Repo: pyro
Filename: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/projects/pyro/tests/integration_tests/test_conjugate_gaussian_models.py
ClassName: GaussianPyramidTests
Testname: test_elbo_nonreparameterized_two_layers
Params: param1,253,33,ParamType.ITER,8000
param2,253,39,ParamType.LR,0.001
Assertion: assert_equal(0.0, max_log_sig_error, prec=0.04)
Original runtime: 67.425
>>Getting original runtime
Optimization Iteration: 1
Running with params: {'param1': 8000, 'param2': 0.001}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_8000_0.001
Launching 30 jobs, 30 in parallel
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Timings: Avg: 66.52533333333334, Max: 68.56, Min: 65.27
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 66.52533333333334, Max: 68.56, Min: 65.27
Variance (0.0) too small, using delta distribution
Variance (3.651615642214754e-41) too small, using delta distribution
Variance (6.38832200740629e-37) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 66.52533333333334
Score: 66.52533333333334
Best-score: 66.52533333333334
Best-param: {'param1': 8000, 'param2': 0.001}
>>Setting original runtime to 66.52533333333334
Optimization Iteration: 1
Running with params: {'param1': 1300, 'param2': 0.011451534568517063}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_1300_0.011451534568517063
Launching 30 jobs, 30 in parallel
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Timings: Avg: 12.395000000000001, Max: 12.67, Min: 12.209999999999999
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.8931977372352651
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 12.395000000000001, Max: 12.67, Min: 12.209999999999999
Variance (1.0891660456978988e-34) too small, using delta distribution
Variance (2.5855365588320847e-37) too small, using delta distribution
Variance (2.9020996364550907e-36) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 12.395000000000001
Score: 12.395000000000001
Best-score: 12.395000000000001
Best-param: {'param1': 1300, 'param2': 0.011451534568517063}
Optimization Iteration: 2
Running with params: {'param1': 100, 'param2': 0.0045147313471077585}
Lower learning rate.. returning... Best: 0.011451534568517063, Proposed: 0.0045147313471077585
Optimization Iteration: 3
Running with params: {'param1': 7000, 'param2': 0.033848677110652675}
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Optimization Iteration: 4
Running with params: {'param1': 4500, 'param2': 0.00303458344472251}
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Optimization Iteration: 5
Running with params: {'param1': 800, 'param2': 0.026619492889279867}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_800_0.026619492889279867
Launching 30 jobs, 30 in parallel
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Timings: Avg: 8.427333333333333, Max: 8.57, Min: 8.19
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: inf
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 8.417166666666667, Max: 8.58, Min: 8.19
Passed tests : 60
Failed tests : 0
Converged: True
Convergence score: 0.6328775911610859
updating...
Evaluating 60 values out of 60
Overall-timings: Avg: 8.417166666666667, Max: 8.58, Min: 8.19
Variance (3.347807911141875e-35) too small, using delta distribution
Variance (1.2287834280595645e-35) too small, using delta distribution
Variance (2.261337665821862e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 8.417166666666667
Score: 8.417166666666667
Best-score: 8.417166666666667
Best-param: {'param1': 800, 'param2': 0.026619492889279867}
Optimization Iteration: 6
Running with params: {'param1': 6300, 'param2': 0.00041961763334143323}
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Optimization Iteration: 7
Running with params: {'param1': 3700, 'param2': 0.01399511230170099}
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Optimization Iteration: 8
Running with params: {'param1': 300, 'param2': 0.0001558871106936892}
Lower learning rate.. returning... Best: 0.026619492889279867, Proposed: 0.0001558871106936892
Optimization Iteration: 9
Running with params: {'param1': 200, 'param2': 0.0004536681908041882}
Lower learning rate.. returning... Best: 0.026619492889279867, Proposed: 0.0004536681908041882
Optimization Iteration: 10
Running with params: {'param1': 1700, 'param2': 0.005716757219541893}
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Optimization Iteration: 11
