a2c-PandaReachDense-v3 / config.json
ckandemir's picture
Initial commit
74c4f11
raw
history blame contribute delete
No virus
14.5 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 0x7fc98ad5e170>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc98af5b080>"}, "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": 1691971522237228781, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 2.9781005e-01 -1.2641732e-04 4.4971415e-01]\n [-9.2245214e-02 -4.6738312e-01 -2.2524083e-01]\n [-1.4695113e+00 -1.2806302e+00 7.0572317e-01]\n [ 2.9781005e-01 -1.2641732e-04 4.4971415e-01]]", "desired_goal": "[[ 0.06619154 -1.5942304 -1.3848159 ]\n [-0.89448917 -1.3649727 -0.92443186]\n [-1.1511927 -0.92374045 1.3277119 ]\n [-1.5370494 0.47631752 1.0607139 ]]", "observation": "[[ 2.9781005e-01 -1.2641732e-04 4.4971415e-01 4.7397768e-01\n -6.0571916e-03 3.8357350e-01]\n [-9.2245214e-02 -4.6738312e-01 -2.2524083e-01 -1.7843813e+00\n -1.6887571e+00 -1.3661798e+00]\n [-1.4695113e+00 -1.2806302e+00 7.0572317e-01 -6.9935578e-01\n -8.0923736e-01 1.6510699e+00]\n [ 2.9781005e-01 -1.2641732e-04 4.4971415e-01 4.7397768e-01\n -6.0571916e-03 3.8357350e-01]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": "[[ 0.02033504 -0.0626264 0.15094498]\n [ 0.09177888 -0.04334509 0.1689116 ]\n [ 0.06829059 -0.09330771 0.14435327]\n [-0.12751932 -0.12787823 0.03141209]]", "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": 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 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "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": "2.0.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}