a2c-PandaReachDense-v2 / config.json
andrei-saceleanu's picture
Commit #3
f0e4fa6
{"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 0x7f47cab3aee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f47cab36de0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "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, "num_timesteps": 1500000, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1674723318401722280, "learning_rate": 0.00096, "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": "[[0.2453028 0.00300309 0.5651783 ]\n [0.2453028 0.00300309 0.5651783 ]\n [0.2453028 0.00300309 0.5651783 ]\n [0.2453028 0.00300309 0.5651783 ]]", "desired_goal": "[[ 0.9009005 1.4298149 0.5355709 ]\n [-0.3384777 -0.90674615 0.9914977 ]\n [-0.531913 -0.0901069 1.0902642 ]\n [ 0.91152966 0.32453346 1.3182898 ]]", "observation": "[[0.2453028 0.00300309 0.5651783 0.04757169 0.00309532 0.06007918]\n [0.2453028 0.00300309 0.5651783 0.04757169 0.00309532 0.06007918]\n [0.2453028 0.00300309 0.5651783 0.04757169 0.00309532 0.06007918]\n [0.2453028 0.00300309 0.5651783 0.04757169 0.00309532 0.06007918]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAEQrHvRa83D0qNGE9FM1CPUz04j3mq5M+xtUYvo9Wpr1DqCc9LREGPq9Z0r3J8LA8lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[-0.09718717 0.10778062 0.05498139]\n [ 0.04755886 0.11081752 0.28842086]\n [-0.14925298 -0.08121978 0.04093195]\n [ 0.1309249 -0.10271012 0.02159919]]", "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": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 46875, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}