itexbarr's picture
First commit to the Deep RL course
49cd552
{
"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 0x7f2f8f520c10>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2f8f520ca0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2f8f520d30>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2f8f520dc0>",
"_build": "<function ActorCriticPolicy._build at 0x7f2f8f520e50>",
"forward": "<function ActorCriticPolicy.forward at 0x7f2f8f520ee0>",
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7f2f8f520f70>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2f8f523040>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f2f8f5230d0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2f8f523160>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2f8f5231f0>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2f8f523280>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f2f95f11c60>"
},
"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": 1673709622517107148,
"learning_rate": 0.0003,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"_last_obs": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADOfAbxzg/A+PbTLvGawmr6wna07fv5IPQAAAAAAAAAAAHfovZYXkj4ac7k80ByHvla2MLuGJKc8AAAAAAAAAAAa0sk9h5+UP2pndT0+a5W+fw3lPc5OFT0AAAAAAAAAAHNUAb4lTko+AsQxPi2g9b0czio9Kag8PAAAAAAAAAAAM2MPPBgplD57NNG8THBcvjsCy7oFomO9AAAAAAAAAAC9+XK+SK3fPumJPT4dozy+faYLvP1Q9DwAAAAAAAAAAGYOD7xk44A9zU7VuypYpL1YNJi87uAgPQAAAAAAAAAA5geLPUjnn7qQezyzDvoBMGdeNTouYdEzAACAPwAAgD8zD/28caJzu6ERqj1qlYK9VWCKvKJ8V74AAIA/AACAP42pHL4uysU+0uWuPSkpYr6f8ee8MuBnugAAAAAAAAAAZkSBPdU1Zz+s3Ay+b0ezvtzesj0eLcm9AAAAAAAAAAAm7ow9jFMCPjc1Sr5rGpO+jcACvaaYAL0AAAAAAAAAAI2CS74zrm0/0Ptavpv33r7Y60y+Z7C7PQAAAAAAAAAADUmavZuFmz95Z6W9Np/fvhL8Mju+JDi9AAAAAAAAAAAD3VK+9Dj6vGKfcLzBwxK7zEhcPnUJ3DsAAIA/AACAP5Op3b6b+Ww/Z76ZvgGTA7/iQrm+6o/jPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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
}