File size: 16,026 Bytes
f0acc73 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
{
"policy_class": {
":type:": "<class 'abc.ABCMeta'>",
":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
"__module__": "stable_baselines3.common.policies",
"__doc__": "\n 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\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: Features extractor to use.\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 ActorCriticPolicy.__init__ at 0x7fc194210d30>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc194210dc0>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc194210e50>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc194210ee0>",
"_build": "<function ActorCriticPolicy._build at 0x7fc194210f70>",
"forward": "<function ActorCriticPolicy.forward at 0x7fc194212040>",
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc1942120d0>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc194212160>",
"_predict": "<function ActorCriticPolicy._predict at 0x7fc1942121f0>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc194212280>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc194212310>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc1942123a0>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc._abc_data object at 0x7fc194211640>"
},
"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
}
},
"observation_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
6
],
"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'>",
":serialized:": "gAWVUgsAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLA4wGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZSMFG51bXB5LnJhbmRvbS5fcGlja2xllIwSX19yYW5kb21zdGF0ZV9jdG9ylJOUjAdNVDE5OTM3lGgQjBRfX2JpdF9nZW5lcmF0b3JfY3RvcpSTlIaUUpR9lCiMDWJpdF9nZW5lcmF0b3KUjAdNVDE5OTM3lIwFc3RhdGWUfZQojANrZXmUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWwAkAAAAAAAAAAACAU8KznIcDtZNy7Ktb6Oay8s+2gdrVBu9hoTFNoGu1zNkT5hifdJx5L8ilG4DEeQFJng9D5F3gGJOSE1XM1EopZNIIlb400J5EcnoD8K2/CnObez7pYLEG2nUDRQtufdYWausENGaDt/P1pS9p70JjQ7Vc98J3UsxGRDctCIlu0I6ud/sYtoBPe575TzLsEti5jl6FqRnKrj12LWcrQoCexe7HH/UiAV1LzyQPzBlSZERXmHCdCvUSF7XpWt47xP9BzzqxX7aH3TPYWImqos1/ez/JlLdsD0MfMZl9G2CQq7cHHRlM3sj7jroA9c+pGt4l/iAGpRb80HbjwU71ykPTAVp531BXrc2qmIU6z9Fh4TAPx7fZ1kVF+L1Irlou+4Ckky7Ys59nB7KkciTI+N5jlb62ybZt0+ZWgIA6LKLvdx/mTQtB4k1aplT/C7L9/ybKCFn2quN/7YlIkxoH1U0xdabG6rgOrR+SHMmvUwvtKB+19Ibb07mSgVQyjNAvnyADPJf3pkxylZtn7f/OVpWEaWfl6BcLwy0grrEgUK+H+8P8XWMuBginXgwzn3sy4+ZOlr45op6TtuqX0Knz/SySGDlBIK8JqKObzB6fGt+ovJHEM8KlL4veKwkLkuuMWBaex3FBdWskry5qhslxMgnk2thh8DaXmAfbuI8j0SqHMW1kleITi9ekfXx/eSi5hX1GjA/M62Zixuay1H8zH9VjsTRcGacyJ0vh1hNReDFoNsXFbLfLqaIvbLDQjY7T289ZXsupvAxu2GVTbqWst+ckPPzwH7vLikULC+weAKwxarqm+ugAXgyz774meHOsvQYuu18nvrrunjZWDvwaKuYohEwUfSnpotE9XhX99yUTc8sGPQidTfXkzm/t8MWP8it4l4VSEgDLn8GW8t2DAh8EwFa/KOGoZEGjYqZ2IMA70E+F2LqgaZlQLFMONTIx3yuN5F2e1MT4v2wdBRK9R+lGMpxIiNldyOwwxLDBTRDMhd7APidmDwQBnvaIecKFa95btwHkRBEUT5g++/I0DDg685EX4OMO2YtTPqM3PQluS4puEhAQRVukNGSh4gYDgcBPKZl4ThNf+G+E7El9fmWJcP39Sifw6Mn+GEisM1RhHY05XZHUv5W4r8kD2jSLMY+IIL2+LtQrW7it7y28+sEicLoEfYOky9ZJF6l0fR+sXEawf+REH9LvtRJ4yzfxr7KisNpr1axv1ae5CDXS+XTzuOG/BJnHvt8arnY1XWH9SdkCOeok6MI8GBCtjTCxJ5JbpI5J0i0A66mJaRW9LMfP6Cil3/cVRQ9uN2KTtV3o7rJwY4XCnj7DJmqrUwofDDl7Ek0PoN7w0Hh8YHOy8qhPw7V8ALdjZn7eYtjCQIldQvHbM1I73RtCLQvQGFMXUCJ022pGRqTvZX5XWSizqbgX6TJmI6LDF9wcpYealB7cDwelfqdpzHRmyjRbIX9b+w4uj//aDRgP2SgiOAq/D/9/0SbgK/E0FQyclhNVAkbKwXhAxKGczpvJow0mFFUAt/5fT5KAsmQTAt8p0FsrGMDTfk4RzZgqZSm+ihVRS371Tx3twpGA1goo/AIfJh8slJC3hkR1OGCN7LAPGCwbM9rHlKSU4uuhJiff196h9q1kPMld6989MfKLVkvCl7ofCRurPUW46ceJKE951sQD1v8cK0HK1JmuBTCXAelCUCIFNLGk3tMXNVmuuFF3o3xb4V4T1IAYIfBdyEVHhIIZOE/JEY79daQw8njYEtQ6YwZ6kNCBYfrjq2OglITcRdwDmINL42ro6HnbWgLZQ8Ce/EiPVBtWHwhvGUHK1FNONzRzXgT1zKEg+WAigeuK4QVIxdITM4YvUyYvpQJuJd+xGD1no7BYIKXdV4aDlsRnWSMmS+zTyTvC0+TgBMCNpMvdChjaB/XTrMVsm0vgPmCYswn067MTYWfm5oCqqmNciqoRfFL2O2mxFT1VMcKDrxHBdBUhSG5UmAerx86KAEytbsCbn6OOj8Y02VwVynzXd0WJfLioeGMZISM1eneWfTc1mQ6CpdDxJqUmU86/KsBL3Bb0S2NAqFysFJZKxDwLej8xz+xH8IxEHzlkiiNH+2IIq0663FAwi6wg6dgcryDqQ+lNDwn898nylrcYShigDrtrFBNezKx3ZjpkPCnPUeQB4hJUrYCUJy5CyytC/x1UsByKez/aSNEWnlWnzYdJf2PoKL0YfmaR3KpXzi9ax3BHPgk1cdmgdVkqevFJ0DUdTBFQj/mhaKqcaT0rKJLgy/11AhWW4nX7+kAdgR0b1iAseI0TbMDtohBuqqUZfqMfUKsdI8v2aeUd0+IqOjPBFe7TZRC7OUYmf789SRTpw9gst4tzx7tLap8JnFt2keKhqd3vBgqpvlsxvx0DcPC+bo/qIldKiAn5D7TPjeWLzJ1gmpk1mVKOyWOv/ZzlRTfe8yEsMsRcgdPxbOuxLjlOwo1uFh9NjHoOz/xbnI62I49ZzT59GUCNtAL74UqjlRoyXZ5ELEjhTn+F5fYfEkY2TnSsgKO4Wwb/xD41S4mBL7LcUyF76ybV7Yx0L6V2QGoSfyhHFqMQJs/haLPPW18mWJb/UDl90ZN9TEzcdXvZsmCeqzCagC6YDHp3fop+5nAQSnT/Byt2j7z+6cnl/aZh6oKs5xrEMmuzpLFbXNVof9hNmX5E0DQ2M8uBqqeW95p6z8ySnOxURAO28oYWsbVyeYaNlWLZrOtIMZDRjjbecSSwMLlrBhw4mZVht4DgOQxI1+P7sPHZLMf89U+5ctf1rD0r1AXgyXjzOxKvCxWMhrz6Ah19+zal/bAIpw+0V7Pq85PRQO4UeScmMwODR8jcOfILuMmo7xXhemY/JqtOncklEaGapMeGlkiefvQkx9L5EWvLn6stI4zRP4pZXx9iOz17IKJmKOVHgCIAOiheb0bwkjNkItlfYO3LzeLLPuBDNLFg7tQu5NPWy28a4nBsE/gsyEteRvF2ECYFIOJg06dzc77IWw7o+z1Q5APxLg9uvyFniYWNuJyk7rflLCmYcg1gN657CWff8YfPr0ukKOamco94X1nFdyroxHiQlRXaP91DOqMueI1pCasyRQt0jtbWwxdEVyzP3GzUZXBWqa0xXCzwe29cxg2aiwKuuAAVfaCE/Pt1cJXq8wvliF81sMDPMbowd9+uyWuExq/e+2W3wWeV3hVofoiEySjBrJPWVJW9++UocJbC0ppNw5mtHktkZqUk6kVtUgVQ4Cj4udj/bluZzcqWjIvOCJO52M+xcQY808Ei8T/lwwS9TguuzQ3e0KR7hptgNcX1/XhCvAuUaAmMAnU0lImIh5RSlChLA2gNTk5OSv////9K/////0sAdJRiTXAChZSMAUOUdJRSlIwDcG9zlE1wAnWMCWhhc19nYXVzc5RLAIwFZ2F1c3OURwAAAAAAAAAAdWJ1Yi4=",
"n": 3,
"_shape": [],
"dtype": "int64",
"_np_random": "RandomState(MT19937)"
},
"n_envs": 1,
"num_timesteps": 500000,
"_total_timesteps": 500000,
"_num_timesteps_at_start": 0,
"seed": 0,
"action_noise": null,
"start_time": 1670923261266675547,
"learning_rate": 0.0007,
"tensorboard_log": "runs/Acrobot-v1__a2c__3084184381__1670923258/Acrobot-v1",
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"_last_obs": null,
"_last_episode_starts": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
},
"_last_original_obs": {
":type:": "<class 'numpy.ndarray'>",
":serialized:": "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"
},
"_episode_num": 0,
"use_sde": false,
"sde_sample_freq": -1,
"_current_progress_remaining": 0.0,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 6250,
"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
} |