morganjeffries's picture
I swear I did this before. Also, this one is garbage because Colab cut off my GPU for the day.
89fcd58
raw
history blame
18.7 kB
{
"name": "root",
"gauges": {
"Pyramids.Policy.Entropy.mean": {
"value": 1.0835151672363281,
"min": 1.0835151672363281,
"max": 1.5257622003555298,
"count": 3
},
"Pyramids.Policy.Entropy.sum": {
"value": 32453.4453125,
"min": 32453.4453125,
"max": 46285.5234375,
"count": 3
},
"Pyramids.Step.mean": {
"value": 89922.0,
"min": 29952.0,
"max": 89922.0,
"count": 3
},
"Pyramids.Step.sum": {
"value": 89922.0,
"min": 29952.0,
"max": 89922.0,
"count": 3
},
"Pyramids.Policy.ExtrinsicValueEstimate.mean": {
"value": -0.08867810666561127,
"min": -0.08867810666561127,
"max": 0.07104282081127167,
"count": 3
},
"Pyramids.Policy.ExtrinsicValueEstimate.sum": {
"value": -21.282745361328125,
"min": -21.282745361328125,
"max": 16.837148666381836,
"count": 3
},
"Pyramids.Policy.RndValueEstimate.mean": {
"value": 0.1582680195569992,
"min": 0.1582680195569992,
"max": 0.4405379891395569,
"count": 3
},
"Pyramids.Policy.RndValueEstimate.sum": {
"value": 37.98432540893555,
"min": 37.98432540893555,
"max": 104.40750122070312,
"count": 3
},
"Pyramids.Losses.PolicyLoss.mean": {
"value": 0.06670783374719283,
"min": 0.06670783374719283,
"max": 0.0724487753318865,
"count": 3
},
"Pyramids.Losses.PolicyLoss.sum": {
"value": 0.6003705037247354,
"min": 0.5071414273232054,
"max": 0.6307520627593446,
"count": 3
},
"Pyramids.Losses.ValueLoss.mean": {
"value": 0.00027809637314151506,
"min": 0.00027809637314151506,
"max": 0.010961821917419734,
"count": 3
},
"Pyramids.Losses.ValueLoss.sum": {
"value": 0.0025028673582736354,
"min": 0.0025028673582736354,
"max": 0.07673275342193814,
"count": 3
},
"Pyramids.Policy.LearningRate.mean": {
"value": 7.48634083788889e-05,
"min": 7.48634083788889e-05,
"max": 0.0002515063018788571,
"count": 3
},
"Pyramids.Policy.LearningRate.sum": {
"value": 0.00067377067541,
"min": 0.00067377067541,
"max": 0.0017605441131519997,
"count": 3
},
"Pyramids.Policy.Epsilon.mean": {
"value": 0.12495444444444447,
"min": 0.12495444444444447,
"max": 0.1838354285714286,
"count": 3
},
"Pyramids.Policy.Epsilon.sum": {
"value": 1.1245900000000002,
"min": 1.1245900000000002,
"max": 1.3844619999999999,
"count": 3
},
"Pyramids.Policy.Beta.mean": {
"value": 0.002502949,
"min": 0.002502949,
"max": 0.008385159314285713,
"count": 3
},
"Pyramids.Policy.Beta.sum": {
"value": 0.022526541,
"min": 0.022526541,
"max": 0.058696115199999996,
"count": 3
},
"Pyramids.Losses.RNDLoss.mean": {
"value": 0.10466020554304123,
"min": 0.10466020554304123,
"max": 0.4057938754558563,
"count": 3
},
"Pyramids.Losses.RNDLoss.sum": {
"value": 0.9419418573379517,
"min": 0.9419418573379517,
"max": 2.840557098388672,
"count": 3
},
"Pyramids.Environment.EpisodeLength.mean": {
"value": 999.0,
"min": 997.0625,
"max": 999.0,
"count": 3
},
"Pyramids.Environment.EpisodeLength.sum": {
"value": 31968.0,
"min": 15984.0,
"max": 31968.0,
"count": 3
},
"Pyramids.Environment.CumulativeReward.mean": {
"value": -0.999987552408129,
"min": -1.0000000521540642,
"max": -0.9355313021223992,
"count": 3
},
"Pyramids.Environment.CumulativeReward.sum": {
"value": -31.999601677060127,
"min": -31.999601677060127,
"max": -16.000000834465027,
"count": 3
},
"Pyramids.Policy.ExtrinsicReward.mean": {
"value": -0.999987552408129,
"min": -1.0000000521540642,
"max": -0.9355313021223992,
"count": 3
},
"Pyramids.Policy.ExtrinsicReward.sum": {
"value": -31.999601677060127,
"min": -31.999601677060127,
"max": -16.000000834465027,
"count": 3
},
"Pyramids.Policy.RndReward.mean": {
"value": 1.244899629149586,
"min": 1.244899629149586,
"max": 8.592460774816573,
"count": 3
},
"Pyramids.Policy.RndReward.sum": {
"value": 39.83678813278675,
"min": 39.83678813278675,
"max": 137.47937239706516,
"count": 3
},
"Pyramids.IsTraining.mean": {
"value": 1.0,
"min": 1.0,
"max": 1.0,
"count": 3
},
"Pyramids.IsTraining.sum": {
"value": 1.0,
"min": 1.0,
"max": 1.0,
"count": 3
}
},
"metadata": {
"timer_format_version": "0.1.0",
