Upload PPO LunarLander-v2 trained agent
Browse files- README.md +36 -0
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +94 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +7 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
ADDED
@@ -0,0 +1,36 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 |
+
- metrics:
|
12 |
+
- type: mean_reward
|
13 |
+
value: 255.27 +/- 21.23
|
14 |
+
name: mean_reward
|
15 |
+
task:
|
16 |
+
type: reinforcement-learning
|
17 |
+
name: reinforcement-learning
|
18 |
+
dataset:
|
19 |
+
name: LunarLander-v2
|
20 |
+
type: LunarLander-v2
|
21 |
+
---
|
22 |
+
|
23 |
+
# **PPO** Agent playing **LunarLander-v2**
|
24 |
+
This is a trained model of a **PPO** agent playing **LunarLander-v2**
|
25 |
+
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
26 |
+
|
27 |
+
## Usage (with Stable-baselines3)
|
28 |
+
TODO: Add your code
|
29 |
+
|
30 |
+
|
31 |
+
```python
|
32 |
+
from stable_baselines3 import ...
|
33 |
+
from huggingface_sb3 import load_from_hub
|
34 |
+
|
35 |
+
...
|
36 |
+
```
|
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 0x7fcc1a6677a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcc1a667830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcc1a6678c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcc1a667950>", "_build": "<function ActorCriticPolicy._build at 0x7fcc1a6679e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fcc1a667a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcc1a667b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcc1a667b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcc1a667c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcc1a667cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcc1a667d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcc1a6b4690>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1664984711607510335, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJq0rjyujba6Mn+EtlLpgrFoY9w5zWCaNQAAgD8AAIA/ACSxPawMoz5UCRG+G8htvuVzjToo4s69AAAAAAAAAADGbIQ+ddtLP7lEsb6P1Ie+oIOoPUf4R74AAAAAAAAAAFPgKb5yBuI+yzh8PYEqib5VGhW9Jt2MvAAAAAAAAAAADcc9vjq1JD6RCoM+wjlBvlhu5Du6BVs9AAAAAAAAAABmVks8+ewSPjNaEzz+D1q+g3y8vQLJcDwAAAAAAAAAAJqnLjxX0Es+RS7KPTYIK74nFdo8dhkdPQAAAAAAAAAAMztwu64nkz3x/sM9AZ01vk+xhz1gJHk7AAAAAAAAAABmgWq9RaKtPNWnFT622UW+0J0aPYsgcz0AAAAAAAAAADPCmr5XDwI/X9EmPv4To75DKhq+EY8IPgAAAAAAAAAAjbmYvWI3nj+Y4cO+pBIIvxIexL35c0C+AAAAAAAAAACzS4q9SB2+PrHQAD22tJG+LngVPHMRWjwAAAAAAAAAADOvgjuhjIc94as/vqnTWr5+JYy9mv9sPQAAAAAAAAAADTXJvXq+mj7W+7c95e9Rvh7tET0DgA29AAAAAAAAAADN8/C9QQwGPh4jNz60yGe+pa9GvbFFpjoAAAAAAAAAADPtZDzO/5a8sngSvVNoMr2i6wG+arANvgAