| { | |
| "policy_class": { | |
| ":type:": "<class 'abc.ABCMeta'>", | |
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| "__module__": "sb3_contrib.qrdqn.policies", | |
| "__doc__": "\n Policy class with quantile and target networks for QR-DQN.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param n_quantiles: Number of quantiles\n :param net_arch: The specification of the network architecture.\n :param activation_fn: Activation function\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\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 QRDQNPolicy.__init__ at 0x7f48962d3820>", | |
| "_build": "<function QRDQNPolicy._build at 0x7f48962d38b0>", | |
| "make_quantile_net": "<function QRDQNPolicy.make_quantile_net at 0x7f48962d3940>", | |
| "forward": "<function QRDQNPolicy.forward at 0x7f48962d39d0>", | |
| "_predict": "<function QRDQNPolicy._predict at 0x7f48962d3a60>", | |
| "_get_constructor_parameters": "<function QRDQNPolicy._get_constructor_parameters at 0x7f48962d3af0>", | |
| "set_training_mode": "<function QRDQNPolicy.set_training_mode at 0x7f48962d3b80>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc._abc_data object at 0x7f48962d6800>" | |
| }, | |
| "verbose": 1, | |
| "policy_kwargs": { | |
| ":type:": "<class 'dict'>", | |
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| "net_arch": [ | |
| 256, | |
| 256 | |
| ], | |
| "n_quantiles": 25, | |
| "optimizer_class": "<class 'torch.optim.adam.Adam'>", | |
| "optimizer_kwargs": { | |
| "eps": 7.8125e-05 | |
| } | |
| }, | |
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| ":type:": "<class 'gym.spaces.box.Box'>", | |
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| "low": "[ -1. -1. -1. -1. -12.566371 -28.274334]", | |
| "high": "[ 1. 1. 1. 1. 12.566371 28.274334]", | |
| "bounded_below": "[ True True True True True True]", | |
| "bounded_above": "[ True True True True True True]", | |
| "_np_random": null | |
| }, | |
| "action_space": { | |
| ":type:": "<class 'gym.spaces.discrete.Discrete'>", | |
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| }, | |
| "ep_success_buffer": { | |
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| }, | |
| "_n_updates": 100000, | |
| "buffer_size": 1, | |
| "batch_size": 128, | |
| "learning_starts": 0, | |
| "tau": 1.0, | |
| "gamma": 0.99, | |
| "gradient_steps": -1, | |
| "optimize_memory_usage": false, | |
| "replay_buffer_class": { | |
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| "__module__": "stable_baselines3.common.buffers", | |
| "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device: PyTorch device\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n Cannot be used in combination with handle_timeout_termination.\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ", | |
| "__init__": "<function ReplayBuffer.__init__ at 0x7f489676a430>", | |
| "add": "<function ReplayBuffer.add at 0x7f489676a4c0>", | |
| "sample": "<function ReplayBuffer.sample at 0x7f489676a550>", | |
| "_get_samples": "<function ReplayBuffer._get_samples at 0x7f489676a5e0>", | |
| "__abstractmethods__": "frozenset()", | |
| "_abc_impl": "<_abc._abc_data object at 0x7f4896761c00>" | |
| }, | |
| "replay_buffer_kwargs": {}, | |
| "train_freq": { | |
| ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", | |
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| }, | |
| "actor": null, | |
| "use_sde_at_warmup": false, | |
| "exploration_initial_eps": 1.0, | |
| "exploration_final_eps": 0.1, | |
| "exploration_fraction": 0.12, | |
| "target_update_interval": 250, | |
| "max_grad_norm": null, | |
| "exploration_rate": 0.1, | |
| "exploration_schedule": { | |
| ":type:": "<class 'function'>", | |
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| }, | |
| "n_quantiles": 25, | |
| "batch_norm_stats": [], | |
| "batch_norm_stats_target": [] | |
| } |