File size: 15,640 Bytes
2b6db5f |
1 |
{"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 0x7fea093d8430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fea093d6a80>"}, "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": 1682165515772438364, "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": "[[0.41968834 0.00240471 0.603941 ]\n [0.41968834 0.00240471 0.603941 ]\n [0.41968834 0.00240471 0.603941 ]\n [0.41968834 0.00240471 0.603941 ]]", "desired_goal": "[[ 0.26515862 -0.57539064 -1.0841217 ]\n [-0.52676076 0.48448774 0.7636437 ]\n [-0.651161 -1.3933295 1.3354737 ]\n [ 0.3409599 0.601789 -0.88416916]]", "observation": "[[ 4.1968834e-01 2.4047145e-03 6.0394102e-01 5.3687594e-03\n -2.6911119e-04 4.0479340e-03]\n [ 4.1968834e-01 2.4047145e-03 6.0394102e-01 5.3687594e-03\n -2.6911119e-04 4.0479340e-03]\n [ 4.1968834e-01 2.4047145e-03 6.0394102e-01 5.3687594e-03\n -2.6911119e-04 4.0479340e-03]\n [ 4.1968834e-01 2.4047145e-03 6.0394102e-01 5.3687594e-03\n -2.6911119e-04 4.0479340e-03]]"}, "_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": "[[ 0.09243681 -0.10221669 0.22554094]\n [ 0.04285616 -0.11646201 0.07040366]\n [ 0.04921832 0.02283826 0.12044468]\n [-0.08959702 0.11146685 0.10228491]]", "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-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}} |