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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:": "gAWVdBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI1GUxsXmvcECUhpRSlIwBbJRNggGMAXSUR0CSfbCpFTegdX2UKGgGaAloD0MIfA4sR0gJcECUhpRSlGgVTR8BaBZHQJJ+bCO3lS11fZQoaAZoCWgPQwifILHdvQxtQJSGlFKUaBVNJAFoFkdAkn6b4zrNW3V9lChoBmgJaA9DCP8G7dXHeFBAlIaUUpRoFUvuaBZHQJKAp3HJcPh1fZQoaAZoCWgPQwgTgH9KVVZxQJSGlFKUaBVNLwFoFkdAkoDBsMy8BnV9lChoBmgJaA9DCJ3VAntM6ktAlIaUUpRoFUvZaBZHQJKBFglWwNd1fZQoaAZoCWgPQwiID+z4rzBvQJSGlFKUaBVNHAFoFkdAkoFpLEk0JnV9lChoBmgJaA9DCJzDtdrDlnFAlIaUUpRoFU0HAWgWR0CSgZHB1s+FdX2UKGgGaAloD0MIk3GMZI9PcUCUhpRSlGgVTR4BaBZHQJKCGDtgKF91fZQoaAZoCWgPQwhjCWtjLE1yQJSGlFKUaBVNEAFoFkdAkoIumR/3FnV9lChoBmgJaA9DCO5gxD6BN3BAlIaUUpRoFU0dAWgWR0CSgz8pkPMCdX2UKGgGaAloD0MI/fhLi7rlcUCUhpRSlGgVTQoBaBZHQJKETCXQdCF1fZQoaAZoCWgPQwiMZI9QM6wiwJSGlFKUaBVL4GgWR0CShfYNy5qedX2UKGgGaAloD0MIQ8pPqv05cECUhpRSlGgVTS4BaBZHQJKGgTCcf/51fZQoaAZoCWgPQwi/mC1ZFZlxQJSGlFKUaBVNEAFoFkdAkobeEh7mdXV9lChoBmgJaA9DCCuIga59qHBAlIaUUpRoFU1PAWgWR0CShxFNtZV5dX2UKGgGaAloD0MIEVK3s6/xcECUhpRSlGgVTTcBaBZHQJKHheIEbHZ1fZQoaAZoCWgPQwiBP/z8dwxiQJSGlFKUaBVN6ANoFkdAkoep5E+gUXV9lChoBmgJaA9DCCntDb6wZW9AlIaUUpRoFU0HAWgWR0CSikAKfFrEdX2UKGgGaAloD0MI2xX6YBkb1D+UhpRSlGgVTQ0BaBZHQJKKS8dxQzl1fZQoaAZoCWgPQwgzxRwEXa5xQJSGlFKUaBVNIwFoFkdAkopoLw4KhXV9lChoBmgJaA9DCFd3LLaJM3NAlIaUUpRoFU1zAWgWR0CSiww0fozOdX2UKGgGaAloD0MInznrUw66ckCUhpRSlGgVTTMBaBZHQJKLQz67/XJ1fZQoaAZoCWgPQwgd5PVgEsBxQJSGlFKUaBVNHwFoFkdAkouy4J/oaHV9lChoBmgJaA9DCPxSP29qJXFAlIaUUpRoFUv1aBZHQJKMkYP5HmR1fZQoaAZoCWgPQwhDVOHP8D5TQJSGlFKUaBVLyWgWR0CSjKB0p3HJdX2UKGgGaAloD0MICU59ILm0cECUhpRSlGgVTUkBaBZHQJKNBdcB2fV1fZQoaAZoCWgPQwgShgFLbqdyQJSGlFKUaBVNSAFoFkdAko5Ese4kNXV9lChoBmgJaA9DCOYeEr53P25AlIaUUpRoFU0HAWgWR0CSj05B1LamdX2UKGgGaAloD0MIQ6ooXiU6cUCUhpRSlGgVTRQBaBZHQJKQM6hg3Lp1fZQoaAZoCWgPQwg0vcRY5vpwQJSGlFKUaBVNFgFoFkdAkpB+Z5Rj0HV9lChoBmgJaA9DCAzNdRppRHBAlIaUUpRoFU0SAWgWR0CSkRY6XBxhdX2UKGgGaAloD0MISDFAogl8akCUhpRSlGgVTQQCaBZHQJKSMHiWE9N1fZQoaAZoCWgPQwibOo+Kf8xvQJSGlFKUaBVNOAFoFkdAkpJEtRNypHV9lChoBmgJaA9DCOXwSSeS9W5AlIaUUpRoFU0pAWgWR0CSlLW8h9srdX2UKGgGaAloD0MIxyqlZ7q8ckCUhpRSlGgVTR0BaBZHQJKVI55qubJ1fZQoaAZoCWgPQwgGZRpNbs9xQJSGlFKUaBVNRAFoFkdAkpXYk/r0KHV9lChoBmgJaA9DCJCF6BD4dnBAlIaUUpRoFU1AAWgWR0CSldmoR7JGdX2UKGgGaAloD0MIzAuwj85QcECUhpRSlGgVTTMBaBZHQJKWSyon8bd1fZQoaAZoCWgPQwiyutVzktRwQJSGlFKUaBVNVwFoFkdAkpglVtGd7XV9lChoBmgJaA9DCC2Y+KPo43BAlIaUUpRoFU0yAWgWR0CSmD7yQPqcdX2UKGgGaAloD0MIP28qUuE9bkCUhpRSlGgVTUABaBZHQJKYVbNbC791fZQoaAZoCWgPQwjFU480eOFyQJSGlFKUaBVNSgFoFkdAkpiXw9aEBnV9lChoBmgJaA9DCL5PVaEBHm9AlIaUUpRoFU0dAWgWR0CSmMIqbz9TdX2UKGgGaAloD0MIjpJX51i2cUCUhpRSlGgVTRMBaBZHQJKZR