ppo-Pyramids / run_logs /timers.json
Adi-AI-2005's picture
First Push for Pyramids Training
2f5560c verified
{
"name": "root",
"gauges": {
"Pyramids.Policy.Entropy.mean": {
"value": 0.8218531012535095,
"min": 0.8218531012535095,
"max": 1.4017139673233032,
"count": 16
},
"Pyramids.Policy.Entropy.sum": {
"value": 24787.08984375,
"min": 22427.423828125,
"max": 38343.68359375,
"count": 16
},
"Pyramids.Step.mean": {
"value": 479892.0,
"min": 29983.0,
"max": 479892.0,
"count": 16
},
"Pyramids.Step.sum": {
"value": 479892.0,
"min": 29983.0,
"max": 479892.0,
"count": 16
},
"Pyramids.Policy.ExtrinsicValueEstimate.mean": {
"value": 0.16719870269298553,
"min": -0.09453507512807846,
"max": 0.18006311357021332,
"count": 16
},
"Pyramids.Policy.ExtrinsicValueEstimate.sum": {
"value": 41.79967498779297,
"min": -22.499347686767578,
"max": 45.19584274291992,
"count": 16
},
"Pyramids.Policy.RndValueEstimate.mean": {
"value": 0.04031394422054291,
"min": 0.008605342358350754,
"max": 0.4116668403148651,
"count": 16
},
"Pyramids.Policy.RndValueEstimate.sum": {
"value": 10.078486442565918,
"min": 2.1169142723083496,
"max": 66.13185119628906,
"count": 16
},
"Pyramids.Losses.PolicyLoss.mean": {
"value": 0.07071494894710777,
"min": 0.06409087616463414,
"max": 0.07432501029365489,
"count": 16
},
"Pyramids.Losses.PolicyLoss.sum": {
"value": 0.9900092852595088,
"min": 0.22297503088096465,
"max": 1.0283716070727107,
"count": 16
},
"Pyramids.Losses.ValueLoss.mean": {
"value": 0.01113278306284984,
"min": 0.0015895596431628114,
"max": 0.01113278306284984,
"count": 16
},
"Pyramids.Losses.ValueLoss.sum": {
"value": 0.15585896287989776,
"min": 0.008619954277795236,
"max": 0.15585896287989776,
"count": 16
},
"Pyramids.Policy.LearningRate.mean": {
"value": 2.0581250282471426e-05,
"min": 2.0581250282471426e-05,
"max": 0.0002865078044974,
"count": 16
},
"Pyramids.Policy.LearningRate.sum": {
"value": 0.00028813750395459994,
"min": 0.00028813750395459994,
"max": 0.0028506831497724003,
"count": 16
},
"Pyramids.Policy.Epsilon.mean": {
"value": 0.10686038571428572,
"min": 0.10686038571428572,
"max": 0.1955026,
"count": 16
},
"Pyramids.Policy.Epsilon.sum": {
"value": 1.4960454,
"min": 0.5865078,
"max": 2.3381796,
"count": 16
},
"Pyramids.Policy.Beta.mean": {
"value": 0.0006953525328571428,
"min": 0.0006953525328571428,
"max": 0.009550709740000001,
"count": 16
},
"Pyramids.Policy.Beta.sum": {
"value": 0.00973493546,
"min": 0.00973493546,
"max": 0.09505773724000002,
"count": 16
},
"Pyramids.Losses.RNDLoss.mean": {
"value": 0.016086162999272346,
"min": 0.015609530732035637,
"max": 0.23164601624011993,
"count": 16
},
"Pyramids.Losses.RNDLoss.sum": {
"value": 0.22520627081394196,
"min": 0.21853342652320862,
"max": 1.1311066150665283,
"count": 16
},
"Pyramids.Environment.EpisodeLength.mean": {
"value": 658.0909090909091,
"min": 656.1777777777778,
"max": 999.0,
"count": 16
},
"Pyramids.Environment.EpisodeLength.sum": {
"value": 28956.0,
"min": 15984.0,
"max": 32536.0,
"count": 16
},
"Pyramids.Environment.CumulativeReward.mean": {
"value": 0.7508090504191138,
"min": -1.0000000521540642,
"max": 0.7508090504191138,
"count": 16
},
"Pyramids.Environment.CumulativeReward.sum": {
"value": 33.03559821844101,
"min": -26.086401507258415,
"max": 33.03559821844101,
"count": 16
},
"Pyramids.Policy.ExtrinsicReward.mean": {
"value": 0.7508090504191138,
"min": -1.0000000521540642,
"max": 0.7508090504191138,
"count": 16
},
"Pyramids.Policy.ExtrinsicReward.sum": {
"value": 33.03559821844101,
"min": -26.086401507258415,
"max": 33.03559821844101,
"count": 16
},
"Pyramids.Policy.RndReward.mean": {
"value": 0.1074948328314349,
"min": 0.10620525570638063,
"max": 2.8118732445515118,
"count": 16
},
"Pyramids.Policy.RndReward.sum": {
"value": 4.729772644583136,
"min": 4.729772644583136,
"max": 36.554352179169655,
"count": 16
},
"Pyramids.IsTraining.mean": {
"value": 1.0,
"min": 1.0,
"max": 1.0,
"count": 16
},
"Pyramids.IsTraining.sum": {
"value": 1.0,
"min": 1.0,
"max": 1.0,
"count": 16
}
},
"metadata": {
"timer_format_version": "0.1.0",
"start_time_seconds": "1736783484",
