Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -1.94 +/- 0.50
+      value: -2.70 +/- 0.83
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0841b38c42af96b986eda7331e4b3b72d013d90af90b735dd55609e83bb0d191
-size 108110
+oid sha256:e9b54a527fd20db8867d99bde637f12fc378e79cb7c5ab7cafab19241b7905c7
+size 108016

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 0x7fab0c9635e0>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7f78c336b0d0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fab0c964400>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f78c3366d40>"
     },
     "verbose": 1,
     "policy_kwargs": {
@@ -41,12 +41,12 @@
         "_np_random": null
     },
     "n_envs": 4,
-    "num_timesteps": 800000,
-    "_total_timesteps": 800000,
+    "num_timesteps": 1000000,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1678395650820940961,
+    "start_time": 1678469266644176954,
     "learning_rate": 0.0007,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -55,10 +55,10 @@
     },
     "_last_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA8mW5PiFf97s2vAw/8mW5PiFf97s2vAw/8mW5PiFf97s2vAw/8mW5PiFf97s2vAw/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAnd2kv6verb9lSUe+bnn2vv45+j5zkZW9OzmCv0cqub8ByZY+DLG/vsUo0T9328Y/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADyZbk+IV/3uza8DD+8yTE8JQU8N+zvlDzyZbk+IV/3uza8DD+8yTE8JQU8N+zvlDzyZbk+IV/3uza8DD+8yTE8JQU8N+zvlDzyZbk+IV/3uza8DD+8yTE8JQU8N+zvlDyUaA5LBEsGhpRoEnSUUpR1Lg==",
-        "achieved_goal": "[[ 0.3621059  -0.00754918  0.5497469 ]\n [ 0.3621059  -0.00754918  0.5497469 ]\n [ 0.3621059  -0.00754918  0.5497469 ]\n [ 0.3621059  -0.00754918  0.5497469 ]]",
-        "desired_goal": "[[-1.2880131  -1.3583578  -0.19461592]\n [-0.48139518  0.4887237  -0.07303133]\n [-1.0173715  -1.4466027   0.2945023 ]\n [-0.37439764  1.6340567   1.5535725 ]]",
-        "observation": "[[ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-02]\n [ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-02]\n [ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-02]\n [ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-02]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[0.41774756 0.02140889 0.590173  ]\n [0.41774756 0.02140889 0.590173  ]\n [0.41774756 0.02140889 0.590173  ]\n [0.41774756 0.02140889 0.590173  ]]",
+        "desired_goal": "[[ 0.2726431   0.47187504 -1.1744308 ]\n [-1.1072891   1.7052453  -1.4475847 ]\n [ 0.658669    1.2890773   0.24379833]\n [-0.86069703  0.1463528  -0.832602  ]]",
+        "observation": "[[ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]\n [ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]\n [ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]\n [ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]]"
     },
     "_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": "[[-0.02257457 -0.13069333  0.20698647]\n [-0.05733326 -0.09490276  0.07546801]\n [-0.14626463  0.00396301  0.17861849]\n [-0.08453283 -0.02056787  0.17960392]]",
+        "desired_goal": "[[ 0.02174883  0.09804311  0.08336237]\n [ 0.14234035  0.03735153  0.27092308]\n [-0.06204448 -0.0481787   0.18040183]\n [ 0.06452412  0.09767589  0.18839759]]",
         "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": 40000,
+    "_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 sha256:4a66a729b84a916a1addf496285e47da4ae855fda6fa75232324b9db91d02e24
+oid sha256:13d8686d58f72bc640a9d92277c83e584d82ba445c3dccf65c5845a2f0ec3256
 size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0d948b0017a1cb93d36a461bd80c825d95f3a8355a43a230d0cad7c9cda3e730
+oid sha256:630fdc6b89bbc94ae0fa374c8c1e37f79c78ccb2dedfb8d82c1fc361c1d5dcc3
 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 0x7fab0c9635e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fab0c964400>"}, "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": 800000, "_total_timesteps": 800000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678395650820940961, "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": "[[ 0.3621059  -0.00754918  0.5497469 ]\n [ 0.3621059  -0.00754918  0.5497469 ]\n [ 0.3621059  -0.00754918  0.5497469 ]\n [ 0.3621059  -0.00754918  0.5497469 ]]", "desired_goal": "[[-1.2880131  -1.3583578  -0.19461592]\n [-0.48139518  0.4887237  -0.07303133]\n [-1.0173715  -1.4466027   0.2945023 ]\n [-0.37439764  1.6340567   1.5535725 ]]", "observation": "[[ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-02]\n [ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-02]\n [ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-02]\n [ 3.6210591e-01 -7.5491820e-03  5.4974687e-01  1.0851320e-02\n   1.1206871e-05  1.8180810e-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": "[[-0.02257457 -0.13069333  0.20698647]\n [-0.05733326 -0.09490276  0.07546801]\n [-0.14626463  0.00396301  0.17861849]\n [-0.08453283 -0.02056787  0.17960392]]", "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": 40000, "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 0x7f78c336b0d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f78c3366d40>"}, "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": 1678469266644176954, "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": "[[0.41774756 0.02140889 0.590173  ]\n [0.41774756 0.02140889 0.590173  ]\n [0.41774756 0.02140889 0.590173  ]\n [0.41774756 0.02140889 0.590173  ]]", "desired_goal": "[[ 0.2726431   0.47187504 -1.1744308 ]\n [-1.1072891   1.7052453  -1.4475847 ]\n [ 0.658669    1.2890773   0.24379833]\n [-0.86069703  0.1463528  -0.832602  ]]", "observation": "[[ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]\n [ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]\n [ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]\n [ 0.41774756  0.02140889  0.590173   -0.00333584  0.00077959 -0.00590458]]"}, "_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": "[[ 0.02174883  0.09804311  0.08336237]\n [ 0.14234035  0.03735153  0.27092308]\n [-0.06204448 -0.0481787   0.18040183]\n [ 0.06452412  0.09767589  0.18839759]]", "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-glibc2.31 # 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": -1.94126617629081, "std_reward": 0.4956061308166094, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-09T21:51:12.078741"}
+{"mean_reward": -2.697501630242914, "std_reward": 0.832400901376507, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-10T18:45:19.396007"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b4afccf9770ec7c688c475f03923b5aad797c68a403156ec026fa15ab5a617ad
+oid sha256:5ad5ff606e65d3e694134be20cda028062de044395a785ee61448481ed450b3c
 size 3056