File size: 14,484 Bytes
2860864 |
1 |
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7f95a82108c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f95a8210950>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f95a82109e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f95a8210a70>", "_build": "<function ActorCriticPolicy._build at 0x7f95a8210b00>", "forward": "<function ActorCriticPolicy.forward at 0x7f95a8210b90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f95a8210c20>", "_predict": "<function ActorCriticPolicy._predict at 0x7f95a8210cb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f95a8210d40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f95a8210dd0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f95a8210e60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f95a8254cf0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gASVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/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}}, "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, "num_timesteps": 4000000, "_total_timesteps": 4000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1662845809.700044, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "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:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAAAAACUdJRiLg=="}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 125000, "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, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.13", "Stable-Baselines3": "1.6.0", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}} |