Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -11.37 +/- 3.93
+      value: -0.75 +/- 0.31
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:71aee7d86a64ea9d539d797d0325fa8e09e066683c331cbf14a613d2c2ceda10
-size 108151
+oid sha256:e2e2832acd2faad9e3b60b7e0a72fff4909d74d3bb8c8135c0c4ec2b92083943
+size 109622

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 0x7efe5f6b6b80>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7fb344ed9e50>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7efe5f6ba0c0>"
+        "_abc_impl": "<_abc_data object at 0x7fb344ed3b70>"
     },
     "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": 1677768871285161250,
-    "learning_rate": 0.0007,
+    "start_time": 1677782022499747752,
+    "learning_rate": 0.0009,
     "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": "[[ 0.33061817 -0.00169847  0.5175132 ]\n [ 0.33061817 -0.00169847  0.5175132 ]\n [ 0.33061817 -0.00169847  0.5175132 ]\n [ 0.33061817 -0.00169847  0.5175132 ]]",
-        "desired_goal": "[[ 0.15797567  0.58657527  1.6246266 ]\n [-0.75125     1.1486844   0.5148736 ]\n [ 0.48854867  0.30212227  0.57982033]\n [-1.6893511  -1.1166296   1.6430757 ]]",
-        "observation": "[[ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]\n [ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]\n [ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]\n [ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[0.43636298 0.00863972 0.5400465 ]\n [0.43636298 0.00863972 0.5400465 ]\n [0.43636298 0.00863972 0.5400465 ]\n [0.43636298 0.00863972 0.5400465 ]]",
+        "desired_goal": "[[-0.14880489  0.55318564 -1.6443441 ]\n [-0.59145683 -1.3308283  -1.6283106 ]\n [ 1.0237713   1.3991371   1.624736  ]\n [-0.6956226   1.6533705  -0.5701466 ]]",
+        "observation": "[[0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]\n [0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]\n [0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]\n [0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]]"
     },
     "_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": "[[ 0.0038506  -0.09820127  0.12213448]\n [ 0.06473903  0.13285929  0.06240363]\n [-0.02937738 -0.08263664  0.25052732]\n [-0.12345978  0.14032957  0.27535456]]",
+        "desired_goal": "[[ 0.0185377  -0.00046267  0.13785695]\n [-0.13872017 -0.00891246  0.11607324]\n [ 0.02344366 -0.04401819  0.22371544]\n [ 0.13212773  0.08203067  0.19684553]]",
         "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,
-    "gamma": 0.99,
+    "_n_updates": 31250,
+    "n_steps": 8,
+    "gamma": 0.9,
     "gae_lambda": 1.0,
     "ent_coef": 0.0,
-    "vf_coef": 0.5,
-    "max_grad_norm": 0.5,
+    "vf_coef": 0.4,
+    "max_grad_norm": 0.2,
     "normalize_advantage": false
 }

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:efa9f1c50433826659240fa08da35127dedea2b28311805b2bacce53e82fab85
-size 44734
+oid sha256:96b98c483277cfb55cc04ef9abcb9f44ae31a5a2660c6ad7a477fa8f93316ff2
+size 45438

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d7fb7388388cd403dc90b628ae7582505394f31811d228fc1ca777b6b0f08c41
-size 46014
+oid sha256:7998ca1608a4cc51751f64527759152c7c7a153aa63ed9884b6f47e577c0aad8
+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 0x7efe5f6b6b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7efe5f6ba0c0>"}, "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:": "gAWVWAMAAAAAAACMD2d5bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwOZ3ltLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowGX3NoYXBllEsDhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZSMAUOUdJRSlIwEaGlnaJRoHiiWDAAAAAAAAAAAACBBAAAgQQAAIEGUaBZLA4WUaCF0lFKUjA1ib3VuZGVkX2JlbG93lGgeKJYDAAAAAAAAAAEBAZRoE4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZRoIXSUUpSMDWJvdW5kZWRfYWJvdmWUaB4olgMAAAAAAAAAAQEBlGgtSwOFlGghdJRSlIwKX25wX3JhbmRvbZROdWKMDGRlc2lyZWRfZ29hbJRoDSmBlH2UKGgQaBZoGUsDhZRoG2geKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZRoIXSUUpRoJGgeKJYMAAAAAAAAAAAAIEEAACBBAAAgQZRoFksDhZRoIXSUUpRoKWgeKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoM2geKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoOE51YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgWaBlLBoWUaBtoHiiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBZLBoWUaCF0lFKUaCRoHiiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBZLBoWUaCF0lFKUaCloHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDNoHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDhOdWJ1aBlOaBBOaDhOdWIu", "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": 1677768871285161250, "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": "[[ 0.33061817 -0.00169847  0.5175132 ]\n [ 0.33061817 -0.00169847  0.5175132 ]\n [ 0.33061817 -0.00169847  0.5175132 ]\n [ 0.33061817 -0.00169847  0.5175132 ]]", "desired_goal": "[[ 0.15797567  0.58657527  1.6246266 ]\n [-0.75125     1.1486844   0.5148736 ]\n [ 0.48854867  0.30212227  0.57982033]\n [-1.6893511  -1.1166296   1.6430757 ]]", "observation": "[[ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]\n [ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]\n [ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]\n [ 0.33061817 -0.00169847  0.5175132   0.02131903 -0.00153637  0.01736951]]"}, "_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": "[[ 0.0038506  -0.09820127  0.12213448]\n [ 0.06473903  0.13285929  0.06240363]\n [-0.02937738 -0.08263664  0.25052732]\n [-0.12345978  0.14032957  0.27535456]]", "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-5.15.0-60-generic-x86_64-with-glibc2.29 # 66~20.04.1-Ubuntu SMP Wed Jan 25 09:41:30 UTC 2023", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.20.0", "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 0x7fb344ed9e50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fb344ed3b70>"}, "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": 1677782022499747752, "learning_rate": 0.0009, "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": "[[0.43636298 0.00863972 0.5400465 ]\n [0.43636298 0.00863972 0.5400465 ]\n [0.43636298 0.00863972 0.5400465 ]\n [0.43636298 0.00863972 0.5400465 ]]", "desired_goal": "[[-0.14880489  0.55318564 -1.6443441 ]\n [-0.59145683 -1.3308283  -1.6283106 ]\n [ 1.0237713   1.3991371   1.624736  ]\n [-0.6956226   1.6533705  -0.5701466 ]]", "observation": "[[0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]\n [0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]\n [0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]\n [0.43636298 0.00863972 0.5400465  0.11439891 0.00065817 0.08020803]]"}, "_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": "[[ 0.0185377  -0.00046267  0.13785695]\n [-0.13872017 -0.00891246  0.11607324]\n [ 0.02344366 -0.04401819  0.22371544]\n [ 0.13212773  0.08203067  0.19684553]]", "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": 0.9, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.2, "normalize_advantage": false, "system_info": {"OS": "Linux-5.15.0-60-generic-x86_64-with-glibc2.29 # 66~20.04.1-Ubuntu SMP Wed Jan 25 09:41:30 UTC 2023", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu117", "GPU Enabled": "True", "Numpy": "1.20.0", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -11.365973581559956, "std_reward": 3.931651145740805, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-02T16:19:39.832379"}
+{"mean_reward": -0.7503685432486236, "std_reward": 0.3068699245811292, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-02T19:57:48.088371"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f9dbd676b4c457769c3a122556377240d4b595906f477ebaa13da49f49f70658
+oid sha256:b9bf8395ea19fd517c4633c6a3348e24c1ebb36868cdbf9e5715f4246bf1c704
 size 3218