"python_version": "3.10.12 (main, Nov 6 2024, 20:22:13) [GCC 11.4.0]",
"command_line_arguments": "/usr/local/bin/mlagents-learn ./config/ppo/PyramidsRND.yaml --env=./training-envs-executables/linux/Pyramids/Pyramids --run-id=Pyramids Training --no-graphics --resume",
"mlagents_version": "1.2.0.dev0",
"mlagents_envs_version": "1.2.0.dev0",
"communication_protocol_version": "1.5.0",
"pytorch_version": "2.5.1+cu121",
"numpy_version": "1.23.5",
"end_time_seconds": "1736784508"
},
"total": 1024.626133001,
"count": 1,
"self": 0.4771244139999453,
"children": {
"run_training.setup": {
"total": 0.05486030099996242,
"count": 1,
"self": 0.05486030099996242
},
"TrainerController.start_learning": {
"total": 1024.094148286,
"count": 1,
"self": 0.6168152419968465,
"children": {
"TrainerController._reset_env": {
"total": 2.1712185540000064,
"count": 1,
"self": 2.1712185540000064
},
"TrainerController.advance": {
"total": 1021.2239919380033,
"count": 30786,
"self": 0.6336862899715925,
"children": {
"env_step": {
"total": 695.8379171090241,
"count": 30786,
"self": 625.2730052410059,
"children": {
"SubprocessEnvManager._take_step": {
"total": 70.18478575300469,
"count": 30786,
"self": 2.1632423169855883,
"children": {
"TorchPolicy.evaluate": {
"total": 68.0215434360191,
"count": 30436,
"self": 68.0215434360191
}
}
},
"workers": {
"total": 0.3801261150135815,
"count": 30786,
"self": 0.0,
"children": {
"worker_root": {
"total": 1021.860913875991,
"count": 30786,
"is_parallel": true,
"self": 451.09090727198486,
"children": {
"run_training.setup": {
"total": 0.0,
"count": 0,
"is_parallel": true,
"self": 0.0,
"children": {
"steps_from_proto": {
"total": 0.00209486099993228,
"count": 1,
"is_parallel": true,
"self": 0.0006973370000196155,
"children": {
"_process_rank_one_or_two_observation": {
"total": 0.0013975239999126643,
"count": 8,
"is_parallel": true,
"self": 0.0013975239999126643
}
}
},
"UnityEnvironment.step": {
"total": 0.0452558769998177,
"count": 1,
"is_parallel": true,
"self": 0.0005682189998879039,
"children": {
"UnityEnvironment._generate_step_input": {
"total": 0.0004359550000572199,
"count": 1,
"is_parallel": true,
"self": 0.0004359550000572199
},
"communicator.exchange": {
"total": 0.04256188099998326,
"count": 1,
"is_parallel": true,
"self": 0.04256188099998326
},
"steps_from_proto": {
"total": 0.0016898219998893182,
"count": 1,
"is_parallel": true,
"self": 0.0003678539997054031,
"children": {
"_process_rank_one_or_two_observation": {
"total": 0.0013219680001839151,
"count": 8,
"is_parallel": true,
"self": 0.0013219680001839151
}
}
}
}
}
}
},
"UnityEnvironment.step": {
"total": 570.7700066040061,
"count": 30785,
"is_parallel": true,
"self": 15.56219973903876,
"children": {
"UnityEnvironment._generate_step_input": {
"total": 11.16187519201435,
"count": 30785,
"is_parallel": true,
"self": 11.16187519201435
},
"communicator.exchange": {
"total": 497.36558166495774,
"count": 30785,
"is_parallel": true,
"self": 497.36558166495774
},
"steps_from_proto": {
"total": 46.68035000799523,
"count": 30785,
"is_parallel": true,
"self": 9.347248153031842,
"children": {
"_process_rank_one_or_two_observation": {
"total": 37.33310185496339,
"count": 246280,
"is_parallel": true,
"self": 37.33310185496339
}
}
}
}
}
}
}
}
}
}
},
"trainer_advance": {
"total": 324.7523885390076,
"count": 30786,
"self": 1.1181802269559284,
"children": {
"process_trajectory": {
"total": 62.56286166304949,
"count": 30786,
"self": 62.44559191104986,
"children": {
"RLTrainer._checkpoint": {
"total": 0.11726975199962908,
"count": 1,
"self": 0.11726975199962908
}
}
},
"_update_policy": {
"total": 261.0713466490022,
"count": 210,
"self": 147.64122675499607,
"children": {
"TorchPPOOptimizer.update": {
"total": 113.43011989400611,
"count": 11070,
"self": 113.43011989400611
}
}
}
}
}
}
},
"trainer_threads": {
"total": 9.169998520519584e-07,
"count": 1,
"self": 9.169998520519584e-07
},
"TrainerController._save_models": {
"total": 0.08212163500002134,
"count": 1,
"self": 0.0020013969997307868,
"children": {
"RLTrainer._checkpoint": {
"total": 0.08012023800029056,
"count": 1,
"self": 0.08012023800029056
}
}
}
}
}
}
}