0x7f2e7128f820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f2e7128ec00>"}, "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": 1680201971250299735, "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": "[[ 0.42889756 -0.06043423  0.31509554]\n [ 0.42889756 -0.06043423  0.31509554]\n [ 0.42889756 -0.06043423  0.31509554]\n [ 0.42889756 -0.06043423  0.31509554]]", "desired_goal": "[[-1.2011048  -0.43764248 -0.88138664]\n [ 1.2676928   1.3567592  -0.7148049 ]\n [ 0.8714302  -1.0127459   0.23623775]\n [-1.3287811  -0.16301253 -1.6784117 ]]", "observation": "[[ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]\n [ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]\n [ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]\n [ 0.42889756 -0.06043423  0.31509554  0.02527141 -0.00762091  0.00212479]]"}, "_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": "[[ 0.03355864  0.12091567  0.27472517]\n [ 0.10758366  0.0232089   0.16032615]\n [ 0.04164385  0.11734229  0.23751265]\n [ 0.05972347 -0.02929075  0.2036308 ]]", "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////9LAHSUYkMImuyfpwETGcCUhpRSlIwBbJRLMowBdJRHQKj9cTRplBh1fZQoaAZoCWgPQwjOqWQAqDIcwJSGlFKUaBVLMmgWR0Co/RzBZZB+dX2UKGgGaAloD0MIkgThCiikFMCUhpRSlGgVSzJoFkdAqPzBSzgMt3V9lChoBmgJaA9DCJGBPLt8Ox3AlIaUUpRoFUsyaBZHQKj8XQ+EAYJ1fZQoaAZoCWgPQwg1RYDTuwgUwJSGlFKUaBVLMmgWR0Co/n4s/Y8MdX2UKGgGaAloD0MIc2n8witZFsCUhpRSlGgVSzJoFkdAqP4pnezlcXV9lChoBmgJaA9DCGPyBpj5vhTAlIaUUpRoFUsyaBZHQKj9zoWYWtV1fZQoaAZoCWgPQwgHB3sTQ/ITwJSGlFKUaBVLMmgWR0Co/Wn9ehPCdX2UKGgGaAloD0MIoQ+WsaG7AcCUhpRSlGgVSzJoFkdAqP+RgXuVo3V9lChoBmgJaA9DCMLAc+/h8g7AlIaUUpRoFUsyaBZHQKj/PLdN34d1fZQoaAZoCWgPQwgQJVryeNoSwJSGlFKUaBVLMmgWR0Co/uFEAo5QdX2UKGgGaAloD0MIaqLPRxkxHcCUhpRSlGgVSzJoFkdAqP58roW56XV9lChoBmgJaA9DCIHs9e6PhxrAlIaUUpRoFUsyaBZHQKkAm3OObRZ1fZQoaAZoCWgPQwikpl1MM70XwJSGlFKUaBVLMmgWR0CpAEap5u63dX2UKGgGaAloD0MI/KvHfavFHMCUhpRSlGgVSzJoFkdAqP/rcfvF33V9lChoBmgJaA9DCFD+7h01lhPAlIaUUpRoFUsyaBZHQKj/hsUIsy11fZQoaAZoCWgPQwgE4+DSMWcUwJSGlFKUaBVLMmgWR0CpAbMCDEm6dX2UKGgGaAloD0MIey5Tk+BNDMCUhpRSlGgVSzJoFkdAqQFe9zwMIHV9lChoBmgJaA9DCNhK6C6JYxLAlIaUUpRoFUsyaBZHQKkBA6NlyzZ1fZQoaAZoCWgPQwi1/pYA/GMTwJSGlFKUaBVLMmgWR0CpAJ72lEZ0dX2UKGgGaAloD0MIBRcrajAtFsCUhpRSlGgVSzJoFkdAqQLAxzq8lHV9lChoBmgJaA9DCM5uLZPh+AnAlIaUUpRoFUsyaBZHQKkCa/W1+iJ1fZQoaAZoCWgPQwiGIXL6ev4HwJSGlFKUaBVLMmgWR0CpAhDEWIoFdX2UKGgGaAloD0MIKgMHtHSFDsCUhpRSlGgVSzJoFkdAqQGsgMc6vXV9lChoBmgJaA9DCLaGUnsRDR3AlIaUUpRoFUsyaBZHQKkD1b+Lm6p1fZQoaAZoCWgPQwj7O9ujN5wXwJSGlFKUaBVLMmgWR0CpA4E4vN/wdX2UKGgGaAloD0MIISHKF7TAEMCUhpRSlGgVSzJoFkdAqQMl1loUSXV9lChoBmgJaA9DCOcb0T3rGhTAlIaUUpRoFUsyaBZHQKkCwYb83uN1fZQoaAZoCWgPQwiLwFjfwNQSwJSGlFKUaBVLMmgWR0CpBN/H5rP/dX2UKGgGaAloD0MIxXb3AN3nFMCUhpRSlGgVSzJoFkdAqQSLSThYNnV9lChoBmgJaA9DCNGvrZ/+cxPAlIaUUpRoFUsyaBZHQKkEL9srNGF1fZQoaAZoCWgPQwjzID1FDnESwJSGlFKUaBVLMmgWR0CpA8tkvsZ6dX2UKGgGaAloD0MIbR/ylqs/EsCUhpRSlGgVSzJoFkdAqQXtxXGOuXV9lChoBmgJaA9DCKlKW1zjgx/AlIaUUpRoFUsyaBZHQKkFmUsWfsh1fZQoaAZoCWgPQwgrbtxifh4VwJSGlFKUaBVLMmgWR0CpBT4K6WgOdX2UKGgGaAloD0MIiCtn74xWCsCUhpRSlGgVSzJoFkdAqQTZv99+gHV9lChoBmgJaA9DCBoziXrB5w3AlIaUUpRoFUsyaBZHQKkHP/1g6U91fZQoaAZoCWgPQwiFJ/T6kzgVwJSGlFKUaBVLMmgWR0CpBuuPV/c4dX2UKGgGaAloD0MI38SQnEz8DcCUhpRSlGgVSzJoFkdAqQaRLM9r43V9lChoBmgJaA9DCEIJM23/WhvAlIaUUpRoFUsyaBZHQKkGLLLZBcB1fZQoaAZoCWgPQwgPuRluwCcHwJSGlFKUaBVLMmgWR0CpCFikXUH6dX2UKGgGaAloD0MIqz3shQIGHMCUhpRSlGgVSzJoFkdAqQgEPMB6r3V9lChoBmgJaA9DCCfYf52b9hbAlIaUUpRoFUsyaBZHQKkHqRPoFFF1fZQoaAZoCWgPQwiWJM/1fbggwJSGlFKUaBVLMmgWR0CpB0TMA3kxdX2UKGgGaAloD0MI1Cr6QzN/EsCUhpRSlGgVSzJoFkdAqQlmfGuLaXV9lChoBmgJaA9DCMCV7NgI7CPAlIaUUpRoFUsyaBZHQKkJEeFL39J1fZQoaAZoCWgPQwjZCS/Bqe8OwJSGlFKUaBVLMmgWR0CpCLba7EpBdX2UKGgGaAloD0MI3H75ZMWQEMCUhpRSlGgVSzJoFkdAqQhSjSG8EnV9lChoBmgJaA9DCNf2dktyIAzAlIaUUpRoFUsyaBZHQKkKa/Vy3kR1fZQoaAZoCWgPQwi/uipQi8EQwJSGlFKUaBVLMmgWR0CpChcqOLiudX2UKGgGaAloD0MIwHXFjPAWFsCUhpRSlGgVSzJoFkdAqQm78m8dxXV9lChoBmgJaA9DCMzvNJnxNgzAlIaUUpRoFUsyaBZHQKkJV3wCr951fZQoaAZoCWgPQwhn7bYLzTUawJSGlFKUaBVLMmgWR0CpC490aIepdX2UKGgGaAloD0MIfR8OEqK8FsCUhpRSlGgVSzJoFkdAqQs7OHFglXV9lChoBmgJaA9DCBY0LbEyGhHAlIaUUpRoFUsyaBZHQKkK39Ujs2N1fZQoaAZoCWgPQwi0WIrkK9EXwJSGlFKUaBVLMmgWR0CpCnt4Z/CqdX2UKGgGaAloD0MI8zl3u16KG8CUhpRSlGgVSzJoFkdAqQy7MTviLnV9lChoBmgJaA9DCKMgeHx71xvAlIaUUpRoFUsyaBZHQKkMZqrzXjF1fZQoaAZoCWgPQwjSb18HzjkUwJSGlFKUaBVLMmgWR0CpDAs7MgU2dX2UKGgGaAloD0MImE9WDFeHBsCUhpRSlGgVSzJoFkdAqQum7J4jbHV9lChoBmgJaA9DCFnDRe7pqgrAlIaUUpRoFUsyaBZHQKkOGiY9gWt1fZQoaAZoCWgPQwhCQ/8EFysUwJSGlFKUaBVLMmgWR0CpDcZkK/mDdX2UKGgGaAloD0MIRUqzeRyGBsCUhpRSlGgVSzJoFkdAqQ1r/IbOvHV9lChoBmgJaA9DCJGcTNwqOBnAlIaUUpRoFUsyaBZHQKkNCCEHt4R1fZQoaAZoCWgPQwh7Szlf7K0YwJSGlFKUaBVLMmgWR0CpEBeIVM24dX2UKGgGaAloD0MIhe0nY3yoEMCUhpRSlGgVSzJoFkdAqQ/DLSuyNXV9lChoBmgJaA9DCEVHcvkPaRbAlIaUUpRoFUsyaBZHQKkPaF2V3Ux1fZQoaAZoCWgPQwis/Z3t0UsawJSGlFKUaBVLMmgWR0CpDwY51eSkdX2UKGgGaAloD0MITFRvDWzVAsCUhpRSlGgVSzJoFkdAqRICLjxTbXV9lChoBmgJaA9DCDkPJzCdlh3AlIaUUpRoFUsyaBZHQKkRrl4C6pZ1fZQoaAZoCWgPQwiqSfCGNBoWwJSGlFKUaBVLMmgWR0CpEVSvTw2EdX2UKGgGaAloD0MICCEgX0IBNcCUhpRSlGgVSzJoFkdAqRDxR8+ianV9lChoBmgJaA9DCKkyjLtBJBLAlIaUUpRoFUsyaBZHQKkUBDNQj2V1fZQoaAZoCWgPQwgEyqZc4f0OwJSGlFKUaBVLMmgWR0CpE7IFvAGjdX2UKGgGaAloD0MIisiwijeyEMCUhpRSlGgVSzJoFkdAqRNXbVSXMXV9lChoBmgJaA9DCGe0VUlk7xPAlIaUUpRoFUsyaBZHQKkS851/2Cd1fZQoaAZoCWgPQwil9iLajukTwJSGlFKUaBVLMmgWR0CpFeT72tdSdX2UKGgGaAloD0MIzczMzMw8F8CUhpRSlGgVSzJoFkdAqRWRaPjn3nV9lChoBmgJaA9DCH/ZPXlYuBXAlIaUUpRoFUsyaBZHQKkVNwhGH591fZQoaAZoCWgPQwjfMTz2s5gKwJSGlFKUaBVLMmgWR0CpFNRq46OpdX2UKGgGaAloD0MIuyU5YFdTEsCUhpRSlGgVSzJoFkdAqRe0DdP+GXV9lChoBmgJaA9DCOvkDMUdnxbAlIaUUpRoFUsyaBZHQKkXYL61stV1fZQoaAZoCWgPQwiJXkax3KIRwJSGlFKUaBVLMmgWR0CpFwaXBxgidX2UKGgGaAloD0MIVyO70jJSCMCUhpRSlGgVSzJoFkdAqRai22G7BnV9lChoBmgJaA9DCDdStkjaHRDAlIaUUpRoFUsyaBZHQKkY5rOZ9eB1fZQoaAZoCWgPQwjecvVjk1wLwJSGlFKUaBVLMmgWR0CpGJIaDPGAdX2UKGgGaAloD0MIZrtCHyzTE8CUhpRSlGgVSzJoFkdAqRg28dxQznV9lChoBmgJaA9DCHkDzHwH/wvAlIaUUpRoFUsyaBZHQKkX009hZyN1fZQoaAZoCWgPQwij6IGPwaoDwJSGlFKUaBVLMmgWR0CpGgIvi97GdX2UKGgGaAloD0MIJPJdSl0SA8CUhpRSlGgVSzJoFkdAqRmtn5BToHV9lChoBmgJaA9DCBptVRLZFx3AlIaUUpRoFUsyaBZHQKkZUnqFAVx1fZQoaAZoCWgPQwjfNH12wIUQwJSGlFKUaBVLMmgWR0CpGO3pGFzudX2UKGgGaAloD0MI0v4HWKuGE8CUhpRSlGgVSzJoFkdAqRsl9H+ZPXV9lChoBmgJaA9DCOBIoMGmDg3AlIaUUpRoFUsyaBZHQKka0SsbNr11fZQoaAZoCWgPQwiGyypsBpgIwJSGlFKUaBVLMmgWR0CpGnWuX/o8dX2UKGgGaAloD0MIuoPYmUInFsCUhpRSlGgVSzJoFkdAqRoRW1c+q3V9lChoBmgJaA9DCIczv5oDtBrAlIaUUpRoFUsyaBZHQKkcMPPLPld1fZQoaAZoCWgPQwid1m1Q++0ZwJSGlFKUaBVLMmgWR0CpG9xF7UobdX2UKGgGaAloD0MI91eP+1a7GMCUhpRSlGgVSzJoFkdAqRuA+4b0e3V9lChoBmgJaA9DCNFbPLznwAvAlIaUUpRoFUsyaBZHQKkbHFkxyn11ZS4="}, "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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "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 