OsherElhadad commited on
Commit
26ace59
·
verified ·
1 Parent(s): 56f6636

Initial commit

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - PandaReachJointsSparse-v3
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: PandaReachJointsSparse-v3
16
+ type: PandaReachJointsSparse-v3
17
+ metrics:
18
+ - type: mean_reward
19
+ value: -1.60 +/- 0.80
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **PandaReachJointsSparse-v3**
25
+ This is a trained model of a **PPO** agent playing **PandaReachJointsSparse-v3**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
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 0x000002203F1A7DC0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x000002203F1A63F0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1007616, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716042527484235200, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-0.12248932 -0.48811525 0.06938252]\n [-0.50589657 0.08260352 0.6800011 ]\n [-2.0608335 -1.4326502 -1.0788187 ]\n [ 0.08415911 -0.67595214 -1.4208055 ]]", "desired_goal": "[[-0.2540757 -0.67114425 -1.4554731 ]\n [-1.0265082 0.85943544 1.2258997 ]\n [-1.44641 -1.5638996 -0.7453344 ]\n [ 0.71316147 -0.6702961 -1.5549533 ]]", "observation": "[[-0.12248932 -0.48811525 0.06938252 -1.7645435 -1.9350079 -2.1171045 ]\n [-0.50589657 0.08260352 0.6800011 -0.1686671 -0.04845463 0.51448774]\n [-2.0608335 -1.4326502 -1.0788187 -1.9790804 -1.1595335 -0.5520993 ]\n [ 0.08415911 -0.67595214 -1.4208055 0.54249126 0.1638698 -0.2490084 ]]"}, "_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": "[[ 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": "[[ 0.03838971 -0.00719318 0.21197449]\n [ 0.06162451 0.06356581 0.23944677]\n [ 0.1301866 0.0657801 0.12885888]\n [ 0.05756394 0.11797851 0.1131525 ]]", "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": -0.007616000000000067, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwBgAAAAAAACMAWyUSweMAXSUR0CiwNRUedTYdX2UKGgGR8AYAAAAAAAAaAdLB2gIR0CiwJlvqC6IdX2UKGgGR8AUAAAAAAAAaAdLBmgIR0CiwF2HtWuHdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwRcRlHz6dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwGJG4I8hdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwOJGvwEydX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwGJG4I8hdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwOpLEk0KdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwSJLmITHdX2UKGgGR8AYAAAAAAAAaAdLB2gIR0CiwKpLdvbXdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwHJLEk0KdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwPpLVWjodX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwLpLuhK2dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwHpLdvbXdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwTJL26CldX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwPpLVWjodX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwHpLdvbXdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwMJLdvbXdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwTpLmITHdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwQJLEk0KdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwIpLEk0KdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwJJLEk0KdX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwJJLEk0KdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwRJK8L8adX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwNJLVWjodX2UKGgGR8AUAAAAAAAAaAdLBmgIR0CiwVJLmITHdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwJpLEk0KdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwOJLmITHdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwSJLM9r5dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwOpLVWjodX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwKpLEk0KdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwWJLdvbXdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwTJK8L8adX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwPJLVWjodX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwWpLdvbXdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwLpLEk0KdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwTpK8L8adX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwTpK8L8adX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwXpLdvbXdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwUJK8L8adX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwQJLVWjodX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwMpHZsbedX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwQpHqeK9dX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwYJHy3CsdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwNJLuhK2dX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwVJLmITHdX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwNJLuhK2dX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwZJHy3CsdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwVpHRTjvdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwNpHZsbedX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwRpHqeK9dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwZpHqeK9dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwSJHiFTOdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwaJLuhK2dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwSpLmITHdX2UKGgGR8AUAAAAAAAAaAdLBmgIR0CiwWpLM9r5dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwapMYdhidX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwXJL26CldX2UKGgGR8AcAAAAAAAAaAdLCGgIR0CiwPJL/S6UdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwbJLmITHdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwXpK8L8adX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwTpLdvbXdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwPpLEk0KdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwbpMQEpzdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwYJLuhK2dX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwUpHiFTOdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwYpHI6sAdX2UKGgGR8AUAAAAAAAAaAdLBmgIR0CiwRJIDoyLdX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwZJH7P6bdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwVJIUahpdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwcpIczZZdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwVpL/S6UdX2UKGgGR8AYAAAAAAAAaAdLB2gIR0CiwapHqeK9dX2UKGgGR8AcAAAAAAAAaAdLCGgIR0CiwSpHy3CsdX2UKGgGR8AYAAAAAAAAaAdLB2gIR0CiweJIMBp6dX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwWpIMBp6dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwTJH7P6bdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwepIUahpdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwXJIMBp6dX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwTJH7P6bdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwfJIczZZdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwbpH7P6bdX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwfpMHryEdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwYJL/S6UdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwUJLuhK2dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwgJIMBp6dX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwYpIDoyLdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwcpHqeK9dX2UKGgGRwAAAAAAAAAAaAdLAWgIR0CiwdJK8L8adX2UKGgGR7/wAAAAAAAAaAdLAmgIR0CiwZJLVWjodX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwVJLEk0KdX2UKGgGR8AQAAAAAAAAaAdLBWgIR0CiwhJHqeK9dX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwZpHiFTOdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwVpHRTjvdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwdpHI6sAdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwhpHy3CsdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwWJHZsbedX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwapIczZZdX2UKGgGR8AIAAAAAAAAaAdLBGgIR0CiwepIDoyLdX2UKGgGR8AAAAAAAAAAaAdLA2gIR0CiwiJIlMRIdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1230, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":serialized:": "gAWVqgMAAAAAAACMFWd5bW5hc2l1bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwUZ3ltbmFzaXVtLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUaBCTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowNYm91bmRlZF9iZWxvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYDAAAAAAAAAAEBAZRoEowCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoGyiWAwAAAAAAAAABAQGUaB9LA4WUaCN0lFKUjAZfc2hhcGWUSwOFlIwDbG93lGgbKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFUsDhZRoI3SUUpSMBGhpZ2iUaBsolgwAAAAAAAAAAAAgQQAAIEEAACBBlGgVSwOFlGgjdJRSlIwIbG93X3JlcHKUjAUtMTAuMJSMCWhpZ2hfcmVwcpSMBDEwLjCUjApfbnBfcmFuZG9tlE51YowMZGVzaXJlZF9nb2FslGgNKYGUfZQoaBBoFWgYaBsolgMAAAAAAAAAAQEBlGgfSwOFlGgjdJRSlGgmaBsolgMAAAAAAAAAAQEBlGgfSwOFlGgjdJRSlGgrSwOFlGgtaBsolgwAAAAAAAAAAAAgwQAAIMEAACDBlGgVSwOFlGgjdJRSlGgyaBsolgwAAAAAAAAAAAAgQQAAIEEAACBBlGgVSwOFlGgjdJRSlGg3jAUtMTAuMJRoOYwEMTAuMJRoO051YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgVaBhoGyiWBgAAAAAAAAABAQEBAQGUaB9LBoWUaCN0lFKUaCZoGyiWBgAAAAAAAAABAQEBAQGUaB9LBoWUaCN0lFKUaCtLBoWUaC1oGyiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBVLBoWUaCN0lFKUaDJoGyiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBVLBoWUaCN0lFKUaDeMBS0xMC4wlGg5jAQxMC4wlGg7TnVidWgrTmgQTmg7TnViLg==", "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, (6,), 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 True True True]", "bounded_above": "[ True True True True True True True]", "_shape": [7], "low": "[-1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 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": "Windows-10-10.0.22631-SP0 10.0.22631", "Python": "3.8.16", "Stable-Baselines3": "2.0.0a5", "PyTorch": "1.12.1+cpu", "GPU Enabled": "False", "Numpy": "1.24.4", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}
ppo-PandaReachJointsSparse-v3-1000000.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:84558fe2cae183000743f7e47b97bae0e3d9f23e315d54d039e35273bdb3ba92
3
+ size 157584
ppo-PandaReachJointsSparse-v3-1000000/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-PandaReachJointsSparse-v3-1000000/data ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__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 ",
7
+ "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x000002203F1A7DC0>",
8
