pyramid / run_logs /timers.json
annguyen2004's picture
First Commit
0922677 verified
{
"name": "root",
"gauges": {
"Pyramids.Policy.Entropy.mean": {
"value": 0.47395145893096924,
"min": 0.43914881348609924,
"max": 1.5772427320480347,
"count": 30
},
"Pyramids.Policy.Entropy.sum": {
"value": 23788.572265625,
"min": 22133.099609375,
"max": 82168.0390625,
"count": 30
},
"Pyramids.Step.mean": {
"value": 1499894.0,
"min": 49792.0,
"max": 1499894.0,
"count": 30
},
"Pyramids.Step.sum": {
"value": 1499894.0,
"min": 49792.0,
"max": 1499894.0,
"count": 30
},
"Pyramids.Policy.ExtrinsicValueEstimate.mean": {
"value": 0.7238889336585999,
"min": -0.08758947253227234,
"max": 0.7238889336585999,
"count": 30
},
"Pyramids.Policy.ExtrinsicValueEstimate.sum": {
"value": 201.24111938476562,
"min": -17.605484008789062,
"max": 209.07135009765625,
"count": 30
},
"Pyramids.Policy.RndValueEstimate.mean": {
"value": 0.039022047072649,
"min": 0.039022047072649,
"max": 1.0661793947219849,
"count": 30
},
"Pyramids.Policy.RndValueEstimate.sum": {
"value": 10.848129272460938,
"min": 10.848129272460938,
"max": 213.2358856201172,
"count": 30
},
"Pyramids.Losses.PolicyLoss.mean": {
"value": 0.05059290239053856,
"min": 0.04804883606993826,
"max": 0.05429279381665317,
"count": 30
},
"Pyramids.Losses.PolicyLoss.sum": {
"value": 0.30355741434323136,
"min": 0.20743013373082606,
"max": 0.32058311826040153,
"count": 30
},
"Pyramids.Losses.ValueLoss.mean": {
"value": 0.013280400857790179,
"min": 0.00047992524293536206,
"max": 0.04562955859006067,
"count": 30
},
"Pyramids.Losses.ValueLoss.sum": {
"value": 0.07968240514674108,
"min": 0.0019197009717414483,
"max": 0.18251823436024267,
"count": 30
},
"Pyramids.Policy.LearningRate.mean": {
"value": 0.00010172208247231668,
"min": 0.00010172208247231668,
"max": 0.0001979904010048,
"count": 30
},
"Pyramids.Policy.LearningRate.sum": {
"value": 0.0006103324948339001,
"min": 0.0006103324948339001,
"max": 0.0011089415121959332,
"count": 30
},
"Pyramids.Policy.Epsilon.mean": {
"value": 0.12543050833333336,
"min": 0.12543050833333336,
"max": 0.14949759999999998,
"count": 30
},
"Pyramids.Policy.Epsilon.sum": {
"value": 0.7525830500000001,
"min": 0.5915904,
"max": 0.8772353666666668,
"count": 30
},
"Pyramids.Policy.Beta.mean": {
"value": 0.0025479647316666667,
"min": 0.0025479647316666667,
"max": 0.00494986048,
"count": 30
},
"Pyramids.Policy.Beta.sum": {
"value": 0.015287788390000001,
"min": 0.015287788390000001,
"max": 0.027728089593333335,
"count": 30
},
"Pyramids.Losses.RNDLoss.mean": {
"value": 0.022282997146248817,
"min": 0.022282997146248817,
"max": 0.692805290222168,
"count": 30
},
"Pyramids.Losses.RNDLoss.sum": {
"value": 0.1336979866027832,
"min": 0.1336979866027832,
"max": 2.771221160888672,
"count": 30
},
"Pyramids.Environment.EpisodeLength.mean": {
"value": 278.3,
"min": 253.3451776649746,
"max": 999.0,
"count": 30
},
"Pyramids.Environment.EpisodeLength.sum": {
"value": 50094.0,
"min": 47121.0,
"max": 53748.0,
"count": 30
},
"Pyramids.Environment.CumulativeReward.mean": {
"value": 1.6661210844914118,
"min": -1.0000000596046448,
"max": 1.7369999766650825,
"count": 30
},
"Pyramids.Environment.CumulativeReward.sum": {
"value": 299.90179520845413,
"min": -48.00000286102295,
"max": 343.92599537968636,
"count": 30
},
"Pyramids.Policy.ExtrinsicReward.mean": {
"value": 1.6661210844914118,
"min": -1.0000000596046448,
"max": 1.7369999766650825,
"count": 30
},
"Pyramids.Policy.ExtrinsicReward.sum": {
"value": 299.90179520845413,
"min": -48.00000286102295,
"max": 343.92599537968636,
"count": 30
},
"Pyramids.Policy.RndReward.mean": {
"value": 0.1269037943727906,
"min": 0.12021264313270968,
"max": 25.533917946120102,
"count": 30
},
"Pyramids.Policy.RndReward.sum": {
"value": 22.842682987102307,
"min": 22.842682987102307,
"max": 1225.628061413765,
"count": 30
},
"Pyramids.IsTraining.mean": {
"value": 1.0,
"min": 1.0,
"max": 1.0,
"count": 30
},
"Pyramids.IsTraining.sum": {
"value": 1.0,
"min": 1.0,
"max": 1.0,
"count": 30
}
},
"metadata": {
"timer_format_version": "0.1.0",