1p0wJx1fZQoaAZoCWgPQwiWQiCX+MdxQJSGlFKUaBVNAAFoFkdAkpme8f3evnV9lChoBmgJaA9DCKrv/KIE1U1AlIaUUpRoFUvfaBZHQJKupk1/DtR1fZQoaAZoCWgPQwjJ42n5QRlxQJSGlFKUaBVNOQFoFkdAkq+Lcwg1WXV9lChoBmgJaA9DCDqTNlU3LnJAlIaUUpRoFU0tAWgWR0CSsNzRQaaTdX2UKGgGaAloD0MIsW68O3IXc0CUhpRSlGgVTVMBaBZHQJKxA7xNIsl1fZQoaAZoCWgPQwhPkNjuXsdxQJSGlFKUaBVNBQFoFkdAkrK9zwMH8nV9lChoBmgJaA9DCAvtnGbBEHBAlIaUUpRoFU0fAWgWR0CSsr642CNCdX2UKGgGaAloD0MIzCiWW1oScUCUhpRSlGgVTQwBaBZHQJKy+joIOYp1fZQoaAZoCWgPQwg3iqw1lCdvQJSGlFKUaBVNEAFoFkdAkrV/4/NZ/3V9lChoBmgJaA9DCMFVnkCYA3JAlIaUUpRoFU0VAWgWR0CStfs4T9KmdX2UKGgGaAloD0MInIcTmA6bckCUhpRSlGgVTU0BaBZHQJK2DqZ+hGp1fZQoaAZoCWgPQwja4a/JGr5tQJSGlFKUaBVNLQFoFkdAkrbnb7CSBHV9lChoBmgJaA9DCBVVv9L5G3JAlIaUUpRoFU0OAWgWR0CStwS88La3dX2UKGgGaAloD0MId6IkJNK1ckCUhpRSlGgVTTIBaBZHQJK3f+0gKWt1fZQoaAZoCWgPQwgL1GLwsBlxQJSGlFKUaBVNMQFoFkdAkremy1NQCXV9lChoBmgJaA9DCNDU6xZB3XBAlIaUUpRoFU2aAWgWR0CSt+QQL/jsdX2UKGgGaAloD0MI/wbt1UfgbkCUhpRSlGgVTS0BaBZHQJK4aDRMN+d1fZQoaAZoCWgPQwgUXKyoQa5xQJSGlFKUaBVNMwFoFkdAkrkCIgvDg3V9lChoBmgJaA9DCGrC9pOxtnJAlIaUUpRoFU0XAWgWR0CSuS3UhFEzdX2UKGgGaAloD0MIZOYCl4djckCUhpRSlGgVS/NoFkdAkrlnbEgnt3V9lChoBmgJaA9DCLJmZJA7ZHBAlIaUUpRoFUv/aBZHQJK52NEPUa11fZQoaAZoCWgPQwiPiv87IlhzQJSGlFKUaBVL6WgWR0CSuotUn5SFdX2UKGgGaAloD0MIUb6ghYSXb0CUhpRSlGgVTR0BaBZHQJK8Y6ij+Jh1fZQoaAZoCWgPQwjo3O16qQNxQJSGlFKUaBVNXQFoFkdAkr5wcT8HfXV9lChoBmgJaA9DCEWBPpFnh3JAlIaUUpRoFU0eAWgWR0CSvthZyMkydX2UKGgGaAloD0MIZcbbSi/9bkCUhpRSlGgVTRIBaBZHQJK+0fZElVt1fZQoaAZoCWgPQwj2JLA5RxJxQJSGlFKUaBVNFQFoFkdAksBJnxri2nV9lChoBmgJaA9DCM2VQbXBKG9AlIaUUpRoFU0iAWgWR0CSwPdGiHqNdX2UKGgGaAloD0MIQYNNnQdxckCUhpRSlGgVTTwBaBZHQJLBL4M4LkV1fZQoaAZoCWgPQwg/kLxz6ERwQJSGlFKUaBVNRAFoFkdAksGfh/Aj6nV9lChoBmgJaA9DCF9hwf0Azm5AlIaUUpRoFU0uAWgWR0CSwb0WuX/pdX2UKGgGaAloD0MIUKc8uhEacECUhpRSlGgVTSgBaBZHQJLCKBlMAWB1fZQoaAZoCWgPQwjnw7MEWU5yQJSGlFKUaBVNdAFoFkdAksJnhn8KonV9lChoBmgJaA9DCI/DYP7K43BAlIaUUpRoFU0cAWgWR0CSwpzaK1ohdX2UKGgGaAloD0MIGyycpDkKcUCUhpRSlGgVTSUBaBZHQJLCrBbfP5Z1fZQoaAZoCWgPQwgNGCR92iJyQJSGlFKUaBVNGgFoFkdAksLJaFEiMnV9lChoBmgJaA9DCCL7IMuCL29AlIaUUpRoFU0kAWgWR0CSw2xxkupTdX2UKGgGaAloD0MIhSaJJeVJb0CUhpRSlGgVTSIBaBZHQJLEFri2lVN1fZQoaAZoCWgPQwhSgZNt4ONuQJSGlFKUaBVNGgFoFkdAksVhLCemN3V9lChoBmgJaA9DCED8/Pdgj3JAlIaUUpRoFU0ZAWgWR0CSx6cMEzO5dX2UKGgGaAloD0MIFoielInxckCUhpRSlGgVTS0BaBZHQJLIcaya/h51fZQoaAZoCWgPQwgE5Euo4GVsQJSGlFKUaBVL/2gWR0CSyN4uscQzdX2UKGgGaAloD0MI+z+H+bLucECUhpRSlGgVS+9oFkdAkskF01ZTynV9lChoBmgJaA9DCCCcTx1rOHFAlIaUUpRoFUv9aBZHQJLJB2Qnx8V1fZQoaAZoCWgPQwi+h0uOu9VxQJSGlFKUaBVL+GgWR0CSyT2UjcEedX2UKGgGaAloD0MI8KKvIE22cUCUhpRSlGgVTU0BaBZHQJLJTcN6PbR1fZQoaAZoCWgPQwiZnNoZ5kRyQJSGlFKUaBVNDQFoFkdAkspnpjc2znV9lChoBmgJaA9DCG3n+6lxqHBAlIaUUpRoFU0CAWgWR0CSyp4ZMtbtdX2UKGgGaAloD0MIPZ0rSgnacECUhpRSlGgVTQcBaBZHQJLK+DL8rI51fZQoaAZoCWgPQwg7qpogapNtQJSGlFKUaBVNFAFoFkdAkssl0o0ALnV9lChoBmgJaA9DCMhgxakWXnJAlIaUUpRoFU1VAWgWR0CSyyoESuhcdX2UKGgGaAloD0MIcRx4tdy4bkCUhpRSlGgVTSYBaBZHQJLLcNEw35x1fZQoaAZoCWgPQwgK8x5nmglwQJSGlFKUaBVNEgFoFkdAksv7PMSsbXV9lChoBmgJaA9DCBpTsMZZPXNAlIaUUpRoFU0GAWgWR0CSzFnhbW3CdX2UKGgGaAloD0MItMh2vl+ackCUhpRSlGgVTRsBaBZHQJLOO86FM7F1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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": 4, "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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.14", "Stable-Baselines3": "1.6.1", "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:f7263a0fdbfb884811fbdb49af0d2f3af67e2f957f962366a58d4b9a365d9766
|
3 |
+
size 147138
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.1
|
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 0x7fcc1a6677a0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcc1a667830>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcc1a6678c0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcc1a667950>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fcc1a6679e0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fcc1a667a70>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcc1a667b00>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fcc1a667b90>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcc1a667c20>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcc1a667cb0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcc1a667d40>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7fcc1a6b4690>"
|
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": 507904,
|
46 |
+
"_total_timesteps": 500000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1664984711607510335,
|
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": 248,
|
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": 4,
|
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 sha256:8a796c792d3b739be1896497607eb681d9ae810399a242727457e8e8cae22179
|
3 |
+
size 87865
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:baea549cf5d7339ee08b9d78359c94cc45b26872a13d29f5d17703a647622398
|
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-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
|
2 |
+
Python: 3.7.14
|
3 |
+
Stable-Baselines3: 1.6.1
|
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 (235 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 255.26881665000474, "std_reward": 21.229738310863848, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-05T15:59:28.463578"}
|