0xC4LL3's picture
First commit of A2C agent for PandaPickAndPlace
8db1b8e
raw
history blame
17 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 0x78d8b0eb9510>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78d8b0eb2000>"}, "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": 1696682050169583958, "learning_rate": 0.0007, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[-1.9014017e-01 -6.2749189e-01 1.7191164e-01]\n [-1.6899967e-01 -5.7401397e-04 1.7190804e-01]\n [ 1.0132674e+00 9.9742544e-01 1.7190507e-01]\n [-2.2088231e-01 9.4363278e-01 1.7190970e-01]]", "desired_goal": "[[-0.3759121 0.35174388 0.9029551 ]\n [-1.4869062 0.8077521 0.0193118 ]\n [ 0.37035877 0.88577145 0.39375782]\n [ 0.86583453 1.1270192 -0.3770866 ]]", "observation": "[[-6.27600551e-01 -2.19925091e-01 -8.24127257e-01 7.61142612e-01\n 4.45487708e-01 -2.63282388e-01 -4.13981318e-01 -1.90140173e-01\n -6.27491891e-01 1.71911642e-01 3.01530585e-04 -9.85093229e-03\n -3.11905388e-02 2.09004357e-02 -4.05089520e-02 8.25519785e-02\n 1.26435421e-02 -3.32930163e-02 -2.24563014e-02]\n [-1.37281966e+00 -1.73702165e-01 -3.28247011e-01 2.12390208e+00\n -9.64424536e-02 2.03107715e+00 1.46837592e+00 -1.68999672e-01\n -5.74013975e-04 1.71908036e-01 2.44936586e-04 -9.78299789e-03\n -3.07752136e-02 2.10461244e-02 -4.03639935e-02 8.25235024e-02\n 1.28415590e-02 -3.32929641e-02 -2.22056899e-02]\n [-1.35672078e-01 -1.99839771e-01 -9.39794242e-01 7.72521555e-01\n -3.95363748e-01 3.51366296e-04 -4.06886131e-01 1.01326740e+00\n 9.97425437e-01 1.71905071e-01 3.63365747e-04 -9.75989550e-03\n -2.99898349e-02 2.11728532e-02 -4.07794714e-02 8.25235024e-02\n 1.28415665e-02 -3.32929939e-02 -2.20578462e-02]\n [-1.20396554e+00 2.84279674e-01 -4.26170439e-01 -1.71899259e+00\n 1.44713950e+00 1.16024208e+00 1.39672816e+00 -2.20882311e-01\n 9.43632782e-01 1.71909705e-01 3.41369421e-04 -9.82527900e-03\n -3.11695747e-02 2.07069702e-02 -4.02296446e-02 8.23850259e-02\n 1.11078126e-02 -3.43000591e-02 -2.23957207e-02]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.00096711 -0.06612108 0.02 ]\n [-0.12207589 -0.10285319 0.02 ]\n [ 0.14220344 -0.1089286 0.02 ]\n [ 0.08871587 0.1299762 0.02 ]]", "desired_goal": "[[ 0.01238785 0.12165028 0.17331754]\n [ 0.01936581 -0.11059138 0.18754672]\n [-0.09998512 0.10487051 0.17212778]\n [-0.10810276 -0.09654342 0.1101054 ]]", "observation": "[[ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 9.67112719e-04\n -6.61210790e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -1.22075893e-01\n -1.02853194e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 1.42203435e-01\n -1.08928598e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 8.87158737e-02\n 1.29976198e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+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, (19,), 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 True]", "bounded_above": "[ True True True True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}