"start_time_seconds": "1739010197",
"python_version": "3.10.12 (main, Jul 5 2023, 18:54:27) [GCC 11.2.0]",
"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": "1.2.0.dev0",
"mlagents_envs_version": "1.2.0.dev0",
"communication_protocol_version": "1.5.0",
"pytorch_version": "2.6.0+cu124",
"numpy_version": "1.23.5",
"end_time_seconds": "1739014540"
},
"total": 4343.211638579,
"count": 1,
"self": 0.49571552599900315,
"children": {
"run_training.setup": {
"total": 0.02509687600002053,
"count": 1,
"self": 0.02509687600002053
},
"TrainerController.start_learning": {
"total": 4342.690826177,
"count": 1,
"self": 3.0422231159973308,
"children": {
"TrainerController._reset_env": {
"total": 3.5475151840000194,
"count": 1,
"self": 3.5475151840000194
},
"TrainerController.advance": {
"total": 4336.100126945003,
"count": 97085,
"self": 3.116563392974058,
"children": {
"env_step": {
"total": 3123.495565339006,
"count": 97085,
"self": 2759.640346882132,
"children": {
"SubprocessEnvManager._take_step": {
"total": 362.02454823896977,
"count": 97085,
"self": 8.998269734995972,
"children": {
"TorchPolicy.evaluate": {
"total": 353.0262785039738,
"count": 94211,
"self": 353.0262785039738
}
}
},
"workers": {
"total": 1.8306702179044123,
"count": 97084,
"self": 0.0,
"children": {
"worker_root": {
"total": 4332.975875222022,
"count": 97084,
"is_parallel": true,
"self": 1798.5675234819855,
"children": {
"run_training.setup": {
"total": 0.0,
"count": 0,
"is_parallel": true,
"self": 0.0,
"children": {
"steps_from_proto": {
"total": 0.00626531799997565,
"count": 1,
"is_parallel": true,
"self": 0.004769854999835843,
"children": {
"_process_rank_one_or_two_observation": {
"total": 0.0014954630001398073,
"count": 8,
"is_parallel": true,
"self": 0.0014954630001398073
}
}
},
"UnityEnvironment.step": {
"total": 0.05627556700000014,
"count": 1,
"is_parallel": true,
"self": 0.000609010000005128,
"children": {
"UnityEnvironment._generate_step_input": {
"total": 0.000536020999959419,
"count": 1,
"is_parallel": true,
"self": 0.000536020999959419
},
"communicator.exchange": {
"total": 0.05290789800000084,
"count": 1,
"is_parallel": true,
"self": 0.05290789800000084
},
"steps_from_proto": {
"total": 0.002222638000034749,
"count": 1,
"is_parallel": true,
"self": 0.0005434350001110033,
"children": {
"_process_rank_one_or_two_observation": {
"total": 0.0016792029999237457,
"count": 8,
"is_parallel": true,
"self": 0.0016792029999237457
}
}
}
}
}
}
},
"UnityEnvironment.step": {
"total": 2534.408351740037,
"count": 97083,
"is_parallel": true,
"self": 57.82328162607564,
"children": {
"UnityEnvironment._generate_step_input": {
"total": 40.073639955927035,
"count": 97083,
"is_parallel": true,
"self": 40.073639955927035
},
"communicator.exchange": {
"total": 2263.384976569948,
"count": 97083,
"is_parallel": true,
"self": 2263.384976569948
},
"steps_from_proto": {
"total": 173.12645358808652,
"count": 97083,
"is_parallel": true,
"self": 37.581869337396995,
"children": {
"_process_rank_one_or_two_observation": {
"total": 135.54458425068952,
"count": 776664,
"is_parallel": true,
"self": 135.54458425068952
}
}
}
}
}
}
}
}
}
}
},
"trainer_advance": {
"total": 1209.4879982130228,
"count": 97084,
"self": 6.136099132024356,
"children": {
"process_trajectory": {
"total": 235.83143179800277,
"count": 97084,
"self": 234.3824229140023,
"children": {
"RLTrainer._checkpoint": {
"total": 1.4490088840004773,
"count": 3,
"self": 1.4490088840004773
}
}
},
"_update_policy": {
"total": 967.5204672829958,
"count": 174,
"self": 587.5277926609949,
"children": {
"TorchPPOOptimizer.update": {
"total": 379.99267462200095,
"count": 23180,
"self": 379.99267462200095
}
}
}
}
}
}
},
"trainer_threads": {
"total": 1.6439998944406398e-06,
"count": 1,
"self": 1.6439998944406398e-06
},
"TrainerController._save_models": {
"total": 0.0009592880005584448,
"count": 1,
"self": 4.0442000681650825e-05,
"children": {
"RLTrainer._checkpoint": {
"total": 0.0009188459998767939,
"count": 1,
"self": 0.0009188459998767939
}
}
}
}
}
}
}