Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -6.07 +/- 1.92
+      value: -3.36 +/- 1.05
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ccbbaedeaa5218c936ea22feb916b2c9387f43eec876c529db8775039d6cc059
+oid sha256:7b8e97248d656eea018e3b1ff6cd9082229d868c388669ff65670a4740bd8564
 size 108011

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 0x7f2dc43898b0>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7fd0a1b765e0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f2dc4382bd0>"
+        "_abc_impl": "<_abc_data object at 0x7fd0a1b6fa80>"
     },
     "verbose": 1,
     "policy_kwargs": {
@@ -41,12 +41,12 @@
         "_np_random": null
     },
     "n_envs": 4,
-    "num_timesteps": 1300000,
-    "_total_timesteps": 1300000,
+    "num_timesteps": 1000000,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1676389443664413409,
+    "start_time": 1676471116096030410,
     "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": "[[0.49582466 0.05769715 0.57151014]\n [0.49582466 0.05769715 0.57151014]\n [0.49582466 0.05769715 0.57151014]\n [0.49582466 0.05769715 0.57151014]]",
-        "desired_goal": "[[-0.7169732  -0.73946345 -0.1091762 ]\n [-1.1682241  -0.32105455 -1.2505313 ]\n [-0.18147948  0.186535   -0.84433824]\n [ 1.0783268  -0.19251603 -1.5366349 ]]",
-        "observation": "[[ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]\n [ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]\n [ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]\n [ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[0.42167184 0.01339583 0.5867217 ]\n [0.42167184 0.01339583 0.5867217 ]\n [0.42167184 0.01339583 0.5867217 ]\n [0.42167184 0.01339583 0.5867217 ]]",
+        "desired_goal": "[[ 1.7395017   1.3085183   0.01802156]\n [ 1.2437001  -0.43567458  0.56453305]\n [ 0.4517564   1.4814771  -1.7249931 ]\n [ 0.4856105   0.4135412  -0.13063294]]",
+        "observation": "[[ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]\n [ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]\n [ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]\n [ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]]"
     },
     "_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": "[[ 0.01743734 -0.00428374  0.24177305]\n [ 0.07955647  0.00791843  0.04040086]\n [ 0.13802604 -0.03347956  0.01312697]\n [-0.01707985 -0.02874549  0.28988266]]",
+        "desired_goal": "[[ 0.05621714  0.01094001  0.21260676]\n [-0.10364146 -0.06384447  0.29596746]\n [-0.04887074 -0.12934737  0.2925941 ]\n [ 0.12593985 -0.05719031  0.11832669]]",
         "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:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 65000,
+    "_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 sha256:3e905f9b191d6c67adec312b2f6d39f527e4bba0e5d4f8749db2fde20a58965e
+oid sha256:66fdb86c93b0a6a41c4e183653ea7f707b634a1786f2afbfbf4ae620cdd7899a
 size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:faa1088fbb97f089888dc3fea6665008018c57dc9fcb9fc703bcd0eda209927a
+oid sha256:be129a6a613f68e193b3927362cac1021431055f57864d97ff3fd1bc74a1e735
 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 0x7f2dc43898b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2dc4382bd0>"}, "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": 1300000, "_total_timesteps": 1300000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676389443664413409, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAu9z9PthTbD19ThI/u9z9PthTbD19ThI/u9z9PthTbD19ThI/u9z9PthTbD19ThI/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAjos3v3pNPb/Gl9+9XoiVv0NhpL5pEaC/wtU5vggDPz6NJli/nQaKP+wiRb50sMS/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAAC73P0+2FNsPX1OEj8+PqE6nPLDO0av0Lu73P0+2FNsPX1OEj8+PqE6nPLDO0av0Lu73P0+2FNsPX1OEj8+PqE6nPLDO0av0Lu73P0+2FNsPX1OEj8+PqE6nPLDO0av0LuUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.49582466 0.05769715 0.57151014]\n [0.49582466 0.05769715 0.57151014]\n [0.49582466 0.05769715 0.57151014]\n [0.49582466 0.05769715 0.57151014]]", "desired_goal": "[[-0.7169732  -0.73946345 -0.1091762 ]\n [-1.1682241  -0.32105455 -1.2505313 ]\n [-0.18147948  0.186535   -0.84433824]\n [ 1.0783268  -0.19251603 -1.5366349 ]]", "observation": "[[ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]\n [ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]\n [ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]\n [ 0.49582466  0.05769715  0.57151014  0.00123019  0.00597985 -0.00636855]]"}, "_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": "[[ 0.01743734 -0.00428374  0.24177305]\n [ 0.07955647  0.00791843  0.04040086]\n [ 0.13802604 -0.03347956  0.01312697]\n [-0.01707985 -0.02874549  0.28988266]]", "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": 65000, "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": "1.21.6", "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 0x7fd0a1b765e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fd0a1b6fa80>"}, "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:": "gAWVbQEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaApLA4WUjAFDlHSUUpSMBGhpZ2iUaBIolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgKSwOFlGgVdJRSlIwNYm91bmRlZF9iZWxvd5RoEiiWAwAAAAAAAAABAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYDAAAAAAAAAAEBAZRoIUsDhZRoFXSUUpSMCl9ucF9yYW5kb22UTnViLg==", "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": 1676471116096030410, "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": "[[0.42167184 0.01339583 0.5867217 ]\n [0.42167184 0.01339583 0.5867217 ]\n [0.42167184 0.01339583 0.5867217 ]\n [0.42167184 0.01339583 0.5867217 ]]", "desired_goal": "[[ 1.7395017   1.3085183   0.01802156]\n [ 1.2437001  -0.43567458  0.56453305]\n [ 0.4517564   1.4814771  -1.7249931 ]\n [ 0.4856105   0.4135412  -0.13063294]]", "observation": "[[ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]\n [ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]\n [ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]\n [ 0.42167184  0.01339583  0.5867217   0.01028911 -0.0025072   0.00467074]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA8kNmPbU9MzyWtVk++UHUveTAgr0MiZc+ryxIvaNzBL7lzpU+YPYAPmJAar1DVfI9lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[ 0.05621714  0.01094001  0.21260676]\n [-0.10364146 -0.06384447  0.29596746]\n [-0.04887074 -0.12934737  0.2925941 ]\n [ 0.12593985 -0.05719031  0.11832669]]", "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": "1.21.6", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -6.073329044505954, "std_reward": 1.9192037935923096, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-14T16:43:47.709204"}
+{"mean_reward": -3.3553688935935497, "std_reward": 1.0507451667687073, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-15T15:18:56.009366"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:814c1d4bef695e308450f275f904c33853e6a250c98af8b76e4c1f2b049f4804
+oid sha256:6ddbdd5cee55148bf81159e1cd7e99472c80891b481cdc3cd10884a3b2a7d50c
 size 3056