{ "name": "root", "gauges": { "Pyramids.Policy.Entropy.mean": { "value": 0.07561375200748444, "min": 0.07561375200748444, "max": 1.4175474643707275, "count": 333 }, "Pyramids.Policy.Entropy.sum": { "value": 2290.189208984375, "min": 2277.609375, "max": 43002.71875, "count": 333 }, "Pyramids.Step.mean": { "value": 9989990.0, "min": 29952.0, "max": 9989990.0, "count": 333 }, "Pyramids.Step.sum": { "value": 9989990.0, "min": 29952.0, "max": 9989990.0, "count": 333 }, "Pyramids.Policy.ExtrinsicValueEstimate.mean": { "value": 0.8543348908424377, "min": -0.09571170061826706, "max": 1.001431941986084, "count": 333 }, "Pyramids.Policy.ExtrinsicValueEstimate.sum": { "value": 266.552490234375, "min": -22.683673858642578, "max": 321.45965576171875, "count": 333 }, "Pyramids.Policy.RndValueEstimate.mean": { "value": 0.0060005029663443565, "min": -0.05893249437212944, "max": 0.39971691370010376, "count": 333 }, "Pyramids.Policy.RndValueEstimate.sum": { "value": 1.8721568584442139, "min": -16.913625717163086, "max": 94.73291015625, "count": 333 }, "Pyramids.Losses.PolicyLoss.mean": { "value": 0.06753605802200084, "min": 0.06181583571120907, "max": 0.07418865210020933, "count": 333 }, "Pyramids.Losses.PolicyLoss.sum": { "value": 0.9455048123080119, "min": 0.5193205647014654, "max": 1.102130610325748, "count": 333 }, "Pyramids.Losses.ValueLoss.mean": { "value": 0.016244731489171115, "min": 0.001776320314338212, "max": 0.01687595542713169, "count": 333 }, "Pyramids.Losses.ValueLoss.sum": { "value": 0.22742624084839563, "min": 0.021315843772058543, "max": 0.24031729904555843, "count": 333 }, "Pyramids.Policy.LearningRate.mean": { "value": 7.573447475850008e-07, "min": 7.573447475850008e-07, "max": 0.0002995150630187886, "count": 333 }, "Pyramids.Policy.LearningRate.sum": { "value": 1.0602826466190011e-05, "min": 1.0602826466190011e-05, "max": 0.0043448526517158, "count": 333 }, "Pyramids.Policy.Epsilon.mean": { "value": 0.100252415, "min": 0.100252415, "max": 0.1998383542857143, "count": 333 }, "Pyramids.Policy.Epsilon.sum": { "value": 1.4035338099999999, "min": 1.3988684800000002, "max": 2.9482842, "count": 333 }, "Pyramids.Policy.Beta.mean": { "value": 3.521625850000003e-05, "min": 3.521625850000003e-05, "max": 0.009983851593142858, "count": 333 }, "Pyramids.Policy.Beta.sum": { "value": 0.0004930276190000004, "min": 0.0004930276190000004, "max": 0.14483359158000003, "count": 333 }, "Pyramids.Losses.RNDLoss.mean": { "value": 0.004874624777585268, "min": 0.004479951225221157, "max": 0.4924687445163727, "count": 333 }, "Pyramids.Losses.RNDLoss.sum": { "value": 0.06824474781751633, "min": 0.06451395899057388, "max": 3.4472811222076416, "count": 333 }, "Pyramids.Environment.EpisodeLength.mean": { "value": 188.7391304347826, "min": 170.9467455621302, "max": 999.0, "count": 333 }, "Pyramids.Environment.EpisodeLength.sum": { "value": 30387.0, "min": 15984.0, "max": 32841.0, "count": 333 }, "Pyramids.Environment.CumulativeReward.mean": { "value": 1.7615540238178296, "min": -1.0000000521540642, "max": 1.8290532443826721, "count": 333 }, "Pyramids.Environment.CumulativeReward.sum": { "value": 283.61019783467054, "min": -28.230001620948315, "max": 317.45419831573963, "count": 333 }, "Pyramids.Policy.ExtrinsicReward.mean": { "value": 1.7615540238178296, "min": -1.0000000521540642, "max": 1.8290532443826721, "count": 333 }, "Pyramids.Policy.ExtrinsicReward.sum": { "value": 283.61019783467054, "min": -28.230001620948315, "max": 317.45419831573963, "count": 333 }, "Pyramids.Policy.RndReward.mean": { "value": 0.009537448053684242, "min": 0.00889705627450894, "max": 9.711620643734932, "count": 333 }, "Pyramids.Policy.RndReward.sum": { "value": 1.535529136643163, "min": 1.293063686684036, "max": 155.3859302997589, "count": 333 }, "Pyramids.IsTraining.mean": { "value": 1.0, "min": 1.0, "max": 1.0, "count": 333 }, "Pyramids.IsTraining.sum": { "value": 1.0, "min": 1.0, "max": 1.0, "count": 333 } }, "metadata": { "timer_format_version": "0.1.0", "start_time_seconds": "1777833496", "python_version": "3.10.19 (main, May 3 2026, 16:56:55) [GCC 15.2.1 