{ "name": "root", "gauges": { "Pyramids.Policy.Entropy.mean": { "value": 0.15511548519134521, "min": 0.15511548519134521, "max": 1.4716479778289795, "count": 100 }, "Pyramids.Policy.Entropy.sum": { "value": 4675.80126953125, "min": 4643.11865234375, "max": 44643.9140625, "count": 100 }, "Pyramids.Step.mean": { "value": 2999895.0, "min": 29937.0, "max": 2999895.0, "count": 100 }, "Pyramids.Step.sum": { "value": 2999895.0, "min": 29937.0, "max": 2999895.0, "count": 100 }, "Pyramids.Policy.ExtrinsicValueEstimate.mean": { "value": 0.7782980799674988, "min": -0.15698327124118805, "max": 0.848103404045105, "count": 100 }, "Pyramids.Policy.ExtrinsicValueEstimate.sum": { "value": 229.59793090820312, "min": -37.67598342895508, "max": 260.36773681640625, "count": 100 }, "Pyramids.Policy.RndValueEstimate.mean": { "value": 0.013671457767486572, "min": -0.0007952329469844699, "max": 0.46688979864120483, "count": 100 }, "Pyramids.Policy.RndValueEstimate.sum": { "value": 4.033080101013184, "min": -0.2322080135345459, "max": 111.1197738647461, "count": 100 }, "Pyramids.Losses.PolicyLoss.mean": { "value": 0.07030294589224338, "min": 0.064918372890527, "max": 0.07359794507404635, "count": 100 }, "Pyramids.Losses.PolicyLoss.sum": { "value": 0.9842412424914073, "min": 0.6239968793067233, "max": 1.0878066654338767, "count": 100 }, "Pyramids.Losses.ValueLoss.mean": { "value": 0.015881834198288352, "min": 0.00017079232478792224, "max": 0.01711644900161173, "count": 100 }, "Pyramids.Losses.ValueLoss.sum": { "value": 0.22234567877603692, "min": 0.0023910925470309115, "max": 0.24227163909852284, "count": 100 }, "Pyramids.Policy.LearningRate.mean": { "value": 1.4840852196238058e-06, "min": 1.4840852196238058e-06, "max": 0.00029826734502199633, "count": 100 }, "Pyramids.Policy.LearningRate.sum": { "value": 2.0777193074733282e-05, "min": 2.0777193074733282e-05, "max": 0.004011188262937266, "count": 100 }, "Pyramids.Policy.Epsilon.mean": { "value": 0.10049466190476188, "min": 0.10049466190476188, "max": 0.1994224481481482, "count": 100 }, "Pyramids.Policy.Epsilon.sum": { "value": 1.4069252666666663, "min": 1.4069252666666663, "max": 2.7370627333333335, "count": 100 }, "Pyramids.Policy.Beta.mean": { "value": 5.9416724285714176e-05, "min": 5.9416724285714176e-05, "max": 0.009942302569999999, "count": 100 }, "Pyramids.Policy.Beta.sum": { "value": 0.0008318341399999985, "min": 0.0008318341399999985, "max": 0.13371256705999998, "count": 100 }, "Pyramids.Losses.RNDLoss.mean": { "value": 0.006480519659817219, "min": 0.006480519659817219, "max": 0.40102091431617737, "count": 100 }, "Pyramids.Losses.RNDLoss.sum": { "value": 0.09072727710008621, "min": 0.09072727710008621, "max": 3.6091883182525635, "count": 100 }, "Pyramids.Environment.EpisodeLength.mean": { "value": 223.03649635036496, "min": 204.92857142857142, "max": 999.0, "count": 100 }, "Pyramids.Environment.EpisodeLength.sum": { "value": 30556.0, "min": 16736.0, "max": 32669.0, "count": 100 }, "Pyramids.Environment.CumulativeReward.mean": { "value": 1.7632651988794839, "min": -0.9999871489501768, "max": 1.794964272316013, "count": 100 }, "Pyramids.Environment.CumulativeReward.sum": { "value": 243.33059744536877, "min": -30.999601617455482, "max": 251.29499812424183, "count": 100 }, "Pyramids.Policy.ExtrinsicReward.mean": { "value": 1.7632651988794839, "min": -0.9999871489501768, "max": 1.794964272316013, "count": 100 }, "Pyramids.Policy.ExtrinsicReward.sum": { "value": 243.33059744536877, "min": -30.999601617455482, "max": 251.29499812424183, "count": 100 }, "Pyramids.Policy.RndReward.mean": { "value": 0.015024319115120992, "min": 0.014596954533986076, "max": 7.763516479117029, "count": 100 }, "Pyramids.Policy.RndReward.sum": { "value": 2.073356037886697, "min": 1.979329001579572, "max": 131.9797801449895, "count": 100 }, "Pyramids.IsTraining.mean": { "value": 1.0, "min": 1.0, "max": 1.0, "count": 100 }, "Pyramids.IsTraining.sum": { "value": 1.0, "min": 1.0, "max": 1.0, "count": 100 } }, "metadata": { "timer_format_version": "0.1.0", "start_time_seconds": "1679832002", "python_version": "3.9.16 (main, Dec 