ppo-LunarLander-v2 / config.json
MagmaCode's picture
Upload PPO LunarLander-v2 trained agent
809c9bd verified
{"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 0x7babe7cee440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7babe7cee4d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7babe7cee560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7babe7cee5f0>", "_build": "<function ActorCriticPolicy._build at 0x7babe7cee680>", "forward": "<function ActorCriticPolicy.forward at 0x7babe7cee710>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7babe7cee7a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7babe7cee830>", "_predict": "<function ActorCriticPolicy._predict at 0x7babe7cee8c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7babe7cee950>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7babe7cee9e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7babe7ceea70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7babe7ce57c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710720128134654217, "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"}}