a2c-PandaReachDense-v2 / config.json
yotoshihiro
Initial commit
d2ead38
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 0x7fafd9cd5990>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fafd9ccd580>"}, "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": 1684654534888193050, "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": "[[0.4631245 0.03164394 0.5994048 ]\n [0.4631245 0.03164394 0.5994048 ]\n [0.4631245 0.03164394 0.5994048 ]\n [0.4631245 0.03164394 0.5994048 ]]", "desired_goal": "[[-1.7175791 0.8512162 1.2886976 ]\n [-0.65547967 1.4171824 -1.2938646 ]\n [-0.972089 0.67036605 0.46919164]\n [-0.29666254 0.61533856 -0.6451564 ]]", "observation": "[[0.4631245 0.03164394 0.5994048 0.00479688 0.00494517 0.01214627]\n [0.4631245 0.03164394 0.5994048 0.00479688 0.00494517 0.01214627]\n [0.4631245 0.03164394 0.5994048 0.00479688 0.00494517 0.01214627]\n [0.4631245 0.03164394 0.5994048 0.00479688 0.00494517 0.01214627]]"}, "_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": "[[-0.11651628 0.07838845 0.23658215]\n [ 0.04214129 0.03049028 0.02866958]\n [-0.06492693 -0.01990527 0.07534819]\n [-0.03103387 -0.13421676 0.14900172]]", "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 '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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}