| {"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 0x7fc3ab187290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc3ab187320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc3ab1873b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc3ab187440>", "_build": "<function ActorCriticPolicy._build at 0x7fc3ab1874d0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc3ab187560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc3ab1875f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc3ab187680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc3ab187710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc3ab1877a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc3ab187830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fc3ab242f60>"}, "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": 32, "num_timesteps": 524288, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651850359.5196545, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.04857599999999995, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVJxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIGqVL/9LbcUCUhpRSlIwBbJRL44wBdJRHQKYUhhmXgLt1fZQoaAZoCWgPQwhaETXRp1pxQJSGlFKUaBVNBwFoFkdAphS4UnG83HV9lChoBmgJaA9DCHJtqBinoHFAlIaUUpRoFUvnaBZHQKYVKfozN2V1fZQoaAZoCWgPQwgxC+2c5jhuQJSGlFKUaBVL3WgWR0CmFS0ojOcEdX2UKGgGaAloD0MIqcE0DJ9JcECUhpRSlGgVS/BoFkdAphVbjT8YRHV9lChoBmgJaA9DCLK9FvQe8HBAlIaUUpRoFUvQaBZHQKYVbsrNGEx1fZQoaAZoCWgPQwjHuOLiaD9zQJSGlFKUaBVL0mgWR0CmFW3Y+Sr6dX2UKGgGaAloD0MIOGivPh5FbkCUhpRSlGgVS+NoFkdAphWUYuTRpnV9lChoBmgJaA9DCLH8+bZg3XJAlIaUUpRoFUvLaBZHQKYV/vnbItF1fZQoaAZoCWgPQwgv98lRwOJwQJSGlFKUaBVL4WgWR0CmFk+5OJtSdX2UKGgGaAloD0MI8fCeA8sQcUCUhpRSlGgVS/1oFkdAphZiy+pOvnV9lChoBmgJaA9DCCE9RQ6RjXFAlIaUUpRoFUvzaBZHQKYWXXd0q6R1fZQoaAZoCWgPQwiwIM1YtOBxQJSGlFKUaBVL8mgWR0CmFwHiWE9MdX2UKGgGaAloD0MIG4ANiFBFc0CUhpRSlGgVS9loFkdAphb3IU8FIXV9lChoBmgJaA9DCG10zk9xfHJAlIaUUpRoFUv8aBZHQKYXIKPXCj11fZQoaAZoCWgPQwgkZCDPbktyQJSGlFKUaBVL6WgWR0CmF25Rjz7NdX2UKGgGaAloD0MILXdmgqGackCUhpRSlGgVS9FoFkdAphd6LCN0eXV9lChoBmgJaA9DCL8PBwnRJHBAlIaUUpRoFUvQaBZHQKYXseEqUeN1fZQoaAZoCWgPQwg9R+S7FDBzQJSGlFKUaBVL4WgWR0CmF8ve54GEdX2UKGgGaAloD0MI0A1N2alackCUhpRSlGgVS+loFkdAphjShakhzXV9lChoBmgJaA9DCJbs2AgEznBAlIaUUpRoFUv/aBZHQKYY5UrCm/F1fZQoaAZoCWgPQwjP2QJCK3xxQJSGlFKUaBVNKgFoFkdAphjeG7Bfr3V9lChoBmgJaA9DCPqzHymiKXFAlIaUUpRoFUvmaBZHQKYY8QiiZfF1fZQoaAZoCWgPQwhD5V/LKypzQJSGlFKUaBVL6mgWR0CmGOPx6OYIdX2UKGgGaAloD0MItKolHSVfcECUhpRSlGgVS+1oFkdAphkGepXIVHV9lChoBmgJaA9DCAiwyK+fV3BAlIaUUpRoFUvsaBZHQKYZXh2GIsR1fZQoaAZoCWgPQwgUdeYektVxQJSGlFKUaBVL3GgWR0CmGYlhG6PKdX2UKGgGaAloD0MIYCNJEO7NcECUhpRSlGgVTQEBaBZHQKYZxSn+AEt1fZQoaAZoCWgPQwiL3xRWaq9xQJSGlFKUaBVNFwFoFkdAphnr0Fr2x3V9lChoBmgJaA9DCDViZp9HuXJAlIaUUpRoFUv6aBZHQKYaFrC3w1B1fZQoaAZoCWgPQwjXpUboZ3dxQJSGlFKUaBVL8mgWR0CmGiH/DLr5dX2UKGgGaAloD0MIEr2MYrmgckCUhpRSlGgVS+hoFkdAphpKl7+kxnV9lChoBmgJaA9DCGAhc2WQRXJAlIaUUpRoFUvQaBZHQKYa6XO4XoF1fZQoaAZoCWgPQwg5fT1fM7FwQJSGlFKUaBVL1WgWR0CmGvnrY5DJdX2UKGgGaAloD0MILc4Y5oSfckCUhpRSlGgVS9JoFkdAphr5T850bXV9lChoBmgJaA9DCAmNYON6bW9AlIaUUpRoFUvuaBZHQKYbB/ustCl1fZQoaAZoCWgPQwjmBG1yeBtyQJSGlFKUaBVL6GgWR0CmG0jesPrfdX2UKGgGaAloD0MIti3KbBA8ckCUhpRSlGgVS/5oFkdAphs+ixmkFnV9lChoBmgJaA9DCDiez4C67nFAlIaUUpRoFUv0aBZHQKYboF/QSjB1fZQoaAZoCWgPQwi+g584gGpyQJSGlFKUaBVL1mgWR0CmHBBQN0/4dX2UKGgGaAloD0MIayv2l11fcUCUhpRSlGgVS/ZoFkdAphwPustCiXV9lChoBmgJaA9DCE8IHXSJQm9AlIaUUpRoFUvraBZHQKYcOSQHRkV1fZQoaAZoCWgPQwgSvYxiuXRxQJSGlFKUaBVL82gWR0CmHL6mfoRqdX2UKGgGaAloD0MIOGivPt6Cc0CUhpRSlGgVTQUBaBZHQKYdSvjfek51fZQoaAZoCWgPQwgVj4tqUWVwQJSGlFKUaBVL0WgWR0CmHVhikO7QdX2UKGgGaAloD0MIUhA8vv0rc0CUhpRSlGgVS/JoFkdAph1vJvHcUXV9lChoBmgJaA9DCA98DFacbXFAlIaUUpRoFUv7aBZHQKYd1gn+hoN1fZQoaAZoCWgPQwid1m1QeyBwQJSGlFKUaBVL+WgWR0CmHiMU7CBPdX2UKGgGaAloD0MIZYuk3egxbUCUhpRSlGgVS/JoFkdAph4vNzKcNHV9lChoBmgJaA9DCOoENBE293BAlIaUUpRoFUvZaBZHQKYemelKsdV1fZQoaAZoCWgPQwhHrptS3vByQJSGlFKUaBVNEQFoFkdAph7BRXOnmHV9lChoBmgJaA9DCKq4cYt5DHFAlIaUUpRoFU0gAWgWR0CmHsSHdoFndX2UKGgGaAloD0MIpmH4iFhTcUCUhpRSlGgVS9xoFkdAph7M2UB4lnV9lChoBmgJaA9DCJcaoZ/pOHFAlIaUUpRoFUvYaBZHQKYex114gRt1fZQoaAZoCWgPQwhNEeD0bmJxQJSGlFKUaBVL1WgWR0CmHwVPN3W4dX2UKGgGaAloD0MIq83/q866ckCUhpRSlGgVS+5oFkdAph8urbQC0XV9lChoBmgJaA9DCKxVuybkvXBAlIaUUpRoFUvzaBZHQKYfV3gUDdR1fZQoaAZoCWgPQwhmpN5TeYxwQJSGlFKUaBVL3GgWR0CmH5swtapxdX2UKGgGaAloD0MIteIbCl9zcUCUhpRSlGgVTQMBaBZHQKYfu4hllK91fZQoaAZoCWgPQwhXJ2co7kRzQJSGlFKUaBVL6mgWR0CmH7t1p0wKdX2UKGgGaAloD0MICvX0EXjubUCUhpRSlGgVS+JoFkdAph/pgPVd5nV9lChoBmgJaA9DCMgljjwQoXBAlIaUUpRoFUvbaBZHQKYf9DXvphZ1fZQoaAZoCWgPQwgWo661t+VyQJSGlFKUaBVLzWgWR0CmIGu1ndwedX2UKGgGaAloD0MIjexKy8ghcUCUhpRSlGgVS/ZoFkdApiCZqEeyRnV9lChoBmgJaA9DCANeZtgo/3JAlIaUUpRoFUvUaBZHQKYg43GXHBF1fZQoaAZoCWgPQwhmo3N+SqtxQJSGlFKUaBVL+GgWR0CmIN8POIIodX2UKGgGaAloD0MIK8O4G0SncUCUhpRSlGgVS+poFkdApiEgyO7xu3V9lChoBmgJaA9DCBx6i4d3iW1AlIaUUpRoFUvkaBZHQKYhWydnTRZ1fZQoaAZoCWgPQwjdC8wKxW5yQJSGlFKUaBVL8WgWR0CmIW/m1YyPdX2UKGgGaAloD0MIWHIVix8AcUCUhpRSlGgVS/1oFkdApiG5wl0HQnV9lChoBmgJaA9DCC1cVmGzXnFAlIaUUpRoFU0AAWgWR0CmInUJng5zdX2UKGgGaAloD0MIW0BoPXy3cECUhpRSlGgVS9hoFkdApiKNvS+g13V9lChoBmgJaA9DCP9YiA7BHXFAlIaUUpRoFUvsaBZHQKYijoqTbFl1fZQoaAZoCWgPQwhqFJLMqq9wQJSGlFKUaBVL92gWR0CmIq/0dzXCdX2UKGgGaAloD0MIprkVwurncECUhpRSlGgVS9doFkdApiMQ1DSgG3V9lChoBmgJaA9DCH7k1qSbz3BAlIaUUpRoFUvXaBZHQKYjLDXOGCZ1fZQoaAZoCWgPQwiKHvgYbGZyQJSGlFKUaBVNEAFoFkdApiNc/r0J4XV9lChoBmgJaA9DCHEFFOop93BAlIaUUpRoFUvkaBZHQKYjefthNM51fZQoaAZoCWgPQwie76fGy5RuQJSGlFKUaBVLzmgWR0CmI6xKQJXydX2UKGgGaAloD0MIZ0gVxetCckCUhpRSlGgVS+BoFkdApiPWapgkT3V9lChoBmgJaA9DCAHeAglKbnBAlIaUUpRoFUvFaBZHQKYj1izcAR11fZQoaAZoCWgPQwi9APvoVJ1xQJSGlFKUaBVLzWgWR0CmJDRW1c+rdX2UKGgGaAloD0MIpZ4FobxDbUCUhpRSlGgVS+VoFkdApiQ0t9QXRHV9lChoBmgJaA9DCBZQqKcPwnBAlIaUUpRoFUvQaBZHQKYkgZ4wAVB1fZQoaAZoCWgPQwi6pGq7ibFvQJSGlFKUaBVL5WgWR0CmJMaYVqN7dX2UKGgGaAloD0MImuleJ3XYbkCUhpRSlGgVS+RoFkdApiTEOf/WD3V9lChoBmgJaA9DCPDAAMIHsHBAlIaUUpRoFUvoaBZHQKYk2/X5FgF1fZQoaAZoCWgPQwjwplt2CJ9zQJSGlFKUaBVLyWgWR0CmJUIV2zOYdX2UKGgGaAloD0MI4NkevSGoc0CUhpRSlGgVS+poFkdApiVSgmJFb3V9lChoBmgJaA9DCBTtKqR8DG5AlIaUUpRoFUvraBZHQKYlgVnEl3R1fZQoaAZoCWgPQwhbXOMzWaFwQJSGlFKUaBVL3WgWR0CmJbf1g6U8dX2UKGgGaAloD0MICqNZ2f7bcUCUhpRSlGgVS/JoFkdApiX2N70Fr3V9lChoBmgJaA9DCDW214Ke2HJAlIaUUpRoFUvyaBZHQKYmFxb0OEx1fZQoaAZoCWgPQwj/WIgOge5tQJSGlFKUaBVL82gWR0CmJh1qWToudX2UKGgGaAloD0MIpmPOM3YGb0CUhpRSlGgVS9xoFkdApiZos9SuQ3V9lChoBmgJaA9DCDMzMzMznXFAlIaUUpRoFUvyaBZHQKYmzJTVDrt1fZQoaAZoCWgPQwiBI4EGG6pwQJSGlFKUaBVL52gWR0CmJvlv60pmdX2UKGgGaAloD0MI36Y/+xG7b0CUhpRSlGgVS+hoFkdApib7q6e5F3V9lChoBmgJaA9DCJKumXyz1nFAlIaUUpRoFUvhaBZHQKYnDHy3CsR1fZQoaAZoCWgPQwhssdtnlc5uQJSGlFKUaBVL1mgWR0CmJ09gOSW7dWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 312, "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, "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"}} |