Upload Round2 PandaReachDense-v2 A2C Model

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: -1.73 +/- 0.21
+      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:c33072b25daf4af279b915637b3064b00e2149021e86c9afc0742d5c4676df54
+size 113042

a2c-PandaReachDense-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

a2c-PandaReachDense-v2/data

@@ -0,0 +1,94 @@
+{
+    "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 0x7feedac01940>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7feedac03640>"
+    },
+    "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:": "gAWVUgMAAAAAAACMD2d5bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwOZ3ltLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUaBCTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowGX3NoYXBllEsDhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFUsDhZSMAUOUdJRSlIwEaGlnaJRoHSiWDAAAAAAAAAAAACBBAAAgQQAAIEGUaBVLA4WUaCB0lFKUjA1ib3VuZGVkX2JlbG93lGgdKJYDAAAAAAAAAAEBAZRoEowCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZRoIHSUUpSMDWJvdW5kZWRfYWJvdmWUaB0olgMAAAAAAAAAAQEBlGgsSwOFlGggdJRSlIwKX25wX3JhbmRvbZROdWKMDGRlc2lyZWRfZ29hbJRoDSmBlH2UKGgQaBVoGEsDhZRoGmgdKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFUsDhZRoIHSUUpRoI2gdKJYMAAAAAAAAAAAAIEEAACBBAAAgQZRoFUsDhZRoIHSUUpRoKGgdKJYDAAAAAAAAAAEBAZRoLEsDhZRoIHSUUpRoMmgdKJYDAAAAAAAAAAEBAZRoLEsDhZRoIHSUUpRoN051YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgVaBhLBoWUaBpoHSiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBVLBoWUaCB0lFKUaCNoHSiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBVLBoWUaCB0lFKUaChoHSiWBgAAAAAAAAABAQEBAQGUaCxLBoWUaCB0lFKUaDJoHSiWBgAAAAAAAAABAQEBAQGUaCxLBoWUaCB0lFKUaDdOdWJ1aBhOaBBOaDdOdWIu",
+        "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": "RandomState(MT19937)"
+    },
+    "n_envs": 4,
+    "num_timesteps": 200000,
+    "_total_timesteps": 200000,
+    "_num_timesteps_at_start": 0,
+    "seed": 42,
+    "action_noise": null,
+    "start_time": 1679667826065304585,
+    "learning_rate": 0.00096,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAX9y/Prpn67t7xQ8/X9y/Prpn67t7xQ8/X9y/Prpn67t7xQ8/X9y/Prpn67t7xQ8/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAc++oPhJVBL9mOaA/C2nTP+OR2j+EK5U/3Tydv+ru/D6iRoc/Nz7lPMRysL90Yq6/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAABf3L8+umfru3vFDz8MnDa8kNN6uhKPHrtf3L8+umfru3vFDz8MnDa8kNN6uhKPHrtf3L8+umfru3vFDz8MnDa8kNN6uhKPHrtf3L8+umfru3vFDz8MnDa8kNN6uhKPHruUaA5LBEsGhpRoEnSUUpR1Lg==",
+        "achieved_goal": "[[ 0.37472817 -0.007184    0.56160706]\n [ 0.37472817 -0.007184    0.56160706]\n [ 0.37472817 -0.007184    0.56160706]\n [ 0.37472817 -0.007184    0.56160706]]",
+        "desired_goal": "[[ 0.32995185 -0.51692307  1.2517517 ]\n [ 1.6516432   1.7075771   1.1653905 ]\n [-1.2284199   0.49401027  1.056843  ]\n [ 0.02798377 -1.3785024  -1.3623796 ]]",
+        "observation": "[[ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]\n [ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]\n [ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]\n [ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]]"
+    },
+    "_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": "[[ 0.06581722  0.02034176  0.28795475]\n [-0.08548318 -0.01724023  0.02773104]\n [ 0.00485728  0.04103243  0.24416253]\n [ 0.05257429  0.05634164  0.21994595]]",
+        "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": 37500,
+    "n_steps": 8,
+    "gamma": 0.99,
+    "gae_lambda": 0.9,
+    "ent_coef": 0.0,
+    "vf_coef": 0.4,
+    "max_grad_norm": 0.5,
+    "normalize_advantage": false
+}

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c98489066ba4ce9e6330cfb29729b7047ab2b27f5e6d1afb3e55c7a1644f325
+size 45438

a2c-PandaReachDense-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f0d29a167022cf51498c9e82199bdd1914fccd6d7bafed801db08dae5ff02d89
+size 46718

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: 1.7.0
+- PyTorch: 1.13.1+cu116
+- 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 0x7feedac01940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7feedac03640>"}, "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": "RandomState(MT19937)"}, "n_envs": 4, "num_timesteps": 200000, "_total_timesteps": 200000, "_num_timesteps_at_start": 0, "seed": 42, "action_noise": null, "start_time": 1679667826065304585, "learning_rate": 0.00096, "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": "[[ 0.37472817 -0.007184    0.56160706]\n [ 0.37472817 -0.007184    0.56160706]\n [ 0.37472817 -0.007184    0.56160706]\n [ 0.37472817 -0.007184    0.56160706]]", "desired_goal": "[[ 0.32995185 -0.51692307  1.2517517 ]\n [ 1.6516432   1.7075771   1.1653905 ]\n [-1.2284199   0.49401027  1.056843  ]\n [ 0.02798377 -1.3785024  -1.3623796 ]]", "observation": "[[ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]\n [ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]\n [ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]\n [ 0.37472817 -0.007184    0.56160706 -0.0111456  -0.00095683 -0.00241942]]"}, "_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": "[[ 0.06581722  0.02034176  0.28795475]\n [-0.08548318 -0.01724023  0.02773104]\n [ 0.00485728  0.04103243  0.24416253]\n [ 0.05257429  0.05634164  0.21994595]]", "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": 37500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "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

@@ -0,0 +1 @@
+{"mean_reward": -1.7257298845332116, "std_reward": 0.21271943791970305, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-24T14:34:10.318527"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1884f27816a93284c9e8a109e93ebf80e154b7b769478f9a2809d7aab682ce08
+size 3056