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: -5.52 +/- 1.28
+      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 sha256:2cb68abe4ada4b5a5c6f62401acd792dd5238a85d78a62dd6e66750cac87f40c
+size 108027

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 0x7f5390ea83a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f5390ea7540>"
+    },
+    "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": 1684162131528130137,
+    "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": "[[ 0.26341137 -0.1170655   0.3352828 ]\n [ 0.26341137 -0.1170655   0.3352828 ]\n [ 0.26341137 -0.1170655   0.3352828 ]\n [ 0.26341137 -0.1170655   0.3352828 ]]",
+        "desired_goal": "[[-1.0530348  -1.1787822  -1.7274783 ]\n [ 1.666499   -0.33819476 -0.17884728]\n [-1.5048816  -0.99745655 -1.6369942 ]\n [ 1.6582247   1.3653601   0.09370362]]",
+        "observation": "[[ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]\n [ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]\n [ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]\n [ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]]"
+    },
+    "_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": "[[-0.08974698 -0.08400584  0.14521691]\n [-0.08140061  0.09849281  0.08578038]\n [-0.13034512 -0.01588291  0.23306477]\n [ 0.12626371  0.13177316  0.2969232 ]]",
+        "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:c89c117cc052e4737c11d174d5e99a256b4506bfa1dc01bc2688ad38149d3d3c
+size 44670

a2c-PandaReachDense-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1264448b88395f41aad406f91363756cf9eca045b50b6732f5d2ee46ee64efbd
+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-5.15.0-71-generic-x86_64-with-glibc2.35 # 78-Ubuntu SMP Tue Apr 18 09:00:29 UTC 2023
+- Python: 3.9.13
+- Stable-Baselines3: 1.8.0
+- PyTorch: 1.11.0+cu102
+- GPU Enabled: True
+- Numpy: 1.21.2
+- 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 0x7f5390ea83a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f5390ea7540>"}, "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": 1684162131528130137, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA292GPgnA770wqqs+292GPgnA770wqqs+292GPgnA770wqqs+292GPgnA770wqqs+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA2MmGv1bilr8CHt2/10/VP90nrb6+Ize+9p/Av1BZf78HidG/tUDUPx/Erj+v5789lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADb3YY+CcDvvTCqqz5VFNg8CeaRvMC4Oj3b3YY+CcDvvTCqqz5VFNg8CeaRvMC4Oj3b3YY+CcDvvTCqqz5VFNg8CeaRvMC4Oj3b3YY+CcDvvTCqqz5VFNg8CeaRvMC4Oj2UaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[ 0.26341137 -0.1170655   0.3352828 ]\n [ 0.26341137 -0.1170655   0.3352828 ]\n [ 0.26341137 -0.1170655   0.3352828 ]\n [ 0.26341137 -0.1170655   0.3352828 ]]", "desired_goal": "[[-1.0530348  -1.1787822  -1.7274783 ]\n [ 1.666499   -0.33819476 -0.17884728]\n [-1.5048816  -0.99745655 -1.6369942 ]\n [ 1.6582247   1.3653601   0.09370362]]", "observation": "[[ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]\n [ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]\n [ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]\n [ 0.26341137 -0.1170655   0.3352828   0.02637688 -0.01780988  0.04558635]]"}, "_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": "[[-0.08974698 -0.08400584  0.14521691]\n [-0.08140061  0.09849281  0.08578038]\n [-0.13034512 -0.01588291  0.23306477]\n [ 0.12626371  0.13177316  0.2969232 ]]", "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-5.15.0-71-generic-x86_64-with-glibc2.35 # 78-Ubuntu SMP Tue Apr 18 09:00:29 UTC 2023", "Python": "3.9.13", "Stable-Baselines3": "1.8.0", "PyTorch": "1.11.0+cu102", "GPU Enabled": "True", "Numpy": "1.21.2", "Gym": "0.21.0"}}

results.json

@@ -0,0 +1 @@
+{"mean_reward": -5.52142021805048, "std_reward": 1.2796801319220894, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-15T10:17:40.605458"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9350f2789fdbc37c82e4aef04cd972b850bb697c49b4bc018554103369af437e
+size 2381