+ "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc_data object at 0x000002203F1A63F0>"
10
+ },
11
+ "verbose": 1,
12
+ "policy_kwargs": {},
13
+ "num_timesteps": 1007616,
14
+ "_total_timesteps": 1000000,
15
+ "_num_timesteps_at_start": 0,
16
+ "seed": null,
17
+ "action_noise": null,
18
+ "start_time": 1716042527484235200,
19
+ "learning_rate": 0.0003,
20
+ "tensorboard_log": null,
21
+ "_last_obs": {
22
+ ":type:": "<class 'collections.OrderedDict'>",
23
+ ":serialized:": "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",
24
+ "achieved_goal": "[[-0.12248932 -0.48811525 0.06938252]\n [-0.50589657 0.08260352 0.6800011 ]\n [-2.0608335 -1.4326502 -1.0788187 ]\n [ 0.08415911 -0.67595214 -1.4208055 ]]",
25
+ "desired_goal": "[[-0.2540757 -0.67114425 -1.4554731 ]\n [-1.0265082 0.85943544 1.2258997 ]\n [-1.44641 -1.5638996 -0.7453344 ]\n [ 0.71316147 -0.6702961 -1.5549533 ]]",
26
+ "observation": "[[-0.12248932 -0.48811525 0.06938252 -1.7645435 -1.9350079 -2.1171045 ]\n [-0.50589657 0.08260352 0.6800011 -0.1686671 -0.04845463 0.51448774]\n [-2.0608335 -1.4326502 -1.0788187 -1.9790804 -1.1595335 -0.5520993 ]\n [ 0.08415911 -0.67595214 -1.4208055 0.54249126 0.1638698 -0.2490084 ]]"
27
+ },
28
+ "_last_episode_starts": {
29
+ ":type:": "<class 'numpy.ndarray'>",
30
+ ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
31
+ },
32
+ "_last_original_obs": {
33
+ ":type:": "<class 'collections.OrderedDict'>",
34
+ ":serialized:": "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",
35
+ "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]]",
36
+ "desired_goal": "[[ 0.03838971 -0.00719318 0.21197449]\n [ 0.06162451 0.06356581 0.23944677]\n [ 0.1301866 0.0657801 0.12885888]\n [ 0.05756394 0.11797851 0.1131525 ]]",
37
+ "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]]"
38
+ },
39
+ "_episode_num": 0,
40
+ "use_sde": false,
41
+ "sde_sample_freq": -1,
42
+ "_current_progress_remaining": -0.007616000000000067,
43
+ "_stats_window_size": 100,
44
+ "ep_info_buffer": {
45
+ ":type:": "<class 'collections.deque'>",
46
+ ":serialized:": "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"
47
+ },
48
+ "ep_success_buffer": {
49
+ ":type:": "<class 'collections.deque'>",
50
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
51
+ },
52
+ "_n_updates": 1230,
53
+ "n_steps": 2048,
54
+ "gamma": 0.99,
55
+ "gae_lambda": 0.95,
56
+ "ent_coef": 0.0,
57
+ "vf_coef": 0.5,
58
+ "max_grad_norm": 0.5,
59
+ "batch_size": 64,
60
+ "n_epochs": 10,
61
+ "clip_range": {
62
+ ":type:": "<class 'function'>",
63
+ ":serialized:": "gAWVpQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMkEM6XFVzZXJzXG9zaGVyXE9uZURyaXZlIC0gQmFyLUlsYW4gVW5pdmVyc2l0eVzXqdeg15Qg15BcRG9jdW1lbnRzXFVWRkFfR29hbF9SZWNvZ25pdGlvblx2ZW52XGxpYlxzaXRlLXBhY2thZ2VzXHN0YWJsZV9iYXNlbGluZXMzXGNvbW1vblx1dGlscy5weZSMBGZ1bmOUS4RDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5RoDHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgefZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
64
+ },
65
+ "clip_range_vf": null,
66
+ "normalize_advantage": true,
67
+ "target_kl": null,
68
+ "observation_space": {
69
+ ":type:": "<class 'gymnasium.spaces.dict.Dict'>",
70
+ ":serialized:": "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",
71
+ "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, (6,), float32))])",
72
+ "_shape": null,
73
+ "dtype": null,
74
+ "_np_random": null
75
+ },
76
+ "action_space": {
77
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
78
+ ":serialized:": "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",
79
+ "dtype": "float32",
80
+ "bounded_below": "[ True True True True True True True]",
81
+ "bounded_above": "[ True True True True True True True]",
82
+ "_shape": [
83
+ 7
84
+ ],
85
+ "low": "[-1. -1. -1. -1. -1. -1. -1.]",
86
+ "high": "[1. 1. 1. 1. 1. 1. 1.]",
87
+ "low_repr": "-1.0",
88
+ "high_repr": "1.0",
89
+ "_np_random": null
90
+ },
91
+ "n_envs": 4,
92
+ "lr_schedule": {
93
+ ":type:": "<class 'function'>",
94
+ ":serialized:": "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"
95
+ }
96
+ }
ppo-PandaReachJointsSparse-v3-1000000/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f46028665991482979f879d00ca2b0b8d7b858081e30e900af07c40eaf204599
3
+ size 93872
ppo-PandaReachJointsSparse-v3-1000000/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e5104e0747a2abf3de820b146fc5d7ea99c09a530c266133c36c2e8faa42ffe2
3
+ size 46910
ppo-PandaReachJointsSparse-v3-1000000/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppo-PandaReachJointsSparse-v3-1000000/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Windows-10-10.0.22631-SP0 10.0.22631
2
+ - Python: 3.8.16
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 1.12.1+cpu
5
+ - GPU Enabled: False
6
+ - Numpy: 1.24.4
7
+ - Cloudpickle: 3.0.0
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.26.2
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -1.6, "std_reward": 0.8, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-18T18:08:54.094439"}
vec_normalize.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:62d74476b3b5ba046e778761f7520bd4cc97b7c50f9ce9ea08b6b6a31670f10e
3
+ size 2587