ThePieroCV's picture
Added first model
c41600a
{
"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 0x7efd11149830>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efd111498c0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efd11149950>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efd111499e0>",
"_build": "<function ActorCriticPolicy._build at 0x7efd11149a70>",
"forward": "<function ActorCriticPolicy.forward at 0x7efd11149b00>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efd11149b90>",
"_predict": "<function ActorCriticPolicy._predict at 0x7efd11149c20>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efd11149cb0>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efd11149d40>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7efd11149dd0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7efd11198840>"
},
"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": 1015808,
"_total_timesteps": 1000000.0,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1651895801.7417972,
"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": -0.015808000000000044,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 372,
"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
}