jfjensen commited on
Commit
3275727
1 Parent(s): 472259d

Upload PPO LunarLander-v2 trained agent

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
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: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 269.30 +/- 22.56
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
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:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n 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\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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\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 ActorCriticPolicy.__init__ at 0x7f0d3a514160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0d3a5141f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0d3a514280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0d3a514310>", "_build": "<function ActorCriticPolicy._build at 0x7f0d3a5143a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f0d3a514430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0d3a5144c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0d3a514550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0d3a5145e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0d3a514670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0d3a514700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f0d3a50f630>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670363609473214309, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVWxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIe5+qQoM6c0CUhpRSlIwBbJRNEgGMAXSUR0CSp4wQlKK6dX2UKGgGaAloD0MIuK6YEd7ibUCUhpRSlGgVS/loFkdAkqemlANXo3V9lChoBmgJaA9DCKzGEtbGmHBAlIaUUpRoFU0XAWgWR0CSp/xWDHwPdX2UKGgGaAloD0MI0Xe3ssSDbkCUhpRSlGgVTTYBaBZHQJKoUppeu3d1fZQoaAZoCWgPQwjZJhWNtY5xQJSGlFKUaBVNBgFoFkdAkqilfZ26kXV9lChoBmgJaA9DCONw5lfztnFAlIaUUpRoFU0TAWgWR0CSqi6HTI/8dX2UKGgGaAloD0MI4/xNKASLcUCUhpRSlGgVTSIBaBZHQJKqoO9WZJF1fZQoaAZoCWgPQwiLql/pPLBwQJSGlFKUaBVL5mgWR0CSqwD28IzFdX2UKGgGaAloD0MIvOZVnZXmckCUhpRSlGgVS+9oFkdAkqsrXL/0d3V9lChoBmgJaA9DCMR6o1YYH3FAlIaUUpRoFU0NAWgWR0CSq/Ai3XqadX2UKGgGaAloD0MI5bM8D26xcECUhpRSlGgVS+ZoFkdAkqvw5/9YOnV9lChoBmgJaA9DCDRJLCl3eG9AlIaUUpRoFUv2aBZHQJKsViQT2391fZQoaAZoCWgPQwjSqpZ0VIhyQJSGlFKUaBVNXgFoFkdAkqxW43FUAHV9lChoBmgJaA9DCE5+i07Wa3FAlIaUUpRoFUv7aBZHQJKtgZ0jkdV1fZQoaAZoCWgPQwg+esN95H1zQJSGlFKUaBVNAQFoFkdAkq2zfm9xqHV9lChoBmgJaA9DCAN3oE75gnJAlIaUUpRoFU0LAWgWR0CSroCNjslcdX2UKGgGaAloD0MIbFopBHIhckCUhpRSlGgVTQEBaBZHQJKue4EwFkh1fZQoaAZoCWgPQwihTKPJhUpzQJSGlFKUaBVNBwFoFkdAkq8R5HEuQXV9lChoBmgJaA9DCNzWFp4XNW5AlIaUUpRoFU0lAWgWR0CSr434bjtHdX2UKGgGaAloD0MIDCB8KBG8ckCUhpRSlGgVTQMBaBZHQJKvr+zdDY11fZQoaAZoCWgPQwjUf9b8uJRyQJSGlFKUaBVNGwFoFkdAkq/wtz0Yj3V9lChoBmgJaA9DCAPRkzKpH3JAlIaUUpRoFUv9aBZHQJKyBLamGdt1fZQoaAZoCWgPQwgukQvOIPNxQJSGlFKUaBVNFwFoFkdAkrKxsqJ/G3V9lChoBmgJaA9DCIiAQ6gSvnNAlIaUUpRoFU08AWgWR0CSsxNZeRgadX2UKGgGaAloD0MI+RBUjZ4FcECUhpRSlGgVS/poFkdAkrNasU7CBXV9lChoBmgJaA9DCGQ8SiU8MG1AlIaUUpRoFU0SAWgWR0CSs6Y9xIatdX2UKGgGaAloD0MIBvcDHpiWcECUhpRSlGgVTRYBaBZHQJKzxYp2ECh1fZQoaAZoCWgPQwiCOuXRjcBzQJSGlFKUaBVNOgFoFkdAkrVkWAPNFHV9lChoBmgJaA9DCLeyRGfZRHBAlIaUUpRoFU0EAWgWR0CStWVmjCYUdX2UKGgGaAloD0MITIkkepmzb0CUhpRSlGgVS+ZoFkdAkrVmFBY3enV9lChoBmgJaA9DCAN8t3mjSHNAlIaUUpRoFU0MAWgWR0CStW3oLXtjdX2UKGgGaAloD0MIbsK9Mi8DcUCUhpRSlGgVS/9oFkdAkrYbbYbsGHV9lChoBmgJaA9DCB+hZkjV6HFAlIaUUpRoFUvxaBZHQJK2S3rleWx1fZQoaAZoCWgPQwjggmxZvlZzQJSGlFKUaBVNngFoFkdAkraDv7WNFXV9lChoBmgJaA9DCLX5f9WRI3JAlIaUUpRoFUvxaBZHQJK24bn5i3J1fZQoaAZoCWgPQwgIBhA+lERsQJSGlFKUaBVL+GgWR0CSt0izLOiWdX2UKGgGaAloD0MIfPKwUCtgcECUhpRSlGgVTQwBaBZHQJK3ZuAI6bR1fZQoaAZoCWgPQwgxzXSvU4BxQJSGlFKUaBVL4GgWR0CSuO3gk1MudX2UKGgGaAloD0MIk3Ahj6CfcECUhpRSlGgVTQUBaBZHQJLR86uGKyh1fZQoaAZoCWgPQwjP2JdsPE5yQJSGlFKUaBVL82gWR0CS0gpjc2zfdX2UKGgGaAloD0MIyvrNxLTscUCUhpRSlGgVTQEBaBZHQJLSFAu7HyV1fZQoaAZoCWgPQwiFQgQcAutwQJSGlFKUaBVNQAFoFkdAktLGelKsdXV9lChoBmgJaA9DCCB6Uia1+nFAlIaUUpRoFU0dAWgWR0CS0x7dBSk1dX2UKGgGaAloD0MIDJBoAkVdbkCUhpRSlGgVS/RoFkdAktOXrD63zHV9lChoBmgJaA9DCAfqlEe3KXFAlIaUUpRoFU0BAWgWR0CS0/Sn+AEudX2UKGgGaAloD0MIcceb/BaLb0CUhpRSlGgVTQYBaBZHQJLUGXMQmNR1fZQoaAZoCWgPQwi9UwH3PGtwQJSGlFKUaBVNCwFoFkdAktQ672+PBHV9lChoBmgJaA9DCMlYbf6fwHFAlIaUUpRoFUvzaBZHQJLUdAVwgkl1fZQoaAZoCWgPQwidSgaAapxwQJSGlFKUaBVNDQFoFkdAktTtszl90HV9lChoBmgJaA9DCALWql2TRW9AlIaUUpRoFUv5aBZHQJLVnW/ag291fZQoaAZoCWgPQwh3vMlv0eZxQJSGlFKUaBVNDgFoFkdAktW4GdI5HXV9lChoBmgJaA9DCOwWgbE+JW5AlIaUUpRoFU0pAWgWR0CS1gHXVbzLdX2UKGgGaAloD0MI2ERmLrC7cECUhpRSlGgVTQsBaBZHQJLWKGgzxgB1fZQoaAZoCWgPQwhyhuKONyByQJSGlFKUaBVNGgFoFkdAktghd+ocaXV9lChoBmgJaA9DCHV2MjjKPW5AlIaUUpRoFUvxaBZHQJLYUhvBJqZ1fZQoaAZoCWgPQwjWV1cFaiVUQJSGlFKUaBVLvGgWR0CS2REhaC+UdX2UKGgGaAloD0MIrMq+K8IRcECUhpRSlGgVS+hoFkdAktlHnhbW3HV9lChoBmgJaA9DCCGSIcdWWHFAlIaUUpRoFUv6aBZHQJLZdCpm29d1fZQoaAZoCWgPQwhiZwqdV0RtQJSGlFKUaBVNKQFoFkdAktoMwDeTFHV9lChoBmgJaA9DCHHl7J0RPXJAlIaUUpRoFUvtaBZHQJLaMTi83/B1fZQoaAZoCWgPQwiMutbeZwRwQJSGlFKUaBVNLgFoFkdAkto5swco6XV9lChoBmgJaA9DCH7FGi7ym3JAlIaUUpRoFU0UAWgWR0CS21MX7+DOdX2UKGgGaAloD0MIsacd/pp+ckCUhpRSlGgVTQgBaBZHQJLbYB91EE11fZQoaAZoCWgPQwg50hkY+fBrQJSGlFKUaBVNDQFoFkdAktwU9IPK+3V9lChoBmgJaA9DCO4m+KZp9XBAlIaUUpRoFU1KAWgWR0CS3GOgg5imdX2UKGgGaAloD0MIcF0xIzxrckCUhpRSlGgVTR4BaBZHQJLdXviLl3h1fZQoaAZoCWgPQwiXxi+8EpJvQJSGlFKUaBVNGQFoFkdAkt3Bj4Hoo3V9lChoBmgJaA9DCGgibHh6V0lAlIaUUpRoFUvLaBZHQJLd9K3/gix1fZQoaAZoCWgPQwjAl8KDpsJwQJSGlFKUaBVNXQFoFkdAkt+x3mmtQ3V9lChoBmgJaA9DCAAapUu/DXNAlIaUUpRoFU0VAWgWR0CS4Db70nPWdX2UKGgGaAloD0MIcGHdeHfBcECUhpRSlGgVS/ZoFkdAkuB4MBp5/3V9lChoBmgJaA9DCHe9NEWAnW9AlIaUUpRoFUv+aBZHQJLgg3gk1Mx1fZQoaAZoCWgPQwieQq7UcyhyQJSGlFKUaBVNhgFoFkdAkuCZYDDCQHV9lChoBmgJaA9DCGTo2EElKXNAlIaUUpRoFUv4aBZHQJLgupiqhlF1fZQoaAZoCWgPQwjWbrvQXEJyQJSGlFKUaBVL82gWR0CS4VwSamXPdX2UKGgGaAloD0MI95MxPky9bUCUhpRSlGgVTSUBaBZHQJLik9X9zfd1fZQoaAZoCWgPQwhgH526cnxyQJSGlFKUaBVNBAFoFkdAkuMV8w5/9nV9lChoBmgJaA9DCCWxpNx9RHBAlIaUUpRoFU06AWgWR0CS41Pci4axdX2UKGgGaAloD0MIpgpGJbWBc0CUhpRSlGgVS/RoFkdAkuOaoQ4CIXV9lChoBmgJaA9DCCz0wTK2sGxAlIaUUpRoFU0iAWgWR0CS496YVqN7dX2UKGgGaAloD0MInff/ccKIcUCUhpRSlGgVTRoBaBZHQJLkURIz3yt1fZQoaAZoCWgPQwhws3ixMFNwQJSGlFKUaBVNBQFoFkdAkuUI6Oo5xXV9lChoBmgJaA9DCAMJih8jQXNAlIaUUpRoFU0HAWgWR0CS5XdZ7ojfdX2UKGgGaAloD0MIfLjkuNO3cECUhpRSlGgVTQ0BaBZHQJLl2bpeNT91fZQoaAZoCWgPQwiBIhYxLLxzQJSGlFKUaBVL3GgWR0CS5qIKtxMndX2UKGgGaAloD0MIIVhVLz9tb0CUhpRSlGgVS+xoFkdAkucEnw5NoXV9lChoBmgJaA9DCMxiYvOxhHBAlIaUUpRoFU0AAWgWR0CS52PoFFDwdX2UKGgGaAloD0MI6Nztemlrb0CUhpRSlGgVTRUBaBZHQJLnlfPX05F1fZQoaAZoCWgPQwhh+l5D8J5vQJSGlFKUaBVNAgFoFkdAkufvdyksSXV9lChoBmgJaA9DCK/PnPWp8W1AlIaUUpRoFU0SAWgWR0CS6CeUY8+zdX2UKGgGaAloD0MIMe2b+yuWc0CUhpRSlGgVS/loFkdAkuhAX668QXV9lChoBmgJaA9DCEIG8uzyBG1AlIaUUpRoFUvqaBZHQJLpponKGL11fZQoaAZoCWgPQwgEqRQ72ktwQJSGlFKUaBVNFgFoFkdAkuotkvsZ53V9lChoBmgJaA9DCLqfU5DfCHJAlIaUUpRoFUvZaBZHQJLqQ2vStvJ1fZQoaAZoCWgPQwi9VGzMK4BxQJSGlFKUaBVNEgFoFkdAkuqPIS13MnV9lChoBmgJaA9DCFZ/hGFAP3JAlIaUUpRoFUv5aBZHQJLqo4FRpDh1fZQoaAZoCWgPQwiFXn8SH4FuQJSGlFKUaBVL3mgWR0CS64OPeYUndX2UKGgGaAloD0MIG0mCcIWhbkCUhpRSlGgVS/xoFkdAkuv22CuloHV9lChoBmgJaA9DCFRTknU4uG1AlIaUUpRoFU0/AWgWR0CS7FLzf779dX2UKGgGaAloD0MItMnhk84CckCUhpRSlGgVS/JoFkdAkux8DKYAsHVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 5, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:51f2284356b96a5832819ad6231c6fdbf07e5741958d71702df4a908e21a2c08
3
+ size 147234
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__doc__": "\n 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\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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\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 ActorCriticPolicy.__init__ at 0x7f0d3a514160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0d3a5141f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0d3a514280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0d3a514310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f0d3a5143a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f0d3a514430>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0d3a5144c0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f0d3a514550>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0d3a5145e0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0d3a514670>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0d3a514700>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f0d3a50f630>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 1015808,
46
+ "_total_timesteps": 1000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670363609473214309,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.015808000000000044,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 310,
79
+ "n_steps": 1024,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.98,
82
+ "ent_coef": 0.01,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 5,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d6c098322f6b2803d7f71a7577083098cc47b7ac41b0832863641dd18c881a2d
3
+ size 87993
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d7ad558aea1078eb2b618d10b244e48afc6a92aac7c4b98b1e5ffd275adef081
3
+ size 43201
ppo-LunarLander-v2/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-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.8.15
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.12.1+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (199 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 269.30215545534395, "std_reward": 22.56440943911104, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-06T22:16:34.320015"}