ppo-LunarLander-v2 / config.json
hugging-robot's picture
Upload PPO LunarLander-v2 trained agent
1fe62c5 verified
raw
history blame contribute delete
No virus
13.8 kB
{"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 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 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 ActorCriticPolicy.__init__ at 0x7adfeca1cb80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7adfeca1cc10>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7adfeca1cca0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7adfeca1cd30>", "_build": "<function ActorCriticPolicy._build at 0x7adfeca1cdc0>", "forward": "<function ActorCriticPolicy.forward at 0x7adfeca1ce50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7adfeca1cee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7adfeca1cf70>", "_predict": "<function ActorCriticPolicy._predict at 0x7adfeca1d000>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7adfeca1d090>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7adfeca1d120>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7adfeca1d1b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7adfeca18a40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1714805250610586282, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_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": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}