Running with params: {'param1': 7400, 'param2': 0.01916189163133319}
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Optimization Iteration: 12
Running with params: {'param1': 1400, 'param2': 0.04000188793081061}
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Optimization Iteration: 13
Running with params: {'param1': 1500, 'param2': 0.003146836912598636}
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Optimization Iteration: 14
Running with params: {'param1': 300, 'param2': 0.0010760604488906271}
Lower learning rate.. returning... Best: 0.026619492889279867, Proposed: 0.0010760604488906271
Optimization Iteration: 15
Running with params: {'param1': 100, 'param2': 0.00046622705728367503}
Lower learning rate.. returning... Best: 0.026619492889279867, Proposed: 0.00046622705728367503
Optimization Iteration: 16
Running with params: {'param1': 200, 'param2': 0.014944350958326684}
Lower learning rate.. returning... Best: 0.026619492889279867, Proposed: 0.014944350958326684
Optimization Iteration: 17
Running with params: {'param1': 700, 'param2': 0.009173574244645452}
Lower learning rate.. returning... Best: 0.026619492889279867, Proposed: 0.009173574244645452
Optimization Iteration: 18
Running with params: {'param1': 4200, 'param2': 0.013626679538517664}
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Optimization Iteration: 19
Running with params: {'param1': 1800, 'param2': 0.0007096398616939678}
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Optimization Iteration: 20
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Optimization Iteration: 21
Running with params: {'param1': 700, 'param2': 0.04642100367114126}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_700_0.04642100367114126
Launching 30 jobs, 30 in parallel
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Timings: Avg: 7.671666666666667, Max: 7.79, Min: 7.54
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.9345386270319955
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 7.671666666666667, Max: 7.79, Min: 7.54
Variance (2.697305010654832e-34) too small, using delta distribution
Variance (8.494905841942397e-36) too small, using delta distribution
Variance (5.703561283221783e-34) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 7.671666666666667
Score: 7.671666666666667
Best-score: 7.671666666666667
Best-param: {'param1': 700, 'param2': 0.04642100367114126}
Optimization Iteration: 22
Running with params: {'param1': 700, 'param2': 0.030086274671194735}
Lower learning rate.. returning... Best: 0.04642100367114126, Proposed: 0.030086274671194735
Optimization Iteration: 23
Running with params: {'param1': 500, 'param2': 0.046355700064022384}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_500_0.046355700064022384
Launching 30 jobs, 30 in parallel
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Timings: Avg: 6.074666666666666, Max: 6.26, Min: 5.9399999999999995
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: 1.7320508075688774
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 6.060999999999999, Max: 6.26, Min: 5.9399999999999995
Passed tests : 60
Failed tests : 0
Converged: True
Convergence score: 0.8553989227683015
updating...
Evaluating 60 values out of 60
Overall-timings: Avg: 6.060999999999999, Max: 6.26, Min: 5.9399999999999995
Variance (1.4933981777102691e-33) too small, using delta distribution
Variance (2.527783052008247e-34) too small, using delta distribution
Variance (3.686036819018474e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 6.060999999999999
Score: 6.060999999999999
Best-score: 6.060999999999999
Best-param: {'param1': 500, 'param2': 0.046355700064022384}
Optimization Iteration: 24
Running with params: {'param1': 500, 'param2': 0.0019109371272852352}
Lower learning rate.. returning... Best: 0.046355700064022384, Proposed: 0.0019109371272852352
Optimization Iteration: 25
Running with params: {'param1': 400, 'param2': 0.048642442708551156}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_400_0.048642442708551156
Launching 30 jobs, 30 in parallel
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Timings: Avg: 5.272666666666666, Max: 5.36, Min: 5.1899999999999995
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: 3.081295510409852
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 5.2755, Max: 5.36, Min: 5.1899999999999995
Passed tests : 60
Failed tests : 0
Converged: True
Convergence score: 0.525596822085243
updating...
Evaluating 60 values out of 60
Overall-timings: Avg: 5.2755, Max: 5.36, Min: 5.1899999999999995
Variance (2.2208379671215313e-34) too small, using delta distribution
Variance (4.852440680194403e-36) too small, using delta distribution
Variance (2.2567924209986823e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 5.2755
Score: 5.2755
Best-score: 5.2755
Best-param: {'param1': 400, 'param2': 0.048642442708551156}
Optimization Iteration: 26
Running with params: {'param1': 400, 'param2': 0.00015573812489561722}
Lower learning rate.. returning... Best: 0.048642442708551156, Proposed: 0.00015573812489561722
Optimization Iteration: 27
Running with params: {'param1': 200, 'param2': 0.049408058248462575}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_200_0.049408058248462575
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.6783333333333332, Max: 3.73, Min: 3.63
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: 1.319075179406883
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.694666666666667, Max: 3.8, Min: 3.63
Passed tests : 60
Failed tests : 0
Converged: False
Convergence score: 1.301435708210646
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.706666666666667, Max: 3.8000000000000003, Min: 3.62
Passed tests : 90
Failed tests : 0
Converged: True
Convergence score: 0.9193445622097101
updating...
Evaluating 90 values out of 90
Overall-timings: Avg: 3.706666666666667, Max: 3.8000000000000003, Min: 3.62
Variance (6.756670476423525e-33) too small, using delta distribution
Variance (4.873077136575505e-37) too small, using delta distribution
Variance (2.2996849037553535e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 3.706666666666667
Score: 3.706666666666667
Best-score: 3.706666666666667
Best-param: {'param1': 200, 'param2': 0.049408058248462575}
Optimization Iteration: 28
Running with params: {'param1': 200, 'param2': 0.006852908083725108}
Lower learning rate.. returning... Best: 0.049408058248462575, Proposed: 0.006852908083725108
Optimization Iteration: 29
Running with params: {'param1': 100, 'param2': 0.022191533819367584}
Lower learning rate.. returning... Best: 0.049408058248462575, Proposed: 0.022191533819367584
Optimization Iteration: 30
Running with params: {'param1': 200, 'param2': 0.049455703676788}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_200_0.049455703676788
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.6756666666666664, Max: 3.75, Min: 3.5300000000000002
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: 1.4192915448239072
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.677333333333333, Max: 3.75, Min: 3.5300000000000002
Passed tests : 60
Failed tests : 0
Converged: False
Convergence score: 1.3508690723046275
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.6815555555555552, Max: 3.75, Min: 3.5300000000000002
Passed tests : 90
Failed tests : 0
Converged: True
Convergence score: 0.6398416728806312
updating...
Evaluating 90 values out of 90
Overall-timings: Avg: 3.6815555555555552, Max: 3.75, Min: 3.5300000000000002
Variance (5.8607118168783805e-33) too small, using delta distribution
Variance (4.024496744187632e-37) too small, using delta distribution
Variance (1.9599409142710273e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 3.6815555555555552
Score: 3.6815555555555552
Best-score: 3.6815555555555552
Best-param: {'param1': 200, 'param2': 0.049455703676788}
Optimization Iteration: 31
Running with params: {'param1': 100, 'param2': 0.008856104400270116}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.008856104400270116
Optimization Iteration: 32
Running with params: {'param1': 200, 'param2': 0.00010030339482793957}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.00010030339482793957
Optimization Iteration: 33
Running with params: {'param1': 100, 'param2': 0.0016944847434087985}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0016944847434087985
Optimization Iteration: 34
Running with params: {'param1': 1000, 'param2': 0.004003831754328607}
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Optimization Iteration: 35
Running with params: {'param1': 2300, 'param2': 0.02843206486611474}
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Optimization Iteration: 36
Running with params: {'param1': 100, 'param2': 0.019896422717274875}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.019896422717274875
Optimization Iteration: 37
Running with params: {'param1': 300, 'param2': 0.005674590833404441}
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Optimization Iteration: 38
Running with params: {'param1': 200, 'param2': 0.03660881546395462}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.03660881546395462
Optimization Iteration: 39
Running with params: {'param1': 1100, 'param2': 0.00023495483278502077}
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Optimization Iteration: 40
Running with params: {'param1': 100, 'param2': 0.0014053962250082674}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0014053962250082674
Optimization Iteration: 41
Running with params: {'param1': 200, 'param2': 0.0029746544632284983}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0029746544632284983
Optimization Iteration: 42
Running with params: {'param1': 300, 'param2': 0.009876341997759521}
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Optimization Iteration: 43
Running with params: {'param1': 2500, 'param2': 0.023389175863062453}
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Optimization Iteration: 44
Running with params: {'param1': 100, 'param2': 0.01625673899515242}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.01625673899515242
Optimization Iteration: 45
Running with params: {'param1': 400, 'param2': 0.004459862138266672}
Higher iteration... returning...