7 2022, 01:11:51) \n[GCC 9.4.0]", "command_line_arguments": "/usr/local/bin/mlagents-learn ./config/ppo/PyramidsRND.yaml --env=./training-envs-executables/linux/Pyramids/Pyramids --run-id=Pyramids1 --no-graphics", "mlagents_version": "0.31.0.dev0", "mlagents_envs_version": "0.31.0.dev0", "communication_protocol_version": "1.5.0", "pytorch_version": "1.11.0+cu102", "numpy_version": "1.21.2", "end_time_seconds": "1679843793" }, "total": 11791.167157627999, "count": 1, "self": 0.8452808589991037, "children": { "run_training.setup": { "total": 0.1298563580003247, "count": 1, "self": 0.1298563580003247 }, "TrainerController.start_learning": { "total": 11790.192020411, "count": 1, "self": 7.712836508133478, "children": { "TrainerController._reset_env": { "total": 3.9206680269999197, "count": 1, "self": 3.9206680269999197 }, "TrainerController.advance": { "total": 11778.426079532866, "count": 194747, "self": 8.118636043982406, "children": { "env_step": { "total": 8183.406791162026, "count": 194747, "self": 7741.892572322901, "children": { "SubprocessEnvManager._take_step": { "total": 437.0267408940085, "count": 194747, "self": 22.99007947424161, "children": { "TorchPolicy.evaluate": { "total": 414.0366614197669, "count": 187570, "self": 414.0366614197669 } } }, "workers": { "total": 4.4874779451160975, "count": 194747, "self": 0.0, "children": { "worker_root": { "total": 11764.174782125228, "count": 194747, "is_parallel": true, "self": 4594.58522178731, "children": { "run_training.setup": { "total": 0.0, "count": 0, "is_parallel": true, "self": 0.0, "children": { "steps_from_proto": { "total": 0.0021881799998482165, "count": 1, "is_parallel": true, "self": 0.00063519900004394, "children": { "_process_rank_one_or_two_observation": { "total": 0.0015529809998042765, "count": 8, "is_parallel": true, "self": 0.0015529809998042765 } } }, "UnityEnvironment.step": { "total": 0.06623803399997996, "count": 1, "is_parallel": true, "self": 0.0006612440001845243, "children": { "UnityEnvironment._generate_step_input": { "total": 0.000539293999736401, "count": 1, "is_parallel": true, "self": 0.000539293999736401 }, "communicator.exchange": { "total": 0.06313770500037208, "count": 1, "is_parallel": true, "self": 0.06313770500037208 }, "steps_from_proto": { "total": 0.0018997909996869566, "count": 1, "is_parallel": true, "self": 0.00042171999893980683, "children": { "_process_rank_one_or_two_observation": { "total": 0.0014780710007471498, "count": 8, "is_parallel": true, "self": 0.0014780710007471498 } } } } } } }, "UnityEnvironment.step": { "total": 7169.589560337919, "count": 194746, "is_parallel": true, "self": 136.1175623244908, "children": { "UnityEnvironment._generate_step_input": { "total": 83.57608859527863, "count": 194746, "is_parallel": true, "self": 83.57608859527863 }, "communicator.exchange": { "total": 6551.015613763098, "count": 194746, "is_parallel": true, "self": 6551.015613763098 }, "steps_from_proto": { "total": 398.88029565505076, "count": 194746, "is_parallel": true, "self": 92.14011037233377, "children": { "_process_rank_one_or_two_observation": { "total": 306.740185282717, "count": 1557968, "is_parallel": true, "self": 306.740185282717 } } } } } } } } } } }, "trainer_advance": { "total": 3586.900652326859, "count": 194747, "self": 15.366107405485764, "children": { "process_trajectory": { "total": 510.95675706935253, "count": 194747, "self": 510.14051679435124, "children": { "RLTrainer._checkpoint": { "total": 0.8162402750012916, "count": 6, "self": 0.8162402750012916 } } }, "_update_policy": { "total": 3060.5777878520207, "count": 1404, "self": 1243.9668085360113, "children": { "TorchPPOOptimizer.update": { "total": 1816.6109793160094, "count": 68385, "self": 1816.6109793160094 } } } } } } }, "trainer_threads": { "total": 1.2729997251881287e-06, "count": 1, "self": 1.2729997251881287e-06 }, "TrainerController._save_models": { "total": 0.13243506999970123, "count": 1, "self": 0.003974127999754273, "children": { "RLTrainer._checkpoint": { "total": 0.12846094199994695, "count": 1, "self": 0.12846094199994695 } } } } } } }