rl_class / config.json
jefsnacker's picture
bigger and better model
882423c
{"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 0x7fc23e150170>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc23e150200>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc23e150290>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc23e150320>", "_build": "<function ActorCriticPolicy._build at 0x7fc23e1503b0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc23e150440>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc23e1504d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc23e150560>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc23e1505f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc23e150680>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc23e150710>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fc23e11cab0>"}, "verbose": 0, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVbAAAAAAAAAB9lCiMDWFjdGl2YXRpb25fZm6UjBt0b3JjaC5ubi5tb2R1bGVzLmFjdGl2YXRpb26UjARSZUxVlJOUjAhuZXRfYXJjaJRdlH2UKIwCcGmUXZQoTQABTQABZYwCdmaUXZQoTQABTQABZXVhdS4=", "activation_fn": "<class 'torch.nn.modules.activation.ReLU'>", "net_arch": [{"pi": [256, 256], "vf": [256, 256]}]}, "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": 32, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651948583.062961, "learning_rate": {":type:": "<class 'function'>", ":serialized:": "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"}, "tensorboard_log": "runs/24cnevl2", "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_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": 310, "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": 2048, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}