a2c-PandaReachDense-v2 / config.json
bsenst's picture
commit a2c-PandaReachDense-v2
bad5396
raw
history blame
15.9 kB
{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__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 0x74d6cd8e6200>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x74d6cd843e40>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gASVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 500000, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681356411662449620, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[3.6041334e-01 1.1638246e-04 5.5005938e-01]\n [3.6041334e-01 1.1638246e-04 5.5005938e-01]\n [3.6041334e-01 1.1638246e-04 5.5005938e-01]\n [3.6041334e-01 1.1638246e-04 5.5005938e-01]]", "desired_goal": "[[ 0.6146432 -0.8561748 -1.5529544 ]\n [ 0.34249 0.35144597 -0.09810262]\n [-0.7075738 0.09926184 1.1396627 ]\n [-0.82559675 -1.4829557 -0.71278936]]", "observation": "[[3.6041334e-01 1.1638246e-04 5.5005938e-01 1.5567051e-04 8.5071115e-05\n 4.5359782e-03]\n [3.6041334e-01 1.1638246e-04 5.5005938e-01 1.5567051e-04 8.5071115e-05\n 4.5359782e-03]\n [3.6041334e-01 1.1638246e-04 5.5005938e-01 1.5567051e-04 8.5071115e-05\n 4.5359782e-03]\n [3.6041334e-01 1.1638246e-04 5.5005938e-01 1.5567051e-04 8.5071115e-05\n 4.5359782e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAEBAQGUdJRiLg=="}, "_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": "[[-0.04653713 -0.14105336 0.14583465]\n [ 0.10636713 0.07777031 0.15173781]\n [ 0.10170978 -0.14878033 0.19063649]\n [ 0.1342813 -0.11611761 0.26896277]]", "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:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 25000, "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-5.15.90+-x86_64-with-debian-bullseye-sid # 1 SMP Thu Apr 6 11:02:12 UTC 2023", "Python": "3.7.12", "Stable-Baselines3": "1.8.0", "PyTorch": "1.13.0+cpu", "GPU Enabled": "False", "Numpy": "1.21.6", "Gym": "0.21.0"}}