{"policy_class": {":type:": "", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__annotations__": "{'q_net': , 'q_net_target': }", "__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__": "", "_build": "", "make_q_net": "", "forward": "", "_predict": "", "_get_constructor_parameters": "", "set_training_mode": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f50c89e8d00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100000, "_total_timesteps": 100000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713257541082973744, "learning_rate": 0.0001, "tensorboard_log": null, "_last_obs": {":type:": "", ":serialized:": "gAWV1QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZgAAAAAAAAAAAAAAAAAPA/AAAAAAAAAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAAAAAAAAAADwPwAAAAAAAMa/mpmZmZmZuT9VVVVVVVXFP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsMhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "", ":serialized:": "gAWV1QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZgAAAAAAAAAAAAAAAAAPA/AAAAAAAAAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAAAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAAAAAAAAAADwPwAAAAAAQMa/AAAAAAAAAACamZmZmZnJP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsMhpSMAUOUdJRSlC4="}, "_episode_num": 1025, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "", ":serialized:": "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"}, "ep_success_buffer": {":type:": "", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 12500, "observation_space": {":type:": "", ":serialized:": "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", "dtype": "float64", "bounded_below": "[False False False False False False False False False False False False]", "bounded_above": "[False False False False False False False False False False False False]", "_shape": [12], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf]", "low_repr": "-inf", "high_repr": "inf", "_np_random": null}, "action_space": {":type:": "", ":serialized:": "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", "n": "2", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "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:": "", ":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__": "", "add": "", "sample": "", "_get_samples": "", "_maybe_cast_dtype": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f50c89c75c0>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 10000, "_n_calls": 100000, "max_grad_norm": 10, "exploration_rate": 0.05, "lr_schedule": {":type:": "", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "exploration_schedule": {":type:": "", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.146.1-microsoft-standard-WSL2-x86_64-with-glibc2.35 # 1 SMP Thu Jan 11 04:09:03 UTC 2024", "Python": "3.9.18", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.0+cpu", "GPU Enabled": "False", "Numpy": "1.26.1", "Cloudpickle": "3.0.0", "Gymnasium": "0.29.1", "OpenAI Gym": "0.26.2"}}