File size: 14,318 Bytes
b1c17f8 |
1 |
{"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 0x7c3e6c22e9e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c3e6c22ea70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c3e6c22eb00>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c3e6c22eb90>", "_build": "<function ActorCriticPolicy._build at 0x7c3e6c22ec20>", "forward": "<function ActorCriticPolicy.forward at 0x7c3e6c22ecb0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c3e6c22ed40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c3e6c22edd0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c3e6c22ee60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c3e6c22eef0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c3e6c22ef80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c3e6c22f010>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c3e6c2211c0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1690628009571217649, "learning_rate": 0.00096, "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:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 0, "use_sde": true, "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": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [28], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -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 inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.6", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}} |