lysukhin's picture
Baseline of PPO @ 512k iterations
10b1b7d
{
"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 0x7f2be1393cb0>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2be1393d40>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2be1393dd0>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2be1393e60>",
"_build": "<function ActorCriticPolicy._build at 0x7f2be1393ef0>",
"forward": "<function ActorCriticPolicy.forward at 0x7f2be1393f80>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2be139a050>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f2be139a0e0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2be139a170>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2be139a200>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2be139a290>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f2be13d3ed0>"
},
"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": 524288,
"_total_timesteps": 512000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1652171755.8090763,
"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": -0.02400000000000002,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 140,
"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
}