Initial commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- PandaPickAndPlace-v3
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaPickAndPlace-v3
+      type: PandaPickAndPlace-v3
+    metrics:
+    - type: mean_reward
+      value: -50.00 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+
+# **A2C** Agent playing **PandaPickAndPlace-v3**
+This is a trained model of a **A2C** agent playing **PandaPickAndPlace-v3**
+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-PandaPickAndPlace-v3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44bf0642b31c275ba21f8d6ce879c771a05ebcbec1b748c4e5aacb041cb0f2af
+size 124223

a2c-PandaPickAndPlace-v3/_stable_baselines3_version

@@ -0,0 +1 @@
+2.1.0

a2c-PandaPickAndPlace-v3/data

@@ -0,0 +1,97 @@
+{
+    "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 0x7c09d92a84c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7c09d9299b80>"
+    },
+    "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": 1700002510459144725,
+    "learning_rate": 0.0007,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "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",
+        "achieved_goal": "[[-0.48770073 -0.31277683  0.19237286]\n [-0.65784174 -0.80121917  0.19236945]\n [ 0.3519605  -0.4755582   0.19213945]\n [ 1.3595      2.0735233   0.19237606]]",
+        "desired_goal": "[[-1.5847951   0.3872726  -0.26676735]\n [-0.54414785  0.64419454 -0.571083  ]\n [-0.9475865  -1.0199058   1.5751162 ]\n [ 0.17507976 -0.15177985  0.08091964]]",
+        "observation": "[[-0.88997495  0.03684995  0.39381948  1.3694462   2.048996    1.1721516\n  -0.91256493 -0.48770073 -0.31277683  0.19237286  0.00843385 -0.01226791\n  -0.02407069  0.0631152  -0.10796599  0.08897179  0.03942534 -0.02864459\n  -0.01326825]\n [-1.3504059  -0.57021683 -0.23416084 -2.0064414  -1.5225167  -0.06978171\n  -0.91256565 -0.65784174 -0.80121917  0.19236945  0.00845669 -0.01217163\n  -0.02553804  0.06298838 -0.10820359  0.08897179  0.03942533 -0.0286446\n  -0.01354082]\n [-0.0078149  -0.19303125 -0.6108431  -0.70182544 -0.25017643 -0.23984672\n   1.2620951   0.3519605  -0.4755582   0.19213945  0.00305993 -0.01823657\n   0.0343372  -0.3108304  -1.0126635   0.0963143  -0.8372403  -0.9768143\n   1.7749538 ]\n [ 1.0674692  -0.34847823 -0.8567119  -0.00450858 -1.5303323   0.05949243\n   1.2631716   1.3595      2.0735233   0.19237606  0.00845568 -0.01237036\n  -2.2142448   0.062961   -0.10815759  0.08897179  0.03942532 -0.0286446\n  -0.01356484]]"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.07042839 -0.05378191  0.02      ]\n [ 0.12890953 -0.11412694  0.02      ]\n [ 0.00221592 -0.10594051  0.02      ]\n [-0.11326858  0.08240864  0.02      ]]",
+        "desired_goal": "[[-0.10372608 -0.03467871  0.02665618]\n [-0.12957467 -0.05333249  0.02      ]\n [ 0.08543755  0.01984082  0.09810621]\n [ 0.01722672 -0.04713127  0.2080861 ]]",
+        "observation": "[[ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00  7.04283938e-02\n  -5.37819117e-02  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00  1.28909528e-01\n  -1.14126943e-01  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00  2.21591513e-03\n  -1.05940506e-01  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00 -1.13268584e-01\n   8.24086443e-02  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+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 'gymnasium.spaces.dict.Dict'>",
+        ":serialized:": "gAWVMgQAAAAAAACMFWd5bW5hc2l1bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwUZ3ltbmFzaXVtLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowNYm91bmRlZF9iZWxvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYDAAAAAAAAAAEBAZRoE4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoHCiWAwAAAAAAAAABAQGUaCBLA4WUaCR0lFKUjAZfc2hhcGWUSwOFlIwDbG93lGgcKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZRoJHSUUpSMBGhpZ2iUaBwolgwAAAAAAAAAAAAgQQAAIEEAACBBlGgWSwOFlGgkdJRSlIwIbG93X3JlcHKUjAUtMTAuMJSMCWhpZ2hfcmVwcpSMBDEwLjCUjApfbnBfcmFuZG9tlE51YowMZGVzaXJlZF9nb2FslGgNKYGUfZQoaBBoFmgZaBwolgMAAAAAAAAAAQEBlGggSwOFlGgkdJRSlGgnaBwolgMAAAAAAAAAAQEBlGggSwOFlGgkdJRSlGgsSwOFlGguaBwolgwAAAAAAAAAAAAgwQAAIMEAACDBlGgWSwOFlGgkdJRSlGgzaBwolgwAAAAAAAAAAAAgQQAAIEEAACBBlGgWSwOFlGgkdJRSlGg4jAUtMTAuMJRoOowEMTAuMJRoPE51YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgWaBloHCiWEwAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBlGggSxOFlGgkdJRSlGgnaBwolhMAAAAAAAAAAQEBAQEBAQEBAQEBAQEBAQEBAZRoIEsThZRoJHSUUpRoLEsThZRoLmgcKJZMAAAAAAAAAAAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBZLE4WUaCR0lFKUaDNoHCiWTAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBAAAgQQAAIEEAACBBlGgWSxOFlGgkdJRSlGg4jAUtMTAuMJRoOowEMTAuMJRoPE51YnVoLE5oEE5oPE51Yi4=",
+        "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (19,), float32))])",
+        "_shape": null,
+        "dtype": null,
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True]",
+        "bounded_above": "[ True  True  True  True]",
+        "_shape": [
+            4
+        ],
+        "low": "[-1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1.]",
+        "low_repr": "-1.0",
+        "high_repr": "1.0",
+        "_np_random": null
+    },
+    "n_envs": 4,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

