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: -2.14 +/- 0.97
+      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 sha256:19798562014ec401010ba7e03bbe1c68224147780808035f86e39f726bcd8db2
+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 0x7f5069f44550>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f5069f43780>"
+    },
+    "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": 1682535568843698540,
+    "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": "[[ 0.43551135 -0.02111972  0.57698035]\n [ 0.43551135 -0.02111972  0.57698035]\n [ 0.43551135 -0.02111972  0.57698035]\n [ 0.43551135 -0.02111972  0.57698035]]",
+        "desired_goal": "[[-1.0217866   1.3236643   1.2931019 ]\n [ 0.25115016 -1.582008   -1.6808026 ]\n [-0.01079612 -1.5847905  -0.5820552 ]\n [ 0.15677336  1.180462   -0.0080049 ]]",
+        "observation": "[[ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]\n [ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]\n [ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]\n [ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]]"
+    },
+    "_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": "[[ 0.06934346 -0.12214375  0.25850433]\n [-0.03747467  0.03837039  0.26563972]\n [-0.06154689 -0.08564879  0.0367469 ]\n [-0.10544878 -0.09851675  0.19893494]]",
+        "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:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIUpliDoIO97+UhpRSlIwBbJRLMowBdJRHQKojP9aUzKt1fZQoaAZoCWgPQwiPi2oRUQzyv5SGlFKUaBVLMmgWR0CqIwCIDYAbdX2UKGgGaAloD0MIGLMlqyIc8r+UhpRSlGgVSzJoFkdAqiLCaZx7zHV9lChoBmgJaA9DCHJTA83nHADAlIaUUpRoFUsyaBZHQKoihIEKVpt1fZQoaAZoCWgPQwjRH5p5cs34v5SGlFKUaBVLMmgWR0CqJV4VIqb0dX2UKGgGaAloD0MI9DXLZaMz9b+UhpRSlGgVSzJoFkdAqiUe4qgAZXV9lChoBmgJaA9DCBu5bkp5DQbAlIaUUpRoFUsyaBZHQKok38XN1Qt1fZQoaAZoCWgPQwj6t8t+3YkHwJSGlFKUaBVLMmgWR0CqJKHVPN3XdX2UKGgGaAloD0MIdNTRcTWyBMCUhpRSlGgVSzJoFkdAqic9cjZ+QXV9lChoBmgJaA9DCEGDTZ1Hhf2/lIaUUpRoFUsyaBZHQKom/mbLEDR1fZQoaAZoCWgPQwikchO1NJcHwJSGlFKUaBVLMmgWR0CqJr8Xm/34dX2UKGgGaAloD0MIlRCsqpff7b+UhpRSlGgVSzJoFkdAqiaBJZntfHV9lChoBmgJaA9DCI4CRMGMqfi/lIaUUpRoFUsyaBZHQKoo8q6OHWV1fZQoaAZoCWgPQwh3acNhaSALwJSGlFKUaBVLMmgWR0CqKLKSHM2WdX2UKGgGaAloD0MI10y+2ebG+7+UhpRSlGgVSzJoFkdAqihylnAZbnV9lChoBmgJaA9DCF3dsdgm1fO/lIaUUpRoFUsyaBZHQKooM8jAzpJ1fZQoaAZoCWgPQwgeozzzctgCwJSGlFKUaBVLMmgWR0CqKhg5Jbt7dX2UKGgGaAloD0MIJxdjYB1H/7+UhpRSlGgVSzJoFkdAqinYQnQY13V9lChoBmgJaA9DCGXFcHUABAvAlIaUUpRoFUsyaBZHQKopmFQEZBN1fZQoaAZoCWgPQwiYiLfOvz0FwJSGlFKUaBVLMmgWR0CqKVmfwqiHdX2UKGgGaAloD0MIu9HHfECACMCUhpRSlGgVSzJoFkdAqitBcHGCI3V9lChoBmgJaA9DCLqe6LrwYwPAlIaUUpRoFUsyaBZHQKorATyJ9Ap1fZQoaAZoCWgPQwgzTkNU4W8CwJSGlFKUaBVLMmgWR0CqKsD+zdDZdX2UKGgGaAloD0MIbAiOy7jJC8CUhpRSlGgVSzJoFkdAqiqCL61stXV9lChoBmgJaA9DCHQNMzSeiO+/lIaUUpRoFUsyaBZHQKosbWattAN1fZQoaAZoCWgPQwhKlSh7S/kFwJSGlFKUaBVLMmgWR0CqLC0/W1+idX2UKGgGaAloD0MINuhLb39uBsCUhpRSlGgVSzJoFkdAqivtR+BpYnV9lChoBmgJaA9DCJuuJ7ouXALAlIaUUpRoFUsyaBZHQKorro0ygwp1fZQoaAZoCWgPQwjg1t081SEBwJSGlFKUaBVLMmgWR0CqLZWhh6SldX2UKGgGaAloD0MIDvYmhuQk9r+UhpRSlGgVSzJoFkdAqi1VeruIAXV9lChoBmgJaA9DCJBq2O+JtQDAlIaUUpRoFUsyaBZHQKotFWdVea91fZQoaAZoCWgPQwhZNnNIaqEQwJSGlFKUaBVLMmgWR0CqLNaXjU/fdX2UKGgGaAloD0MImPvkKEA0BcCUhpRSlGgVSzJoFkdAqi7Jk3CKrXV9lChoBmgJaA9DCCrG+ZtQSP+/lIaUUpRoFUsyaBZHQKouiXlbNbF1fZQoaAZoCWgPQwg4ukp311nnv5SGlFKUaBVLMmgWR0CqLkl1KXfJdX2UKGgGaAloD0MI9mIoJ9pV87+UhpRSlGgVSzJoFkdAqi4KwfQrtnV9lChoBmgJaA9DCEUvo1huqfO/lIaUUpRoFUsyaBZHQKov/gb6xgR1fZQoaAZoCWgPQwikAFEwYwr+v5SGlFKUaBVLMmgWR0CqL74Gt6omdX2UKGgGaAloD0MIrKxtisfF6r+UhpRSlGgVSzJoFkdAqi9+Op84P3V9lChoBmgJaA9DCF+2nbZGZAPAlIaUUpRoFUsyaBZHQKovP5Y5ksl1fZQoaAZoCWgPQwhXeQJhpzgEwJSGlFKUaBVLMmgWR0CqMTRh2GIsdX2UKGgGaAloD0MIj4mUZvN4BsCUhpRSlGgVSzJoFkdAqjD0TBZZCHV9lChoBmgJaA9DCGMpkq8EohHAlIaUUpRoFUsyaBZHQKowtH2h7E51fZQoaAZoCWgPQwhWDi2ynW8AwJSGlFKUaBVLMmgWR0CqMHW2G7BgdX2UKGgGaAloD0MIjZYDPdQ29L+UhpRSlGgVSzJoFkdAqjKGFtbcGnV9lChoBmgJaA9DCE3aVN0jm+u/lIaUUpRoFUsyaBZHQKoyRhvze411fZQoaAZoCWgPQwj7eOi7W8kRwJSGlFKUaBVLMmgWR0CqMgYbsF+vdX2UKGgGaAloD0MI9iSwOQePBcCUhpRSlGgVSzJoFkdAqjHIOtnwonV9lChoBmgJaA9DCAWLw5lfzfa/lIaUUpRoFUsyaBZHQKozsqe9SMt1fZQoaAZoCWgPQwithsQ9lh4BwJSGlFKUaBVLMmgWR0CqM3Kjafz0dX2UKGgGaAloD0MIWfs726P3/b+UhpRSlGgVSzJoFkdAqjMzXe3x4XV9lChoBmgJaA9DCCeEDrqE4wXAlIaUUpRoFUsyaBZHQKoy9KqXF991fZQoaAZoCWgPQwg75dGNsMgQwJSGlFKUaBVLMmgWR0CqNN4WUKRddX2UKGgGaAloD0MIOUTcnEoG4b+UhpRSlGgVSzJoFkdAqjSe2VmjCnV9lChoBmgJaA9DCHcTfNP0Weu/lIaUUpRoFUsyaBZHQKo0X4NZvDR1fZQoaAZoCWgPQwjt8UI6PMQBwJSGlFKUaBVLMmgWR0CqNCHctXgcdX2UKGgGaAloD0MIsmSO5V1VAcCUhpRSlGgVSzJoFkdAqjYZiobXH3V9lChoBmgJaA9DCKJESx5Pi/C/lIaUUpRoFUsyaBZHQKo12Zof0Vd1fZQoaAZoCWgPQwi9jGK5pfUSwJSGlFKUaBVLMmgWR0CqNZmza9K3dX2UKGgGaAloD0MI5lyKq8o+77+UhpRSlGgVSzJoFkdAqjVbFCLMtHV9lChoBmgJaA9DCH1BCwkY3fu/lIaUUpRoFUsyaBZHQKo3SKUFB6d1fZQoaAZoCWgPQwiPUZ55OWzxv5SGlFKUaBVLMmgWR0CqNwiZF5OadX2UKGgGaAloD0MIa2EW2jktC8CUhpRSlGgVSzJoFkdAqjbImqo60nV9lChoBmgJaA9DCFUuVP61HAvAlIaUUpRoFUsyaBZHQKo2igGr0at1fZQoaAZoCWgPQwhM3ZVdMPj3v5SGlFKUaBVLMmgWR0CqOHL26ClKdX2UKGgGaAloD0MIZ9E7FXCvBsCUhpRSlGgVSzJoFkdAqjgzEit7r3V9lChoBmgJaA9DCPZ5jPLMGxLAlIaUUpRoFUsyaBZHQKo38wSrYGt1fZQoaAZoCWgPQwgr/BnerAH8v5SGlFKUaBVLMmgWR0CqN7RekYXPdX2UKGgGaAloD0MI4C2QoPjRAsCUhpRSlGgVSzJoFkdAqjnFF6RhdHV9lChoBmgJaA9DCEevBigNNfi/lIaUUpRoFUsyaBZHQKo5hf3N9ph1fZQoaAZoCWgPQwg83XniOdvwv5SGlFKUaBVLMmgWR0CqOUYqgAZLdX2UKGgGaAloD0MIo1huaTWk97+UhpRSlGgVSzJoFkdAqjkHe7+T/3V9lChoBmgJaA9DCKJgxhSs4RHAlIaUUpRoFUsyaBZHQKo6+rp7kXF1fZQoaAZoCWgPQwjhCb3+JN4DwJSGlFKUaBVLMmgWR0CqOrq9wm3OdX2UKGgGaAloD0MIZ3v0hvtIA8CUhpRSlGgVSzJoFkdAqjp7neSB9XV9lChoBmgJaA9DCNF14QfnU/G/lIaUUpRoFUsyaBZHQKo6PdYW+Gp1fZQoaAZoCWgPQwgf+BisOLUAwJSGlFKUaBVLMmgWR0CqPFCuMdcTdX2UKGgGaAloD0MIDhDM0ePXAsCUhpRSlGgVSzJoFkdAqjwQqI7/43V9lChoBmgJaA9DCMFWCRaHMwHAlIaUUpRoFUsyaBZHQKo70dS2php1fZQoaAZoCWgPQwiB64oZ4S33v5SGlFKUaBVLMmgWR0CqO5Mg+yJLdX2UKGgGaAloD0MI+wRQjCzZDMCUhpRSlGgVSzJoFkdAqj4BjQRf4XV9lChoBmgJaA9DCB2PGaiMf+O/lIaUUpRoFUsyaBZHQKo9wi5d4V11fZQoaAZoCWgPQwjBcK5hhkb3v5SGlFKUaBVLMmgWR0CqPYLqD9OzdX2UKGgGaAloD0MIY9NKIZBL87+UhpRSlGgVSzJoFkdAqj1FDMNc4nV9lChoBmgJaA9DCCzvqgfMowrAlIaUUpRoFUsyaBZHQKo/5dqtYCB1fZQoaAZoCWgPQwhzgjY5fJICwJSGlFKUaBVLMmgWR0CqP6apxWDIdX2UKGgGaAloD0MIN4jWijbH+r+UhpRSlGgVSzJoFkdAqj9nbAUL2HV9lChoBmgJaA9DCF+zXDY6Z+i/lIaUUpRoFUsyaBZHQKo/KYqoZQ51fZQoaAZoCWgPQwj2fw7z5SUBwJSGlFKUaBVLMmgWR0CqQd8s189fdX2UKGgGaAloD0MIlxqhn6mX8r+UhpRSlGgVSzJoFkdAqkGf3i704HV9lChoBmgJaA9DCNi4/l2f2QXAlIaUUpRoFUsyaBZHQKpBYRChN/R1fZQoaAZoCWgPQwjWH2EYsGT+v5SGlFKUaBVLMmgWR0CqQSN7KJVKdX2UKGgGaAloD0MIDD84nzqW+7+UhpRSlGgVSzJoFkdAqkQUe2d/a3V9lChoBmgJaA9DCM7g7xezZfK/lIaUUpRoFUsyaBZHQKpD1dxAB1d1fZQoaAZoCWgPQwhxHHi13JkBwJSGlFKUaBVLMmgWR0CqQ5iKJl8PdX2UKGgGaAloD0MIh8PSwI9KAMCUhpRSlGgVSzJoFkdAqkNarPt2LnV9lChoBmgJaA9DCOuM74tLNQHAlIaUUpRoFUsyaBZHQKpGH6be/Hp1fZQoaAZoCWgPQwiyYyMQr2v5v5SGlFKUaBVLMmgWR0CqReDTSb6QdX2UKGgGaAloD0MI3SObq+b59b+UhpRSlGgVSzJoFkdAqkWhe/pMYnV9lChoBmgJaA9DCIqPT8jO2/S/lIaUUpRoFUsyaBZHQKpFY4VARkF1ZS4="
+    },
+    "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 sha256:59721ef4318f1cee5c3b557d864de93ee0f05657d3fbe1d0caf0a055eaa8e85c
+size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bf660de7c15243ead06cc2f2abab45c3b67f73bb1a3ebe30528a68846eabeb2c
+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 0x7f5069f44550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f5069f43780>"}, "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": 1682535568843698540, "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": "[[ 0.43551135 -0.02111972  0.57698035]\n [ 0.43551135 -0.02111972  0.57698035]\n [ 0.43551135 -0.02111972  0.57698035]\n [ 0.43551135 -0.02111972  0.57698035]]", "desired_goal": "[[-1.0217866   1.3236643   1.2931019 ]\n [ 0.25115016 -1.582008   -1.6808026 ]\n [-0.01079612 -1.5847905  -0.5820552 ]\n [ 0.15677336  1.180462   -0.0080049 ]]", "observation": "[[ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]\n [ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]\n [ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]\n [ 0.43551135 -0.02111972  0.57698035  0.016738   -0.00383849  0.01601734]]"}, "_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": "[[ 0.06934346 -0.12214375  0.25850433]\n [-0.03747467  0.03837039  0.26563972]\n [-0.06154689 -0.08564879  0.0367469 ]\n [-0.10544878 -0.09851675  0.19893494]]", "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": -2.1446911875158547, "std_reward": 0.9680834998388873, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-26T19:57:25.764586"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3548daba70c5c6099cabc95f8f6a2bb8bece95a4675e392bc4d50eb833eb423b
+size 2381