jxiao's picture
ppo 2nd try
36e0662
{
"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 0x7f446745ff70>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4467464040>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f44674640d0>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4467464160>",
"_build": "<function ActorCriticPolicy._build at 0x7f44674641f0>",
"forward": "<function ActorCriticPolicy.forward at 0x7f4467464280>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4467464310>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f44674643a0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4467464430>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f44674644c0>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4467464550>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f446745d750>"
},
"verbose": 1,
"policy_kwargs": {},
"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": 16,
"num_timesteps": 10010624,
"_total_timesteps": 10000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1671318916067617713,
"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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
},
"_last_original_obs": null,
"_episode_num": 0,
"use_sde": false,
"sde_sample_freq": -1,
"_current_progress_remaining": -0.0010623999999999079,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 2444,
"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": 64,
"n_epochs": 4,
"clip_range": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"clip_range_vf": null,
"normalize_advantage": true,
"target_kl": null
}