ppo-LunarLander-v2 / config.json
georgysavva's picture
Train with 100,000 steps
3a654fa verified
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}", "__doc__": "\n Policy class with Q-Value Net and target net for DQN\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 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 DQNPolicy.__init__ at 0x7fae14e80af0>", "_build": "<function DQNPolicy._build at 0x7fae14e80b80>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7fae14e80c10>", "forward": "<function DQNPolicy.forward at 0x7fae14e80ca0>", "_predict": "<function DQNPolicy._predict at 0x7fae14e80d30>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7fae14e80dc0>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7fae14e80e50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fae14e6adc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711291427254821940, "learning_rate": 0.0001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 1896, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_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": 14844, "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:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "buffer_size": 1000000, "batch_size": 32, "learning_starts": 50000, "tau": 1.0, "gamma": 0.99, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__module__": "stable_baselines3.common.buffers", "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device: PyTorch device\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n Cannot be used in combination with handle_timeout_termination.\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ", "__init__": "<function ReplayBuffer.__init__ at 0x7fae14e58f70>", "add": "<function ReplayBuffer.add at 0x7fae14e59000>", "sample": "<function ReplayBuffer.sample at 0x7fae14e59090>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7fae14e59120>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fae14e55e80>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 625, "_n_calls": 62500, "max_grad_norm": 10, "exploration_rate": 0.05, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "exploration_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"}}