Initial commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- PandaReachDense-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaReachDense-v2
+      type: PandaReachDense-v2
+    metrics:
+    - type: mean_reward
+      value: -4.10 +/- 0.54
+      name: mean_reward
+      verified: false
+---
+
+# **A2C** Agent playing **PandaReachDense-v2**
+This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

a2c-PandaReachDense-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5b4bf89d30297ce625322bd74ceba599bd4f1a8cc06fea632b203ce22f1bc44f
+size 108058

a2c-PandaReachDense-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.8.0

a2c-PandaReachDense-v2/data

@@ -0,0 +1,95 @@
+{
+    "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 0x7fe4b55674c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fe4b5569280>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        ":type:": "<class 'dict'>",
+        ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
+        "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
+        "optimizer_kwargs": {
+            "alpha": 0.99,
+            "eps": 1e-05,
+            "weight_decay": 0
+        }
+    },
+    "num_timesteps": 1000000,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1681043395020777450,
+    "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": "[[ 0.40375915 -0.0642674   0.447203  ]\n [ 0.40375915 -0.0642674   0.447203  ]\n [ 0.40375915 -0.0642674   0.447203  ]\n [ 0.40375915 -0.0642674   0.447203  ]]",
+        "desired_goal": "[[ 0.2731702  -1.5482376  -1.4569656 ]\n [ 0.07026877  0.5987847   1.0148445 ]\n [ 1.1711339  -0.3662578  -0.5449122 ]\n [ 0.03210905 -0.8813091   0.69893503]]",
+        "observation": "[[ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]\n [ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]\n [ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]\n [ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]]"
+    },
+    "_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": "[[ 0.09563047 -0.09838179  0.048867  ]\n [-0.0629881   0.07836143  0.01119199]\n [ 0.14542373 -0.06741445  0.1578561 ]\n [-0.04971609 -0.10099331  0.08988288]]",
+        "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"
+    },
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": 0.0,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 50000,
+    "n_steps": 5,
+    "gamma": 0.99,
+    "gae_lambda": 1.0,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "normalize_advantage": false,
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.dict.Dict'>",
+        ":serialized:": "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",
+        "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])",
+        "_shape": null,
+        "dtype": null,
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            3
+        ],
+        "low": "[-1. -1. -1.]",
+        "high": "[1. 1. 1.]",
+        "bounded_below": "[ True  True  True]",
+        "bounded_above": "[ True  True  True]",
+        "_np_random": null
+    },
+    "n_envs": 4
+}

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:905516686a8ac718900ecce31813fea4e604c4fde198091ab14f8abfc64133dc
+size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c3ed725bc6fb56afefa8b9c562a7288fafd26d75cefcc36aea5e38cf0748e8aa
+size 46014

a2c-PandaReachDense-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

a2c-PandaReachDense-v2/system_info.txt

@@ -0,0 +1,7 @@
+- 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: 1.8.0
+- PyTorch: 2.0.0+cu118
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Gym: 0.21.0