Optimization Iteration: 46
Running with params: {'param1': 500, 'param2': 0.03493938122826212}
Higher iteration... returning...
Optimization Iteration: 47
Running with params: {'param1': 200, 'param2': 0.0007077509751500207}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0007077509751500207
Optimization Iteration: 48
Running with params: {'param1': 300, 'param2': 0.007212950487345076}
Higher iteration... returning...
Optimization Iteration: 49
Running with params: {'param1': 100, 'param2': 0.01757100526740943}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.01757100526740943
Optimization Iteration: 50
Running with params: {'param1': 900, 'param2': 0.0003102102314967519}
Higher iteration... returning...
Upto iteration 50: {'param1': 200.0, 'param2': 0.049455703676788}
Optimization Iteration: 51
Running with params: {'param1': 100, 'param2': 0.011235550026280478}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.011235550026280478
Optimization Iteration: 52
Running with params: {'param1': 600, 'param2': 0.0028550193520773914}
Higher iteration... returning...
Optimization Iteration: 53
Running with params: {'param1': 200, 'param2': 0.0008848341860659215}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0008848341860659215
Optimization Iteration: 54
Running with params: {'param1': 6100, 'param2': 0.025722572507065725}
Higher iteration... returning...
Optimization Iteration: 55
Running with params: {'param1': 1300, 'param2': 0.04995960423245928}
Higher iteration... returning...
Optimization Iteration: 56
Running with params: {'param1': 3000, 'param2': 0.04166149837556532}
Higher iteration... returning...
Optimization Iteration: 57
Running with params: {'param1': 300, 'param2': 0.01198282766059009}
Higher iteration... returning...
Optimization Iteration: 58
Running with params: {'param1': 400, 'param2': 0.005664471151497221}
Higher iteration... returning...
Optimization Iteration: 59
Running with params: {'param1': 100, 'param2': 0.00363233001567733}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.00363233001567733
Optimization Iteration: 60
Running with params: {'param1': 200, 'param2': 0.007389368380189176}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.007389368380189176
Optimization Iteration: 61
Running with params: {'param1': 600, 'param2': 0.03166812504167211}
Higher iteration... returning...
Optimization Iteration: 62
Running with params: {'param1': 100, 'param2': 0.0020085637184138975}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0020085637184138975
Optimization Iteration: 63
Running with params: {'param1': 200, 'param2': 0.00015048227993807995}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.00015048227993807995
Optimization Iteration: 64
Running with params: {'param1': 800, 'param2': 0.022031920871004185}
Higher iteration... returning...
Optimization Iteration: 65
Running with params: {'param1': 2000, 'param2': 0.0005577673304711762}
Higher iteration... returning...
Optimization Iteration: 66
Running with params: {'param1': 400, 'param2': 0.046774944455497125}
Higher iteration... returning...
Optimization Iteration: 67
Running with params: {'param1': 300, 'param2': 0.04996802505818533}
Higher iteration... returning...
Optimization Iteration: 68
Running with params: {'param1': 300, 'param2': 0.02744049966534668}
Higher iteration... returning...
Optimization Iteration: 69
Running with params: {'param1': 500, 'param2': 0.040623982630757144}
Higher iteration... returning...
Optimization Iteration: 70
Running with params: {'param1': 200, 'param2': 0.019654125614061824}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.019654125614061824
Optimization Iteration: 71
Running with params: {'param1': 100, 'param2': 0.01422495714816623}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.01422495714816623
Optimization Iteration: 72
Running with params: {'param1': 400, 'param2': 0.03361491107528984}
Higher iteration... returning...
