a2c-PandaReachDense-v2 / config.json
Shridipta-06's picture
Third commit
46fe69d
{"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 0x7f6a53ed2ef0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f6a53ece5c0>"}, "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": 3000000, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688776934824039565, "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": "[[0.46076372 0.04455959 0.6587819 ]\n [0.46076372 0.04455959 0.6587819 ]\n [0.46076372 0.04455959 0.6587819 ]\n [0.46076372 0.04455959 0.6587819 ]]", "desired_goal": "[[-0.4400167 -0.05734827 0.9209131 ]\n [ 0.92251605 -1.4212607 0.65496427]\n [-1.0392325 -0.06802563 -0.7323974 ]\n [ 0.5625973 -0.94692075 -0.01809734]]", "observation": "[[ 0.46076372 0.04455959 0.6587819 0.01075925 -0.0023531 0.01246976]\n [ 0.46076372 0.04455959 0.6587819 0.01075925 -0.0023531 0.01246976]\n [ 0.46076372 0.04455959 0.6587819 0.01075925 -0.0023531 0.01246976]\n [ 0.46076372 0.04455959 0.6587819 0.01075925 -0.0023531 0.01246976]]"}, "_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": "[[-9.9671073e-02 1.3104962e-01 2.7320245e-01]\n [ 3.0070953e-02 1.5929168e-02 3.4999624e-02]\n [ 6.3231260e-02 3.5115618e-02 2.3606233e-01]\n [ 6.8361677e-02 -6.1357030e-05 2.9042518e-01]]", "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:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 150000, "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:": "gAWVWAMAAAAAAACMD2d5bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwOZ3ltLnNwYWNlcy5ib3iUjANCb3iUk5QpgZR9lCiMBWR0eXBllIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowGX3NoYXBllEsDhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZSMAUOUdJRSlIwEaGlnaJRoHiiWDAAAAAAAAAAAACBBAAAgQQAAIEGUaBZLA4WUaCF0lFKUjA1ib3VuZGVkX2JlbG93lGgeKJYDAAAAAAAAAAEBAZRoE4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksDhZRoIXSUUpSMDWJvdW5kZWRfYWJvdmWUaB4olgMAAAAAAAAAAQEBlGgtSwOFlGghdJRSlIwKX25wX3JhbmRvbZROdWKMDGRlc2lyZWRfZ29hbJRoDSmBlH2UKGgQaBZoGUsDhZRoG2geKJYMAAAAAAAAAAAAIMEAACDBAAAgwZRoFksDhZRoIXSUUpRoJGgeKJYMAAAAAAAAAAAAIEEAACBBAAAgQZRoFksDhZRoIXSUUpRoKWgeKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoM2geKJYDAAAAAAAAAAEBAZRoLUsDhZRoIXSUUpRoOE51YowLb2JzZXJ2YXRpb26UaA0pgZR9lChoEGgWaBlLBoWUaBtoHiiWGAAAAAAAAAAAACDBAAAgwQAAIMEAACDBAAAgwQAAIMGUaBZLBoWUaCF0lFKUaCRoHiiWGAAAAAAAAAAAACBBAAAgQQAAIEEAACBBAAAgQQAAIEGUaBZLBoWUaCF0lFKUaCloHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDNoHiiWBgAAAAAAAAABAQEBAQGUaC1LBoWUaCF0lFKUaDhOdWJ1aBlOaBBOaDhOdWIu", "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:": "gAWVcwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaAtLA4WUjAFDlHSUUpSMBGhpZ2iUaBMolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgLSwOFlGgWdJRSlIwNYm91bmRlZF9iZWxvd5RoEyiWAwAAAAAAAAABAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBZ0lFKUjA1ib3VuZGVkX2Fib3ZllGgTKJYDAAAAAAAAAAEBAZRoIksDhZRoFnSUUpSMCl9ucF9yYW5kb22UTnViLg==", "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 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"}}