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 sha256:4803fa7c8ee54566590a2b47777c547d18338e8ade6a45d94eca4b56b3bd286d
+size 124203

a2c-PandaPickAndPlace-v3/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

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 0x7fb9cea079c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fb9ce9fbc40>"
+    },
+    "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": 1723367244859958134,
+    "learning_rate": 0.0007,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "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",
+        "achieved_goal": "[[-0.9484688  -1.0925113   0.09267545]\n [ 1.1389405   0.5643116   0.09267314]\n [-0.7011865   0.90016073  0.09266672]\n [ 0.36127654  1.0847107   0.09266672]]",
+        "desired_goal": "[[-0.9419412   0.18630216 -0.0829126 ]\n [-1.1491369  -0.48511037  0.15064095]\n [-0.371754    1.3614675  -1.0909885 ]\n [-1.5629841   1.0279758   1.1657375 ]]",
+        "observation": "[[-1.249996    0.73313344 -1.1254681  -3.271343   -2.591805    0.20322289\n  -0.6028426  -0.9484688  -1.0925113   0.09267545 -0.0139475   0.0124266\n   0.00449243  0.04900742  0.06006775  0.04515425 -0.02546535 -0.00855748\n   0.00982054]\n [ 0.0221082  -2.217978    1.2429067  -0.0772486  -0.07166588  0.25675088\n   1.2337332   1.1389405   0.5643116   0.09267314 -0.01409611  0.01248622\n   0.00557273  0.04951345  0.05984363  0.04537643 -0.02275941 -0.00698271\n   0.01011066]\n [ 0.8198845   0.24663366 -1.1389121   0.1337884   0.33655053 -0.2736263\n   1.2304679  -0.7011865   0.90016073  0.09266672 -0.01405242  0.01265054\n   0.00407986  0.04930323  0.05942349  0.04537643 -0.02275942 -0.00698272\n   0.00966245]\n [ 0.01434503 -2.2261174   1.2498802  -0.07414007 -0.0686443   0.252372\n   1.4841684   0.36127654  1.0847107   0.09266672 -0.0140122   0.01213033\n   0.00397587  0.04928897  0.05969071  0.04537643 -0.02275942 -0.00698273\n   0.00966243]]"
+    },
+    "_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": "[[ 0.13300233  0.0680071   0.02      ]\n [ 0.06535749  0.03507807  0.02      ]\n [ 0.0940716   0.13891219  0.02      ]\n [ 0.04188224 -0.1334683   0.02      ]]",
+        "desired_goal": "[[-0.0878693   0.08601099  0.06457305]\n [ 0.09355531 -0.08523881  0.21546665]\n [ 0.02741212 -0.00365717  0.20204312]\n [-0.0981908   0.04118907  0.0610145 ]]",
+        "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00  0.0000000e+00  1.3300233e-01\n   6.8007104e-02  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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  0.0000000e+00  6.5357491e-02\n   3.5078075e-02  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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  0.0000000e+00  9.4071597e-02\n   1.3891219e-01  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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  0.0000000e+00  4.1882236e-02\n  -1.3346830e-01  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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 '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:ac834264856dc0b2b4bd48323d5af5b676e5580c0c34d6e6effe00dd96cc7d0b
+size 52079

a2c-PandaPickAndPlace-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:22bc79c58880e040aecc25c1c4f8cc8c2872c17c5476d52b07a5582a74a04ec1
+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 +1,8 @@
+- OS: Linux-5.15.0-105-generic-x86_64-with-glibc2.31 # 115~20.04.1-Ubuntu SMP Mon Apr 15 17:33:04 UTC 2024
+- Python: 3.11.9
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.1+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.0.0
+- Gymnasium: 0.28.1

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 0x7fb9cea079c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fb9ce9fbc40>"}, "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": 1723367244859958134, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.9484688  -1.0925113   0.09267545]\n [ 1.1389405   0.5643116   0.09267314]\n [-0.7011865   0.90016073  0.09266672]\n [ 0.36127654  1.0847107   0.09266672]]", "desired_goal": "[[-0.9419412   0.18630216 -0.0829126 ]\n [-1.1491369  -0.48511037  0.15064095]\n [-0.371754    1.3614675  -1.0909885 ]\n [-1.5629841   1.0279758   1.1657375 ]]", "observation": "[[-1.249996    0.73313344 -1.1254681  -3.271343   -2.591805    0.20322289\n  -0.6028426  -0.9484688  -1.0925113   0.09267545 -0.0139475   0.0124266\n   0.00449243  0.04900742  0.06006775  0.04515425 -0.02546535 -0.00855748\n   0.00982054]\n [ 0.0221082  -2.217978    1.2429067  -0.0772486  -0.07166588  0.25675088\n   1.2337332   1.1389405   0.5643116   0.09267314 -0.01409611  0.01248622\n   0.00557273  0.04951345  0.05984363  0.04537643 -0.02275941 -0.00698271\n   0.01011066]\n [ 0.8198845   0.24663366 -1.1389121   0.1337884   0.33655053 -0.2736263\n   1.2304679  -0.7011865   0.90016073  0.09266672 -0.01405242  0.01265054\n   0.00407986  0.04930323  0.05942349  0.04537643 -0.02275942 -0.00698272\n   0.00966245]\n [ 0.01434503 -2.2261174   1.2498802  -0.07414007 -0.0686443   0.252372\n   1.4841684   0.36127654  1.0847107   0.09266672 -0.0140122   0.01213033\n   0.00397587  0.04928897  0.05969071  0.04537643 -0.02275942 -0.00698273\n   0.00966243]]"}, "_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": "[[ 0.13300233  0.0680071   0.02      ]\n [ 0.06535749  0.03507807  0.02      ]\n [ 0.0940716   0.13891219  0.02      ]\n [ 0.04188224 -0.1334683   0.02      ]]", "desired_goal": "[[-0.0878693   0.08601099  0.06457305]\n [ 0.09355531 -0.08523881  0.21546665]\n [ 0.02741212 -0.00365717  0.20204312]\n [-0.0981908   0.04118907  0.0610145 ]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00  0.0000000e+00  1.3300233e-01\n   6.8007104e-02  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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  0.0000000e+00  6.5357491e-02\n   3.5078075e-02  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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  0.0000000e+00  9.4071597e-02\n   1.3891219e-01  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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  0.0000000e+00  4.1882236e-02\n  -1.3346830e-01  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  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 '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-5.15.0-105-generic-x86_64-with-glibc2.31 # 115~20.04.1-Ubuntu SMP Mon Apr 15 17:33:04 UTC 2024", "Python": "3.11.9", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1"}}

results.json

@@ -0,0 +1 @@
+{"mean_reward": -50.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-08-11T19:43:14.808259"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ad5a67e3d8790123798ab34fd7f9596c85e3114dd8432cc87ad17f0657bfb5ef
+size 2953