{"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 0x7f6db1e44c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6db1e44ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6db1e44d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6db1e44dc0>", "_build": "<function ActorCriticPolicy._build at 0x7f6db1e44e50>", "forward": "<function ActorCriticPolicy.forward at 0x7f6db1e44ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f6db1e44f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6db1e47040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6db1e470d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6db1e47160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6db1e471f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6db1e47280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f6db1e463c0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "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": [22], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -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]", "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]", "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]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [6], "low": "[-1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True True True True True True]", "bounded_above": "[ True True True True True True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 155000, "_total_timesteps": 155000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679533131109156798, "learning_rate": 0.0007, "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": false, "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:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 7750, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}} |