config.json

@@ -0,0 +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 0x7fe4b55674c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fe4b5569280>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681043395020777450, "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": "[[ 0.40375915 -0.0642674   0.447203  ]\n [ 0.40375915 -0.0642674   0.447203  ]\n [ 0.40375915 -0.0642674   0.447203  ]\n [ 0.40375915 -0.0642674   0.447203  ]]", "desired_goal": "[[ 0.2731702  -1.5482376  -1.4569656 ]\n [ 0.07026877  0.5987847   1.0148445 ]\n [ 1.1711339  -0.3662578  -0.5449122 ]\n [ 0.03210905 -0.8813091   0.69893503]]", "observation": "[[ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]\n [ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]\n [ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]\n [ 0.40375915 -0.0642674   0.447203   -0.00474274 -0.00486889  0.00847661]]"}, "_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////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA6NnDPWV8yb3EKEg96P+AvfV7oD2bXjc89ekUPpYQir0IpSE+GqNLvZTVzr2EFLg9lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[ 0.09563047 -0.09838179  0.048867  ]\n [-0.0629881   0.07836143  0.01119199]\n [ 0.14542373 -0.06741445  0.1578561 ]\n [-0.04971609 -0.10099331  0.08988288]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIO4pz1NHxDsCUhpRSlIwBbJRLMowBdJRHQKaWbGNJe3R1fZQoaAZoCWgPQwhyjGSPUBMFwJSGlFKUaBVLMmgWR0CmljMFlkH2dX2UKGgGaAloD0MIQ8h5/x8nBsCUhpRSlGgVSzJoFkdAppX4LgGbC3V9lChoBmgJaA9DCAYTfxR19hXAlIaUUpRoFUsyaBZHQKaVtmGM4tJ1fZQoaAZoCWgPQwgAPKJCdRMHwJSGlFKUaBVLMmgWR0CmmBKagElmdX2UKGgGaAloD0MIdqp8z0jEDcCUhpRSlGgVSzJoFkdAppfYcghbGHV9lChoBmgJaA9DCAwCK4cW2Q3AlIaUUpRoFUsyaBZHQKaXngDzRQd1fZQoaAZoCWgPQwhR9pZyvsgTwJSGlFKUaBVLMmgWR0Cml1yLAHmjdX2UKGgGaAloD0MIYvTcQldiBsCUhpRSlGgVSzJoFkdAppmScI7eVXV9lChoBmgJaA9DCH0Facai2RHAlIaUUpRoFUsyaBZHQKaZWGL1mJ51fZQoaAZoCWgPQwj76qpALcYOwJSGlFKUaBVLMmgWR0CmmR2ys0YTdX2UKGgGaAloD0MIxy5RvTUQD8CUhpRSlGgVSzJoFkdAppjcGiYb83V9lChoBmgJaA9DCPw07s1v2A3AlIaUUpRoFUsyaBZHQKabBdkauOl1fZQoaAZoCWgPQwgLXvQVpEkUwJSGlFKUaBVLMmgWR0CmmsucMEzPdX2UKGgGaAloD0MIKH/3jhrzD8CUhpRSlGgVSzJoFkdAppqQ20iQk3V9lChoBmgJaA9DCBhftMcLiQfAlIaUUpRoFUsyaBZHQKaaT1qWTot1fZQoaAZoCWgPQwj/WIgOgSMEwJSGlFKUaBVLMmgWR0CmnFgkcCHRdX2UKGgGaAloD0MIDr3Fw3uOCsCUhpRSlGgVSzJoFkdAppwdbiZOSHV9lChoBmgJaA9DCNB+pIgMSwjAlIaUUpRoFUsyaBZHQKab4i+L3sZ1fZQoaAZoCWgPQwgjTbwDPCkRwJSGlFKUaBVLMmgWR0Cmm6AFPi1idX2UKGgGaAloD0MIt/C8VGzsCcCUhpRSlGgVSzJoFkdApp07vAoG6nV9lChoBmgJaA9DCGowDcNH5A/AlIaUUpRoFUsyaBZHQKadAO4G2Th1fZQoaAZoCWgPQwjPhZFe1M4HwJSGlFKUaBVLMmgWR0CmnMWSlnAZdX2UKGgGaAloD0MIrMq+K4KPGcCUhpRSlGgVSzJoFkdAppyDWoWHlHV9lChoBmgJaA9DCFN5O8JpsRDAlIaUUpRoFUsyaBZHQKaeSeNkvsZ1fZQoaAZoCWgPQwj7kSIyrMIJwJSGlFKUaBVLMmgWR0Cmng8hs67vdX2UKGgGaAloD0MIk1SmmIMg+L+UhpRSlGgVSzJoFkdApp3U4ecQRXV9lChoBmgJaA9DCK1RD9HozgjAlIaUUpRoFUsyaBZHQKadksV+I/J1fZQoaAZoCWgPQwic+dUcIJgMwJSGlFKUaBVLMmgWR0Cmn0SXdCVsdX2UKGgGaAloD0MIeQYN/RPcDsCUhpRSlGgVSzJoFkdApp8KRnvlVHV9lChoBmgJaA9DCPbSFAFOTw/AlIaUUpRoFUsyaBZHQKaezx6v7nB1fZQoaAZoCWgPQwjeH+9VK9MDwJSGlFKUaBVLMmgWR0Cmno1ObiIddX2UKGgGaAloD0MISIrIsIoXD8CUhpRSlGgVSzJoFkdApqAz+NtIkXV9lChoBmgJaA9DCHe9NEWA0wjAlIaUUpRoFUsyaBZHQKaf+UQCjlB1fZQoaAZoCWgPQwi3f2WlSWkOwJSGlFKUaBVLMmgWR0Cmn74LCvX9dX2UKGgGaAloD0MIwJSBA1o6A8CUhpRSlGgVSzJoFkdApp977Gecx3V9lChoBmgJaA9DCFPovMYuoRHAlIaUUpRoFUsyaBZHQKahI5YHPeJ1fZQoaAZoCWgPQwgK8rOR68YNwJSGlFKUaBVLMmgWR0CmoOmNR3vAdX2UKGgGaAloD0MIEALyJVRQDcCUhpRSlGgVSzJoFkdApqCuSfUWmHV9lChoBmgJaA9DCFpj0Amh4xPAlIaUUpRoFUsyaBZHQKagbBfrrxB1fZQoaAZoCWgPQwh+HM2Rlf8KwJSGlFKUaBVLMmgWR0CmogHmzSkTdX2UKGgGaAloD0MI48PsZdvpCMCUhpRSlGgVSzJoFkdApqHHJJXhfnV9lChoBmgJaA9DCAXbiCe7eQ3AlIaUUpRoFUsyaBZHQKahi8Tzund1fZQoaAZoCWgPQwindRvUfisGwJSGlFKUaBVLMmgWR0CmoUmHHmzTdX2UKGgGaAloD0MIT8sPXOXpBMCUhpRSlGgVSzJoFkdApqLfj2i+L3V9lChoBmgJaA9DCKc8uhEWFQvAlIaUUpRoFUsyaBZHQKaipN4Z/Ct1fZQoaAZoCWgPQwiLql/pfNgIwJSGlFKUaBVLMmgWR0CmommJN0vHdX2UKGgGaAloD0MII4YdxqS/A8CUhpRSlGgVSzJoFkdApqInQdCE6HV9lChoBmgJaA9DCMHHYMWp9gTAlIaUUpRoFUsyaBZHQKajvOXVsk91fZQoaAZoCWgPQwgIkncOZQgLwJSGlFKUaBVLMmgWR0Cmo4JBgNPQdX2UKGgGaAloD0MIahK8IY3qEMCUhpRSlGgVSzJoFkdApqNG9QGfPHV9lChoBmgJaA9DCN+l1CXjuBDAlIaUUpRoFUsyaBZHQKajBN21Ul11fZQoaAZoCWgPQwi7Qh8sY4MLwJSGlFKUaBVLMmgWR0CmpKCT+vQodX2UKGgGaAloD0MIUI9tGXCWEMCUhpRSlGgVSzJoFkdApqRl4eLeh3V9lChoBmgJaA9DCJ0ui4nNhwbAlIaUUpRoFUsyaBZHQKakKpSaVlh1fZQoaAZoCWgPQwgpeAq5Uu8MwJSGlFKUaBVLMmgWR0Cmo+hwdbPhdX2UKGgGaAloD0MIqFFIMqt3C8CUhpRSlGgVSzJoFkdApqWCVB2OhnV9lChoBmgJaA9DCD7o2az6XA7AlIaUUpRoFUsyaBZHQKalR7Gecx11fZQoaAZoCWgPQwiKOQg6WhUGwJSGlFKUaBVLMmgWR0CmpQy+QEIPdX2UKGgGaAloD0MIkUYFTrZhDcCUhpRSlGgVSzJoFkdApqTKpo9LYnV9lChoBmgJaA9DCBwHXi13ZgnAlIaUUpRoFUsyaBZHQKamc4wRGtp1fZQoaAZoCWgPQwgxW7Iqwg0LwJSGlFKUaBVLMmgWR0CmpjkyckMTdX2UKGgGaAloD0MIPnWsUnq2EMCUhpRSlGgVSzJoFkdApqX+AVfu1HV9lChoBmgJaA9DCNS6DWq/FQrAlIaUUpRoFUsyaBZHQKalu/etSyd1fZQoaAZoCWgPQwjkTX6LTvYPwJSGlFKUaBVLMmgWR0Cmp3zfaYeDdX2UKGgGaAloD0MIN23GaYjKB8CUhpRSlGgVSzJoFkdApqdCFsYVI3V9lChoBmgJaA9DCEJ6ihwifhLAlIaUUpRoFUsyaBZHQKanBsYVIqd1fZQoaAZoCWgPQwiXkXpP5bQBwJSGlFKUaBVLMmgWR0CmpsUfHPu5dX2UKGgGaAloD0MIa+9TVWjwGcCUhpRSlGgVSzJoFkdApqhi9K28ZnV9lChoBmgJaA9DCCuhuyTOig7AlIaUUpRoFUsyaBZHQKaoKCxu89R1fZQoaAZoCWgPQwiXGwx1WOEMwJSGlFKUaBVLMmgWR0Cmp+zbnHNpdX2UKGgGaAloD0MIx5xn7Es2EcCUhpRSlGgVSzJoFkdApqeq5Gz8g3V9lChoBmgJaA9DCMHIy5pYwAnAlIaUUpRoFUsyaBZHQKapS79Q40d1fZQoaAZoCWgPQwjLZ3ke3E0QwJSGlFKUaBVLMmgWR0CmqRD4pMHsdX2UKGgGaAloD0MIFoVdFD2QEcCUhpRSlGgVSzJoFkdApqjVwBHTZ3V9lChoBmgJaA9DCCnqzD0kXAvAlIaUUpRoFUsyaBZHQKaok4J/oaF1fZQoaAZoCWgPQwhyNh0B3HwQwJSGlFKUaBVLMmgWR0CmqjICdSVGdX2UKGgGaAloD0MIF/IIbqRcEMCUhpRSlGgVSzJoFkdApqn3Y8Md93V9lChoBmgJaA9DCEHYKVYNIg3AlIaUUpRoFUsyaBZHQKapvC0F8oh1fZQoaAZoCWgPQwgqi8Iuig4SwJSGlFKUaBVLMmgWR0CmqXoMrmQsdX2UKGgGaAloD0MIOIQqNXtwEMCUhpRSlGgVSzJoFkdApqslYW+GoXV9lChoBmgJaA9DCBpPBHEeDgvAlIaUUpRoFUsyaBZHQKaq6rtE5Qx1fZQoaAZoCWgPQwiuRnalZYQFwJSGlFKUaBVLMmgWR0CmqrAp8WsSdX2UKGgGaAloD0MIVKwahLktEcCUhpRSlGgVSzJoFkdApqpuEkB0ZHV9lChoBmgJaA9DCLA73XnieRLAlIaUUpRoFUsyaBZHQKasFrrPdEd1fZQoaAZoCWgPQwhodXKG4u4HwJSGlFKUaBVLMmgWR0Cmq9w3HaN/dX2UKGgGaAloD0MIprT+lgCcDsCUhpRSlGgVSzJoFkdApquhlFtsN3V9lChoBmgJaA9DCBy0Vx8PXQbAlIaUUpRoFUsyaBZHQKarYBd2Pkt1fZQoaAZoCWgPQwgzGY7nM+ASwJSGlFKUaBVLMmgWR0CmrPlNDc/MdX2UKGgGaAloD0MIFJSilXsBE8CUhpRSlGgVSzJoFkdApqy+l0o0AXV9lChoBmgJaA9DCAQDCB9KVAjAlIaUUpRoFUsyaBZHQKasg0LMLWt1fZQoaAZoCWgPQwi1xTU+k+0QwJSGlFKUaBVLMmgWR0CmrEEfs/pudX2UKGgGaAloD0MIFoielEmdEMCUhpRSlGgVSzJoFkdApq3ebsniN3V9lChoBmgJaA9DCMJR8uocMxDAlIaUUpRoFUsyaBZHQKato8J2MbZ1fZQoaAZoCWgPQwikwW1t4RkQwJSGlFKUaBVLMmgWR0CmrWh4D9wWdX2UKGgGaAloD0MI4xdeSfI8DsCUhpRSlGgVSzJoFkdApq0mc6Nly3V9lChoBmgJaA9DCNjTDn9N9hPAlIaUUpRoFUsyaBZHQKauxWQOnVJ1fZQoaAZoCWgPQwinJVZGIx8RwJSGlFKUaBVLMmgWR0Cmroq02LpBdX2UKGgGaAloD0MI2EgShCsQEcCUhpRSlGgVSzJoFkdApq5PZRKpUHV9lChoBmgJaA9DCNbjvtU6EQrAlIaUUpRoFUsyaBZHQKauDT4tYjl1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 50000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

results.json

@@ -0,0 +1 @@
+{"mean_reward": -4.095953224226832, "std_reward": 0.5447004883369145, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-09T13:19:27.470548"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d5018f38457da61223f91dfecd786f5f4308d38bc8723feb4e1a6dc539f3ca4
+size 2381