ajankelo's picture
added deeprl class
beb5706
{
"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 0x7f7f123fb0d0>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7f123fb160>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7f123fb1f0>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7f123fb280>",
"_build": "<function ActorCriticPolicy._build at 0x7f7f123fb310>",
"forward": "<function ActorCriticPolicy.forward at 0x7f7f123fb3a0>",
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7f123fb430>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7f123fb4c0>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f7f123fb550>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7f123fb5e0>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7f123fb670>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7f123fb700>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7f7f123faa40>"
},
"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": 1678853893758815214,
"learning_rate": 0.0003,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"_last_obs": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAACDKT2BRLi8nsQfvXdqEL6h4iI9qlVUPgAAgD8AAIA/s1gSPcO5Y7rP15K31amHslbN4DpKr6w2AACAPwAAgD8ahwy+4RqOui7T9TsPN1M54NKXPOTrNboAAIA/AACAPzOPVzwpqG66Rp0WOKLMFDPBc047XqQwtwAAgD8AAIA/ZoZqO8NJdrpgJfG6phz2tQaKQrsXJw06AACAPwAAgD8AMGw7gt2zPw7qND5jiw++R+wYu3jviLsAAAAAAAAAABo3Tz17koC6wqZ5u6SMeDgg5pU6jikKOgAAgD8AAIA/M8CavCkoKLo7Sbe7wWc/OPqlkbsxa5M3AACAPwAAgD8aPXI9w4lvuu7GejlNnGs0ejSkOnL7krgAAIA/AACAPzN6hL1cQxG6shKNtrFQnLEypY24B7OpNQAAgD8AAIA/APxdPI8GPbqrRB61dppJsE1srToYVWc0AACAPwAAgD/NS2Q9Kch+ulsairoT9xm2lA9QO89RnTkAAIA/AACAP3Pxkj2uwZ26JjoWOHdwDjMmoFw6+DMttwAAgD8AAIA/QLKTPUiHirr2Zg27lVcROM1FWrolaps3AACAPwAAgD9N5Sm9KcA7ujQcLTzPqFq02EpEuz3NgrMAAIA/AACAP83pDT0UzJW6ir9eu5e6Wzj+r+W5C5b3OQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
},
"_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": 248,
"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
}