"start_time_seconds": "1676841282",
"python_version": "3.8.10 (default, Nov 14 2022, 12:59:47) \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=Pyramids Training --no-graphics",
"mlagents_version": "0.29.0.dev0",
"mlagents_envs_version": "0.29.0.dev0",
"communication_protocol_version": "1.5.0",
"pytorch_version": "1.8.1+cu102",
"numpy_version": "1.21.6",
"end_time_seconds": "1676841611"
},
"total": 329.59086154199997,
"count": 1,
"self": 1.119241076000094,
"children": {
"run_training.setup": {
"total": 0.16447067899991907,
"count": 1,
"self": 0.16447067899991907
},
"TrainerController.start_learning": {
"total": 328.30714978699996,
"count": 1,
"self": 0.21547677499313522,
"children": {
"TrainerController._reset_env": {
"total": 10.110676624000007,
"count": 1,
"self": 10.110676624000007
},
"TrainerController.advance": {
"total": 317.7982026450069,
"count": 6265,
"self": 0.2609329820045332,
"children": {
"env_step": {
"total": 183.20002682699226,
"count": 6265,
"self": 167.57378283698642,
"children": {
"SubprocessEnvManager._take_step": {
"total": 15.480605588003414,
"count": 6265,
"self": 0.7204715160031583,
"children": {
"TorchPolicy.evaluate": {
"total": 14.760134072000255,
"count": 6260,
"self": 3.161190493001641,
"children": {
"TorchPolicy.sample_actions": {
"total": 11.598943578998615,
"count": 6260,
"self": 11.598943578998615
}
}
}
}
},
"workers": {
"total": 0.14563840200241884,
"count": 6265,
"self": 0.0,
"children": {
"worker_root": {
"total": 327.6130189869941,
"count": 6265,
"is_parallel": true,
"self": 177.08064803098944,
"children": {
"run_training.setup": {
"total": 0.0,
"count": 0,
"is_parallel": true,
"self": 0.0,
"children": {
"steps_from_proto": {
"total": 0.011128786999961449,
"count": 1,
"is_parallel": true,
"self": 0.006503035999912754,
"children": {
"_process_rank_one_or_two_observation": {
"total": 0.0046257510000486946,
"count": 8,
"is_parallel": true,
"self": 0.0046257510000486946
}
}
},
"UnityEnvironment.step": {
"total": 0.06914055199990798,
"count": 1,
"is_parallel": true,
"self": 0.0006731079998871792,
"children": {
"UnityEnvironment._generate_step_input": {
"total": 0.0007300669999494858,
"count": 1,
"is_parallel": true,
"self": 0.0007300669999494858
},
"communicator.exchange": {
"total": 0.06517923800004155,
"count": 1,
"is_parallel": true,
"self": 0.06517923800004155
},
"steps_from_proto": {
"total": 0.002558139000029769,
"count": 1,
"is_parallel": true,
"self": 0.0007207170001493068,
"children": {
"_process_rank_one_or_two_observation": {
"total": 0.001837421999880462,
"count": 8,
"is_parallel": true,
"self": 0.001837421999880462
}
}
}
}
}
}
},
"UnityEnvironment.step": {
"total": 150.53237095600468,
"count": 6264,
"is_parallel": true,
"self": 4.607567904012171,
"children": {
"UnityEnvironment._generate_step_input": {
"total": 2.605182551003054,
"count": 6264,
"is_parallel": true,
"self": 2.605182551003054
},
"communicator.exchange": {
"total": 130.09750493099386,
"count": 6264,
"is_parallel": true,
"self": 130.09750493099386
},
"steps_from_proto": {
"total": 13.222115569995594,
"count": 6264,
"is_parallel": true,
"self": 3.22646498199947,
"children": {
"_process_rank_one_or_two_observation": {
"total": 9.995650587996124,
"count": 50112,
"is_parallel": true,
"self": 9.995650587996124
}
}
}
}
}
}
}
}
}
}
},
"trainer_advance": {
"total": 134.3372428360101,
"count": 6265,
"self": 0.30902015800711524,
"children": {
"process_trajectory": {
"total": 22.619742652002856,
"count": 6265,
"self": 22.619742652002856
},
"_update_policy": {
"total": 111.40848002600012,
"count": 29,
"self": 28.880597093998063,
"children": {
"TorchPPOOptimizer.update": {
"total": 82.52788293200206,
"count": 2292,
"self": 82.52788293200206
}
}
}
}
}
}
},
"trainer_threads": {
"total": 1.991999965866853e-06,
"count": 1,
"self": 1.991999965866853e-06
},
"TrainerController._save_models": {
"total": 0.18279175099996792,
"count": 1,
"self": 0.002382371999942734,
"children": {
"RLTrainer._checkpoint": {
"total": 0.18040937900002518,
"count": 1,
"self": 0.18040937900002518
}
}
}
}
}
}
}