a2c-PandaPickAndPlace-v3/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3795f6151d02159a08ca4b550923689f37b97d76b778d3bbc57fb9ff0aed74ba
+size 52079

a2c-PandaPickAndPlace-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb92152485c670e36ebbfdb4c6014f9f9bcabeeb4041e49a774302177b7d589f
+size 53359

a2c-PandaPickAndPlace-v3/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

a2c-PandaPickAndPlace-v3/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.1.0
+- PyTorch: 2.1.0+cu118
+- GPU Enabled: True
+- Numpy: 1.23.5
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.29.1
+- OpenAI Gym: 0.25.2

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 0x7c09d92a84c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c09d9299b80>"}, "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": 1700002510459144725, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.48770073 -0.31277683  0.19237286]\n [-0.65784174 -0.80121917  0.19236945]\n [ 0.3519605  -0.4755582   0.19213945]\n [ 1.3595      2.0735233   0.19237606]]", "desired_goal": "[[-1.5847951   0.3872726  -0.26676735]\n [-0.54414785  0.64419454 -0.571083  ]\n [-0.9475865  -1.0199058   1.5751162 ]\n [ 0.17507976 -0.15177985  0.08091964]]", "observation": "[[-0.88997495  0.03684995  0.39381948  1.3694462   2.048996    1.1721516\n  -0.91256493 -0.48770073 -0.31277683  0.19237286  0.00843385 -0.01226791\n  -0.02407069  0.0631152  -0.10796599  0.08897179  0.03942534 -0.02864459\n  -0.01326825]\n [-1.3504059  -0.57021683 -0.23416084 -2.0064414  -1.5225167  -0.06978171\n  -0.91256565 -0.65784174 -0.80121917  0.19236945  0.00845669 -0.01217163\n  -0.02553804  0.06298838 -0.10820359  0.08897179  0.03942533 -0.0286446\n  -0.01354082]\n [-0.0078149  -0.19303125 -0.6108431  -0.70182544 -0.25017643 -0.23984672\n   1.2620951   0.3519605  -0.4755582   0.19213945  0.00305993 -0.01823657\n   0.0343372  -0.3108304  -1.0126635   0.0963143  -0.8372403  -0.9768143\n   1.7749538 ]\n [ 1.0674692  -0.34847823 -0.8567119  -0.00450858 -1.5303323   0.05949243\n   1.2631716   1.3595      2.0735233   0.19237606  0.00845568 -0.01237036\n  -2.2142448   0.062961   -0.10815759  0.08897179  0.03942532 -0.0286446\n  -0.01356484]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.07042839 -0.05378191  0.02      ]\n [ 0.12890953 -0.11412694  0.02      ]\n [ 0.00221592 -0.10594051  0.02      ]\n [-0.11326858  0.08240864  0.02      ]]", "desired_goal": "[[-0.10372608 -0.03467871  0.02665618]\n [-0.12957467 -0.05333249  0.02      ]\n [ 0.08543755  0.01984082  0.09810621]\n [ 0.01722672 -0.04713127  0.2080861 ]]", "observation": "[[ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00  7.04283938e-02\n  -5.37819117e-02  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00  1.28909528e-01\n  -1.14126943e-01  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00  2.21591513e-03\n  -1.05940506e-01  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12  1.97400138e-01  0.00000000e+00\n  -0.00000000e+00  0.00000000e+00  0.00000000e+00 -1.13268584e-01\n   8.24086443e-02  1.99999996e-02  0.00000000e+00 -0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n   0.00000000e+00  0.00000000e+00  0.00000000e+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 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (19,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True]", "bounded_above": "[ True  True  True  True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}

results.json

@@ -0,0 +1 @@
+{"mean_reward": -50.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-14T23:50:47.170825"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f9ba5c56282f1e2d09253633d8a9b9f3893c11e00adad2e57737b493159f9af
+size 3013