| { | |
| "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 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 0x7f6ce0f6ae50>", | |
| "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6ce0f6aee0>", | |
| "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6ce0f6af70>", | |
| "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6ce0f6e040>", | |
| "_build": "<function ActorCriticPolicy._build at 0x7f6ce0f6e0d0>", | |
| "forward": "<function ActorCriticPolicy.forward at 0x7f6ce0f6e160>", | |
| "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6ce0f6e1f0>", | |
| "_predict": "<function ActorCriticPolicy._predict at 0x7f6ce0f6e280>", | |
| "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6ce0f6e310>", | |
| "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6ce0f6e3a0>", | |
| "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6ce0f6e430>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc_data object at 0x7f6ce0f6b1b0>" | |
| }, | |
| "verbose": 1, | |
| "policy_kwargs": { | |
| ":type:": "<class 'dict'>", | |
| ":serialized:": "gAWVbQAAAAAAAAB9lCiMDWFjdGl2YXRpb25fZm6UjBt0b3JjaC5ubi5tb2R1bGVzLmFjdGl2YXRpb26UjARUYW5olJOUjAhuZXRfYXJjaJRdlChLgEtAfZQojAJwaZRdlChLQEsgZYwCdmaUXZQoS0BLIGV1ZXUu", | |
| "activation_fn": "<class 'torch.nn.modules.activation.Tanh'>", | |
| "net_arch": [ | |
| 128, | |
| 64, | |
| { | |
| "pi": [ | |
| 64, | |
| 32 | |
| ], | |
| "vf": [ | |
| 64, | |
| 32 | |
| ] | |
| } | |
| ] | |
| }, | |
| "observation_space": { | |
| ":type:": "<class 'gym.spaces.box.Box'>", | |
| ":serialized:": "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", | |
| "dtype": "float32", | |
| "_shape": [ | |
| 8 | |
| ], | |
| "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", | |
| "high": "[inf inf inf inf inf inf inf inf]", | |
| "bounded_below": "[False False False False False False False False]", | |
| "bounded_above": "[False False False False False False False False]", | |
| "_np_random": null | |
| }, | |
| "action_space": { | |
| ":type:": "<class 'gym.spaces.discrete.Discrete'>", | |
| ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", | |
| "n": 4, | |
| "_shape": [], | |
| "dtype": "int64", | |
| "_np_random": null | |
| }, | |
| "n_envs": 128, | |
| "num_timesteps": 20054016, | |
| "_total_timesteps": 20000000, | |
| "_num_timesteps_at_start": 0, | |
| "seed": null, | |
| "action_noise": null, | |
| "start_time": 1651728713.0254502, | |
| "learning_rate": 0.0003, | |
| "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:": "gAWV8wAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYkuAhZSMAUOUdJRSlC4=" | |
| }, | |
| "_last_original_obs": null, | |
| "_episode_num": 0, | |
| "use_sde": false, | |
| "sde_sample_freq": -1, | |
| "_current_progress_remaining": -0.0027007999999999477, | |
| "ep_info_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "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" | |
| }, | |
| "ep_success_buffer": { | |
| ":type:": "<class 'collections.deque'>", | |
| ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" | |
| }, | |
| "_n_updates": 612, | |
| "n_steps": 1024, | |
| "gamma": 0.999, | |
| "gae_lambda": 0.98, | |
| "ent_coef": 0.01, | |
| "vf_coef": 0.5, | |
| "max_grad_norm": 0.5, | |
| "batch_size": 1024, | |
| "n_epochs": 4, | |
| "clip_range": { | |
| ":type:": "<class 'function'>", | |
| ":serialized:": "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" | |
| }, | |
| "clip_range_vf": null, | |
| "normalize_advantage": true, | |
| "target_kl": null | |
| } |