amrahmed's picture
Upload PPO LunarLander-v2 trained agent
9ef6c6a
raw
history blame contribute delete
No virus
14.4 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 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 0x7fca2cf307a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fca2cf30830>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fca2cf308c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fca2cf30950>", "_build": "<function ActorCriticPolicy._build at 0x7fca2cf309e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fca2cf30a70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fca2cf30b00>", "_predict": "<function ActorCriticPolicy._predict at 0x7fca2cf30b90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fca2cf30c20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fca2cf30cb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fca2cf30d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fca2cf6bde0>"}, "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": 1652878146.8931386, "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:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}