a2c-AntBulletEnv-v0 / config.json
michael20at's picture
Initial commit
553fdd6
{"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 0x7f965cb5ee60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f965cb5eef0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f965cb5ef80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f965cb61050>", "_build": "<function ActorCriticPolicy._build at 0x7f965cb610e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f965cb61170>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f965cb61200>", "_predict": "<function ActorCriticPolicy._predict at 0x7f965cb61290>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f965cb61320>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f965cb613b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f965cb61440>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f965cbb1660>"}, "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:": "gASVwwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBVudW1weS5jb3JlLm11bHRpYXJyYXmUjAxfcmVjb25zdHJ1Y3SUk5RoBowHbmRhcnJheZSTlEsAhZRDAWKUh5RSlChLAUsIhZRoColDIAAAgL8AAIC/AACAvwAAgL8AAIC/AACAvwAAgL8AAIC/lHSUYowEaGlnaJRoEmgUSwCFlGgWh5RSlChLAUsIhZRoColDIAAAgD8AAIA/AACAPwAAgD8AAIA/AACAPwAAgD8AAIA/lHSUYowNYm91bmRlZF9iZWxvd5RoEmgUSwCFlGgWh5RSlChLAUsIhZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDCAEBAQEBAQEBlHSUYowNYm91bmRlZF9hYm92ZZRoEmgUSwCFlGgWh5RSlChLAUsIhZRoKolDCAEBAQEBAQEBlHSUYowKX25wX3JhbmRvbZROdWIu", "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": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1665756080346459632, "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": 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, "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": "3.7.14", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}