SamJoshua's picture
1 Million timestep ppo
21f138b
{
"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 0x7f0b888d9820>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0b888d98b0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0b888d9940>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0b888d99d0>",
"_build": "<function ActorCriticPolicy._build at 0x7f0b888d9a60>",
"forward": "<function ActorCriticPolicy.forward at 0x7f0b888d9af0>",
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0b888d9b80>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0b888d9c10>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f0b888d9ca0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0b888d9d30>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0b888d9dc0>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0b888d9e50>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f0b888d59c0>"
},
"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,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1674395785015119778,
"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": 380,
"n_steps": 2048,
"gamma": 0.99,
"gae_lambda": 0.95,
"ent_coef": 0.0,
"vf_coef": 0.5,
"max_grad_norm": 0.5,
"batch_size": 64,
"n_epochs": 10,
"clip_range": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"clip_range_vf": null,
"normalize_advantage": true,
"target_kl": null
}