20260209]", "command_line_arguments": "/home/lyra/.venvs/mlagents-env/bin/mlagents-learn ./config/ppo/PyramidsRND.yaml --env=./training-envs-executables/linux/Pyramids/Pyramids --run-id=Pyramids Training 3 --no-graphics", "mlagents_version": "1.2.0.dev0", "mlagents_envs_version": "1.2.0.dev0", "communication_protocol_version": "1.5.0", "pytorch_version": "2.8.0+cu128", "numpy_version": "1.23.5", "end_time_seconds": "1777840569" }, "total": 7073.488069977, "count": 1, "self": 0.2192988750175573, "children": { "run_training.setup": { "total": 0.014218403986888006, "count": 1, "self": 0.014218403986888006 }, "TrainerController.start_learning": { "total": 7073.254552697996, "count": 1, "self": 5.098532143427292, "children": { "TrainerController._reset_env": { "total": 1.2851067570154555, "count": 1, "self": 1.2851067570154555 }, "TrainerController.advance": { "total": 7066.834196417563, "count": 659781, "self": 5.049942689278396, "children": { "env_step": { "total": 4363.827563082683, "count": 659781, "self": 3845.6388522846974, "children": { "SubprocessEnvManager._take_step": { "total": 514.9294849102444, "count": 659781, "self": 17.37210873494041, "children": { "TorchPolicy.evaluate": { "total": 497.55737617530394, "count": 625071, "self": 497.55737617530394 } } }, "workers": { "total": 3.259225887741195, "count": 659781, "self": 0.0, "children": { "worker_root": { "total": 7064.612573969818, "count": 659781, "is_parallel": true, "self": 3585.5642767888203, "children": { "run_training.setup": { "total": 0.0, "count": 0, "is_parallel": true, "self": 0.0, "children": { "steps_from_proto": { "total": 0.0010457699827384204, "count": 1, "is_parallel": true, "self": 0.0003072059771511704, "children": { "_process_rank_one_or_two_observation": { "total": 0.00073856400558725, "count": 8, "is_parallel": true, "self": 0.00073856400558725 } } }, "UnityEnvironment.step": { "total": 0.014706980990013108, "count": 1, "is_parallel": true, "self": 0.0001484189706388861, "children": { "UnityEnvironment._generate_step_input": { "total": 0.00017089801258407533, "count": 1, "is_parallel": true, "self": 0.00017089801258407533 }, "communicator.exchange": { "total": 0.013944778009317815, "count": 1, "is_parallel": true, "self": 0.013944778009317815 }, "steps_from_proto": { "total": 0.00044288599747233093, "count": 1, "is_parallel": true, "self": 0.00011334801092743874, "children": { "_process_rank_one_or_two_observation": { "total": 0.0003295379865448922, "count": 8, "is_parallel": true, "self": 0.0003295379865448922 } } } } } } }, "UnityEnvironment.step": { "total": 3479.048297180998, "count": 659780, "is_parallel": true, "self": 86.30336274029105, "children": { "UnityEnvironment._generate_step_input": { "total": 55.967362358642276, "count": 659780, "is_parallel": true, "self": 55.967362358642276 }, "communicator.exchange": { "total": 3095.671771015768, "count": 659780, "is_parallel": true, "self": 3095.671771015768 }, "steps_from_proto": { "total": 241.1058010662964, "count": 659780, "is_parallel": true, "self": 52.665990547364345, "children": { "_process_rank_one_or_two_observation": { "total": 188.43981051893206, "count": 5278240, "is_parallel": true, "self": 188.43981051893206 } } } } } } } } } } }, "trainer_advance": { "total": 2697.956690645602, "count": 659781, "self": 9.748778851353563, "children": { "process_trajectory": { "total": 542.5550146230671, "count": 659781, "self": 541.7881467191328, "children": { "RLTrainer._checkpoint": { "total": 0.766867903934326, "count": 20, "self": 0.766867903934326 } } }, "_update_policy": { "total": 2145.6528971711814, "count": 4719, "self": 1277.2010323219874, "children": { "TorchPPOOptimizer.update": { "total": 868.451864849194, "count": 227991, "self": 868.451864849194 } } } } } } }, "trainer_threads": { "total": 4.899920895695686e-07, "count": 1, "self": 4.899920895695686e-07 }, "TrainerController._save_models": { "total": 0.036716889997478575, "count": 1, "self": 0.0008008040022104979, "children": { "RLTrainer._checkpoint": { "total": 0.03591608599526808, "count": 1, "self": 0.03591608599526808 } } } } } } }