a2c-PandaReachDense-v2 / config.json
AtilliO's picture
Initial commit
618c5e9
raw
history blame
15.5 kB
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n MultiInputActorClass 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 (Tuple)\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: Uses the CombinedExtractor\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 MultiInputActorCriticPolicy.__init__ at 0x7b469176f0a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b4691762bc0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1691326154035176974, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA1SrVPnATND3M9ww/1SrVPnATND3M9ww/1SrVPnATND3M9ww/1SrVPnATND3M9ww/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAzWN5P4yA0z8PZKq+CtuhvygdlT7CxQ8/ph06P2Q3sb+Oy16/6/2vv9M1rT/NN0G+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADVKtU+cBM0Pcz3DD8VLwQ8KnUXO4G0gzzVKtU+cBM0Pcz3DD8VLwQ8KnUXO4G0gzzVKtU+cBM0Pcz3DD8VLwQ8KnUXO4G0gzzVKtU+cBM0Pcz3DD8VLwQ8KnUXO4G0gzyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[0.4163424 0.04396385 0.5506561 ]\n [0.4163424 0.04396385 0.5506561 ]\n [0.4163424 0.04396385 0.5506561 ]\n [0.4163424 0.04396385 0.5506561 ]]", "desired_goal": "[[ 0.9741791 1.6523604 -0.33279464]\n [-1.264497 0.29123807 0.5616113 ]\n [ 0.7270149 -1.3845029 -0.8702935 ]\n [-1.3749365 1.3532051 -0.18868943]]", "observation": "[[0.4163424 0.04396385 0.5506561 0.00806787 0.00231106 0.01607728]\n [0.4163424 0.04396385 0.5506561 0.00806787 0.00231106 0.01607728]\n [0.4163424 0.04396385 0.5506561 0.00806787 0.00231106 0.01607728]\n [0.4163424 0.04396385 0.5506561 0.00806787 0.00231106 0.01607728]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]", "desired_goal": "[[-0.13889503 -0.02196605 0.15504013]\n [ 0.12941794 0.01853759 0.1112928 ]\n [-0.05007752 0.09059015 0.18049109]\n [ 0.07352111 -0.11001007 0.06007828]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIUS6NX3hFEcCUhpRSlIwBbJRLMowBdJRHQKbLljAi3Xt1fZQoaAZoCWgPQwjSqMDJNnAPwJSGlFKUaBVLMmgWR0Cmy1XqzJIUdX2UKGgGaAloD0MIKzBkdav3FcCUhpRSlGgVSzJoFkdApssYQOFxn3V9lChoBmgJaA9DCCHqPgCpHRjAlIaUUpRoFUsyaBZHQKbK1oL5RCR1fZQoaAZoCWgPQwj11VWBWqwHwJSGlFKUaBVLMmgWR0CmzHzIV/MGdX2UKGgGaAloD0MInFCIgEMYGsCUhpRSlGgVSzJoFkdApsw8kyDZlHV9lChoBmgJaA9DCIlccAZ/3w7AlIaUUpRoFUsyaBZHQKbL/uVHFxZ1fZQoaAZoCWgPQwg9K2nFN1QewJSGlFKUaBVLMmgWR0Cmy70CRwIddX2UKGgGaAloD0MIaw97oYDNCcCUhpRSlGgVSzJoFkdAps1qj8DSxHV9lChoBmgJaA9DCDze5LfopAjAlIaUUpRoFUsyaBZHQKbNKj0th/l1fZQoaAZoCWgPQwijeQCL/LoLwJSGlFKUaBVLMmgWR0CmzOyFfzBidX2UKGgGaAloD0MIv2GiQQqeGMCUhpRSlGgVSzJoFkdApsyqshgVoHV9lChoBmgJaA9DCLa5MT1hmRDAlIaUUpRoFUsyaBZHQKbOTeMQ2/B1fZQoaAZoCWgPQwjAJJUp5iATwJSGlFKUaBVLMmgWR0Cmzg2IoE0SdX2UKGgGaAloD0MIr7X3qSq0BsCUhpRSlGgVSzJoFkdAps3P2oNutXV9lChoBmgJaA9DCOlDF9S3rA3AlIaUUpRoFUsyaBZHQKbNjgBLf1p1fZQoaAZoCWgPQwgGuCBblk8OwJSGlFKUaBVLMmgWR0CmzzuWSlnAdX2UKGgGaAloD0MI2jnNAu2OB8CUhpRSlGgVSzJoFkdAps77SThYNnV9lChoBmgJaA9DCDhKXp1j4ATAlIaUUpRoFUsyaBZHQKbOvZr56+p1fZQoaAZoCWgPQwg+lj50Qd0XwJSGlFKUaBVLMmgWR0Cmznu2y9mIdX2UKGgGaAloD0MI1SZO7ndIEsCUhpRSlGgVSzJoFkdAptA4fOlfq3V9lChoBmgJaA9DCIRKXMe44hDAlIaUUpRoFUsyaBZHQKbP+Df3vhJ1fZQoaAZoCWgPQwjgZBu4AwUXwJSGlFKUaBVLMmgWR0Cmz7qNIbwSdX2UKGgGaAloD0MIqu6RzVXzDcCUhpRSlGgVSzJoFkdAps94uEmICXV9lChoBmgJaA9DCJ8DyxEywBTAlIaUUpRoFUsyaBZHQKbRJ3zMA3l1fZQoaAZoCWgPQwhwQbYsX/cGwJSGlFKUaBVLMmgWR0Cm0OeCCjDbdX2UKGgGaAloD0MIUrr0L0l1EcCUhpRSlGgVSzJoFkdAptCpxDLKWHV9lChoBmgJaA9DCAUyO4vemRfAlIaUUpRoFUsyaBZHQKbQZ9iMHbB1fZQoaAZoCWgPQwgKD5pd9xYGwJSGlFKUaBVLMmgWR0Cm0hixmkFfdX2UKGgGaAloD0MIVDVB1H3gFsCUhpRSlGgVSzJoFkdAptHYam4y5HV9lChoBmgJaA9DCPoI/OHnnwvAlIaUUpRoFUsyaBZHQKbRmsunMt91fZQoaAZoCWgPQwheZtgo6xcIwJSGlFKUaBVLMmgWR0Cm0VjnNgSfdX2UKGgGaAloD0MIn82qz9W2EcCUhpRSlGgVSzJoFkdAptMWgL7XQXV9lChoBmgJaA9DCBr35jdMtAXAlIaUUpRoFUsyaBZHQKbS1k/8l5Z1fZQoaAZoCWgPQwhe1y/YDXsGwJSGlFKUaBVLMmgWR0Cm0pivX9R8dX2UKGgGaAloD0MI/7EQHQLHC8CUhpRSlGgVSzJoFkdAptJW2oegc3V9lChoBmgJaA9DCAYN/RNcLAjAlIaUUpRoFUsyaBZHQKbUB8cdYGN1fZQoaAZoCWgPQwgr+G2I8foRwJSGlFKUaBVLMmgWR0Cm08eFcpsodX2UKGgGaAloD0MIFlCop49gCMCUhpRSlGgVSzJoFkdAptOJ6By0bHV9lChoBmgJaA9DCHTU0XE1cgjAlIaUUpRoFUsyaBZHQKbTSADJU5x1fZQoaAZoCWgPQwhKCiyAKWMGwJSGlFKUaBVLMmgWR0Cm1UO3MINWdX2UKGgGaAloD0MIgGPPnsuEFsCUhpRSlGgVSzJoFkdAptUDzundf3V9lChoBmgJaA9DCGkaFM0DWAXAlIaUUpRoFUsyaBZHQKbUxsniNsF1fZQoaAZoCWgPQwh79Ib7yC0SwJSGlFKUaBVLMmgWR0Cm1IWMbWEsdX2UKGgGaAloD0MIP1dbsb9MCMCUhpRSlGgVSzJoFkdAptawwAU+LXV9lChoBmgJaA9DCJhr0QK0XRXAlIaUUpRoFUsyaBZHQKbWcQJ5VwR1fZQoaAZoCWgPQwjgSKDBpk4OwJSGlFKUaBVLMmgWR0Cm1jP60pmVdX2UKGgGaAloD0MIaoZUUbxqFMCUhpRSlGgVSzJoFkdAptXyoqCpWHV9lChoBmgJaA9DCFiOkIE8uw3AlIaUUpRoFUsyaBZHQKbYF0Eovzx1fZQoaAZoCWgPQwiILNLEO4AUwJSGlFKUaBVLMmgWR0Cm19d8JD3NdX2UKGgGaAloD0MIySHi5lTyGMCUhpRSlGgVSzJoFkdApteaWqtHQXV9lChoBmgJaA9DCN5VD5iHzBbAlIaUUpRoFUsyaBZHQKbXWZb6guh1fZQoaAZoCWgPQwiwVu2akNYKwJSGlFKUaBVLMmgWR0Cm2aLYf4h2dX2UKGgGaAloD0MIzuLFwhCJFMCUhpRSlGgVSzJoFkdAptljJuEVWXV9lChoBmgJaA9DCEz/klSmeBLAlIaUUpRoFUsyaBZHQKbZJinYQJ51fZQoaAZoCWgPQwh/pIgMq1gUwJSGlFKUaBVLMmgWR0Cm2OT/IbOvdX2UKGgGaAloD0MIY3/ZPXk4DMCUhpRSlGgVSzJoFkdAptslM7EHdHV9lChoBmgJaA9DCDdwB+qUtxPAlIaUUpRoFUsyaBZHQKba5WRzRx91fZQoaAZoCWgPQwg4ZtmTwEYSwJSGlFKUaBVLMmgWR0Cm2qjBEa2ndX2UKGgGaAloD0MIsRh1rb3PGMCUhpRSlGgVSzJoFkdAptpnXRPXTXV9lChoBmgJaA9DCP3BwHPvgQ7AlIaUUpRoFUsyaBZHQKbcWTQmeDp1fZQoaAZoCWgPQwiUTE7tDKMRwJSGlFKUaBVLMmgWR0Cm3BkhRqGldX2UKGgGaAloD0MImPvkKEBUD8CUhpRSlGgVSzJoFkdAptvbsKLKm3V9lChoBmgJaA9DCMR7DixHGBTAlIaUUpRoFUsyaBZHQKbbmhL5AQh1fZQoaAZoCWgPQwjKayV0l0QawJSGlFKUaBVLMmgWR0Cm3UVc+qzadX2UKGgGaAloD0MIozodyHp6EcCUhpRSlGgVSzJoFkdApt0FmYjSonV9lChoBmgJaA9DCMV1jCsu7hLAlIaUUpRoFUsyaBZHQKbcyLxZuAJ1fZQoaAZoCWgPQwi/0vnwLAEOwJSGlFKUaBVLMmgWR0Cm3IdweeWfdX2UKGgGaAloD0MIPDHrxVCOEsCUhpRSlGgVSzJoFkdApt4y+JxecHV9lChoBmgJaA9DCIkJavgWthnAlIaUUpRoFUsyaBZHQKbd8qtHQQd1fZQoaAZoCWgPQwgjumddo/USwJSGlFKUaBVLMmgWR0Cm3bUKiO/+dX2UKGgGaAloD0MI5fG0/MCVBMCUhpRSlGgVSzJoFkdApt1zfixVyXV9lChoBmgJaA9DCO1GH/MBQQnAlIaUUpRoFUsyaBZHQKbfIFlkH2R1fZQoaAZoCWgPQwi9cyhDVQwVwJSGlFKUaBVLMmgWR0Cm3uBRqGlAdX2UKGgGaAloD0MID39N1qgHDMCUhpRSlGgVSzJoFkdApt6imj0tiHV9lChoBmgJaA9DCChjfJi9rAnAlIaUUpRoFUsyaBZHQKbeYNgjQiR1fZQoaAZoCWgPQwiNfF7x1CMLwJSGlFKUaBVLMmgWR0Cm4A2IXTEzdX2UKGgGaAloD0MITfVk/tF3F8CUhpRSlGgVSzJoFkdApt/NQCSzPnV9lChoBmgJaA9DCIBG6dK/JATAlIaUUpRoFUsyaBZHQKbfj5wfhdd1fZQoaAZoCWgPQwgIkKFjB6UUwJSGlFKUaBVLMmgWR0Cm3029+PRzdX2UKGgGaAloD0MIc6JdhZQ/DcCUhpRSlGgVSzJoFkdApuD3hddE9nV9lChoBmgJaA9DCHzT9NkB9wXAlIaUUpRoFUsyaBZHQKbgt0T101Z1fZQoaAZoCWgPQwgLDcSymcMPwJSGlFKUaBVLMmgWR0Cm4Hml67d0dX2UKGgGaAloD0MIoYFYNnPYFsCUhpRSlGgVSzJoFkdApuA3znRsuXV9lChoBmgJaA9DCOVH/Io1/A3AlIaUUpRoFUsyaBZHQKbh8ocaOxV1fZQoaAZoCWgPQwjxZaIIqRsCwJSGlFKUaBVLMmgWR0Cm4bJo0ygxdX2UKGgGaAloD0MI3NjsSPX9FsCUhpRSlGgVSzJoFkdApuF08TzunnV9lChoBmgJaA9DCKBwdmuZTAbAlIaUUpRoFUsyaBZHQKbhM0TDfm91fZQoaAZoCWgPQwiXAz3UtgENwJSGlFKUaBVLMmgWR0Cm4wxKQJXydX2UKGgGaAloD0MIMo/8wcCTBMCUhpRSlGgVSzJoFkdApuLMlolD4XV9lChoBmgJaA9DCM6MfjSc8hvAlIaUUpRoFUsyaBZHQKbijzz3AVR1fZQoaAZoCWgPQwhyFCAKZlwVwJSGlFKUaBVLMmgWR0Cm4k3TNMXadX2UKGgGaAloD0MIcJS8OsdwIMCUhpRSlGgVSzJoFkdApuQY5myxA3V9lChoBmgJaA9DCKLuA5DaRB3AlIaUUpRoFUsyaBZHQKbj2OdXko51fZQoaAZoCWgPQwitMH2vIUgWwJSGlFKUaBVLMmgWR0Cm45trCWNWdX2UKGgGaAloD0MIrrfNVIhnHcCUhpRSlGgVSzJoFkdApuNaEQGwA3V9lChoBmgJaA9DCJsff2lRjxHAlIaUUpRoFUsyaBZHQKblJl4keIV1fZQoaAZoCWgPQwhpdAexM2URwJSGlFKUaBVLMmgWR0Cm5OY2sJY1dX2UKGgGaAloD0MIhxVu+UgqD8CUhpRSlGgVSzJoFkdApuSo0hvBJ3V9lChoBmgJaA9DCBaE8j6OFhfAlIaUUpRoFUsyaBZHQKbkZzPrv9d1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 50000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}