{"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 0x000002925CA78AF0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x000002925CA78B80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x000002925CA78C10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x000002925CA78CA0>", "_build": "<function ActorCriticPolicy._build at 0x000002925CA78D30>", "forward": "<function ActorCriticPolicy.forward at 0x000002925CA78DC0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x000002925CA78E50>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x000002925CA78EE0>", "_predict": "<function ActorCriticPolicy._predict at 0x000002925CA78F70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x000002925CA79000>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x000002925CA79090>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x000002925CA79120>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x000002925CA71D40>"}, "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": [4], "low": "[-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38]", "high": "[4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38]", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLAowGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 2, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "num_timesteps": 25000, "_total_timesteps": 25000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676202537295446500, "learning_rate": 0.0007, "tensorboard_log": "runs/mcfwzfhs", "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAP/fnL1hcm+/aH4LPYzjtD+UjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLBIaUjAFDlHSUUpQu"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_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": 5000, "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": "Windows-10-10.0.22621-SP0 10.0.22621", "Python": "3.10.2", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.0+cpu", "GPU Enabled": "False", "Numpy": "1.24.2", "Gym": "0.21.0"}} |