lunar-lander2 / config.json
gputrain's picture
Initial model upload
bf6e4bb
{"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 0x0000023C9DEF34C0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x0000023C9DEF3550>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x0000023C9DEF35E0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x0000023C9DEF3670>", "_build": "<function ActorCriticPolicy._build at 0x0000023C9DEF3700>", "forward": "<function ActorCriticPolicy.forward at 0x0000023C9DEF3790>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x0000023C9DEF3820>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x0000023C9DEF38B0>", "_predict": "<function ActorCriticPolicy._predict at 0x0000023C9DEF3940>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x0000023C9DEF39D0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x0000023C9DEF3A60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x0000023C9DEF3AF0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x0000023C9DEF4280>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 5109760, "_total_timesteps": 5109520, "_num_timesteps_at_start": 5099520, "seed": null, "action_noise": null, "start_time": 1693257139808078600, "learning_rate": 0.0003, "tensorboard_log": "logs", "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAICznj1TPyk/oDoiPss9a78kgsA9SKR5PQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -4.697114406049252e-05, "_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": 24950, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVYAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAADAvwAAwL8AAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAwD8AAMA/AACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFNbLTEuNSAgICAgICAtMS41ICAgICAgIC01LiAgICAgICAgLTUuICAgICAgICAtMy4xNDE1OTI3IC01LgogLTAuICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMS1sxLjUgICAgICAgMS41ICAgICAgIDUuICAgICAgICA1LiAgICAgICAgMy4xNDE1OTI3IDUuICAgICAgICAxLgogMS4gICAgICAgXZSMCl9ucF9yYW5kb22UTnViLg==", "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": "[-1.5 -1.5 -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[1.5 1.5 5. 5. 3.1415927 5. 1.\n 1. ]", "low_repr": "[-1.5 -1.5 -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[1.5 1.5 5. 5. 3.1415927 5. 1.\n 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV9wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Windows-10-10.0.19045-SP0 10.0.19045", "Python": "3.9.17", "Stable-Baselines3": "2.1.0a1", "PyTorch": "1.13.1", "GPU Enabled": "True", "Numpy": "1.24.3", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.0", "OpenAI Gym": "0.26.2"}}