0x7fcfa3bf8b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fcfa3bf9ac0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "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": 1680282458086409927, "learning_rate": 0.00096, "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": "[[0.32232818 0.01129354 0.5564006 ]\n [0.32232818 0.01129354 0.5564006 ]\n [0.32232818 0.01129354 0.5564006 ]\n [0.32232818 0.01129354 0.5564006 ]]", "desired_goal": "[[-0.9240797  -0.70447314  0.04596613]\n [ 0.9363505  -1.3622799  -1.0687758 ]\n [-0.32586157  1.6560825   0.18086194]\n [ 0.11705303 -1.2692024   1.441783  ]]", "observation": "[[0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]\n [0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]\n [0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]\n [0.32232818 0.01129354 0.5564006  0.06592379 0.00233839 0.06395213]]"}, "_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": "[[-0.06135782  0.00773126  0.03225705]\n [-0.11843164  0.01567101  0.1969178 ]\n [ 0.09844923  0.13372304  0.02439113]\n [ 0.05442555  0.06172934  0.2538309 ]]", "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": true, "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": 31250, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "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": -4.383266517333686, "std_reward": 1.2922084421337725, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-30T19:39:48.114175"}
+{"mean_reward": -0.6649203093023971, "std_reward": 0.20849835809577832, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-31T17:58:31.123880"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:eb49d0db56d7daf49fe45b1c9e1101274ffdaa51e77cf36d1b718ba21ac1edd2
+oid sha256:30d4fa0e7e86e7058a738229964ca82946e07dcf8fee31f8dae3238c833f243b
 size 3056