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: -3.44 +/- 1.09
+      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 sha256:9b1d45dc329d74a7d3a61f51ac9519c5af9d996b8228a7f2e9bcffd4e71df684
+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 0x7f055f6d30d0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f055f6d0e00>"
+    },
+    "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": 1681289198807341880,
+    "learning_rate": 0.0007,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAARzPiPlVijL3GUBg/RzPiPlVijL3GUBg/RzPiPlVijL3GUBg/RzPiPlVijL3GUBg/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAwRWUvy8KqT8mRYM+Yj4lP1HWiL9fBEa+XoE2vxNAy76yFFY8Hx9oPpQa3L8GTCW/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAABHM+I+VWKMvcZQGD/rhcI7ou65u4P5JrtHM+I+VWKMvcZQGD/rhcI7ou65u4P5JrtHM+I+VWKMvcZQGD/rhcI7ou65u4P5JrtHM+I+VWKMvcZQGD/rhcI7ou65u4P5JruUaA5LBEsGhpRoEnSUUpR1Lg==",
+        "achieved_goal": "[[ 0.44179747 -0.06854693  0.5949825 ]\n [ 0.44179747 -0.06854693  0.5949825 ]\n [ 0.44179747 -0.06854693  0.5949825 ]\n [ 0.44179747 -0.06854693  0.5949825 ]]",
+        "desired_goal": "[[-1.1569139   1.3206233   0.25638694]\n [ 0.64548314 -1.0690404  -0.19337605]\n [-0.7129115  -0.39697322  0.01306646]\n [ 0.22668122 -1.7195611  -0.6456913 ]]",
+        "observation": "[[ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]\n [ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]\n [ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]\n [ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]]"
+    },
+    "_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////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA3feCPF0/FL4OWi0+xuXMPSOAX71BUVg9vdVfvXWzdL0B5yo+xHWIvbe+kb0csRk+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==",
+        "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": "[[ 0.01598733 -0.14477296  0.16928884]\n [ 0.10004763 -0.05456556  0.05281186]\n [-0.0546472  -0.05974146  0.16689683]\n [-0.06663087 -0.07116454  0.15008968]]",
+        "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:": "gAWVbQEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaApLA4WUjAFDlHSUUpSMBGhpZ2iUaBIolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgKSwOFlGgVdJRSlIwNYm91bmRlZF9iZWxvd5RoEiiWAwAAAAAAAAABAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYDAAAAAAAAAAEBAZRoIUsDhZRoFXSUUpSMCl9ucF9yYW5kb22UTnViLg==",
+        "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:c2dc845446ede2d909b755033ca5bec0705b9315d77aeaf5ad0bd11f30f09bbd
+size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4c2500bb0199170983acbd5a6ddada150028d98ae073cc4bac694c7a1efe3331
+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 0x7f055f6d30d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f055f6d0e00>"}, "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": 1681289198807341880, "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": "[[ 0.44179747 -0.06854693  0.5949825 ]\n [ 0.44179747 -0.06854693  0.5949825 ]\n [ 0.44179747 -0.06854693  0.5949825 ]\n [ 0.44179747 -0.06854693  0.5949825 ]]", "desired_goal": "[[-1.1569139   1.3206233   0.25638694]\n [ 0.64548314 -1.0690404  -0.19337605]\n [-0.7129115  -0.39697322  0.01306646]\n [ 0.22668122 -1.7195611  -0.6456913 ]]", "observation": "[[ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]\n [ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]\n [ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]\n [ 0.44179747 -0.06854693  0.5949825   0.00593637 -0.0056742  -0.00254783]]"}, "_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": "[[ 0.01598733 -0.14477296  0.16928884]\n [ 0.10004763 -0.05456556  0.05281186]\n [-0.0546472  -0.05974146  0.16689683]\n [-0.06663087 -0.07116454  0.15008968]]", "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, "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": -3.435800801217556, "std_reward": 1.092864040441291, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-12T09:38:06.153291"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ab3b5c3ce78647f8a3949adb303019eed1fce8d1dabfa543f7752eecaaac866
+size 2381