Optimization Iteration: 73
Running with params: {'param1': 100, 'param2': 0.002436941792507866}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.002436941792507866
Optimization Iteration: 74
Running with params: {'param1': 200, 'param2': 0.016465088086855456}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.016465088086855456
Optimization Iteration: 75
Running with params: {'param1': 600, 'param2': 0.009375996701398848}
Higher iteration... returning...
Optimization Iteration: 76
Running with params: {'param1': 1200, 'param2': 0.012143507020989562}
Higher iteration... returning...
Optimization Iteration: 77
Running with params: {'param1': 100, 'param2': 0.03717849214199557}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.03717849214199557
Optimization Iteration: 78
Running with params: {'param1': 200, 'param2': 0.025223848765221647}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.025223848765221647
Optimization Iteration: 79
Running with params: {'param1': 300, 'param2': 0.001223265072187027}
Higher iteration... returning...
Optimization Iteration: 80
Running with params: {'param1': 400, 'param2': 0.005028876237201122}
Higher iteration... returning...
Optimization Iteration: 81
Running with params: {'param1': 800, 'param2': 0.03130457883362597}
Higher iteration... returning...
Optimization Iteration: 82
Running with params: {'param1': 100, 'param2': 0.021656670176580732}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.021656670176580732
Optimization Iteration: 83
Running with params: {'param1': 200, 'param2': 0.04372167847957842}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.04372167847957842
Optimization Iteration: 84
Running with params: {'param1': 1000, 'param2': 0.018996307173832095}
Higher iteration... returning...
Optimization Iteration: 85
Running with params: {'param1': 100, 'param2': 0.00818343069229752}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.00818343069229752
Optimization Iteration: 86
Running with params: {'param1': 500, 'param2': 0.011044745447375024}
Higher iteration... returning...
Optimization Iteration: 87
Running with params: {'param1': 300, 'param2': 0.015579183466509603}
Higher iteration... returning...
Optimization Iteration: 88
Running with params: {'param1': 700, 'param2': 0.00022132764707928998}
Higher iteration... returning...
Optimization Iteration: 89
Running with params: {'param1': 100, 'param2': 0.00011962536637174523}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.00011962536637174523
Optimization Iteration: 90
Running with params: {'param1': 200, 'param2': 0.04941530594479466}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597914817/assert_88575436_200_0.04941530594479466
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.6806666666666668, Max: 3.75, Min: 3.59
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: 1.3606919381372393
Continuing to next batch...
Launching 30 jobs, 30 in parallel
Iter 0...
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Timings: Avg: 3.695333333333333, Max: 3.79, Min: 3.59
Passed tests : 60
Failed tests : 0
Converged: True
Convergence score: 0.7557179431279228
updating...
Evaluating 60 values out of 60
Overall-timings: Avg: 3.695333333333333, Max: 3.79, Min: 3.59
Variance (4.824655128392566e-33) too small, using delta distribution
Variance (1.3484022229885533e-36) too small, using delta distribution
Variance (2.8946156557548556e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 3.695333333333333
Score: 3.695333333333333
Best-score: 3.6815555555555552
Best-param: {'param1': 200, 'param2': 0.049455703676788}
Optimization Iteration: 91
Running with params: {'param1': 100, 'param2': 0.006487276344946518}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.006487276344946518
Optimization Iteration: 92
Running with params: {'param1': 200, 'param2': 0.03836357373199666}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.03836357373199666
Optimization Iteration: 93
Running with params: {'param1': 100, 'param2': 0.0003664582958637057}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0003664582958637057
Optimization Iteration: 94
Running with params: {'param1': 100, 'param2': 0.02909536289029703}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.02909536289029703
Optimization Iteration: 95
Running with params: {'param1': 5100, 'param2': 0.01834777128373238}
Higher iteration... returning...
Optimization Iteration: 96
Running with params: {'param1': 200, 'param2': 0.013373252922636749}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.013373252922636749
Optimization Iteration: 97
Running with params: {'param1': 3500, 'param2': 0.0036893383951062215}
Higher iteration... returning...
Optimization Iteration: 98
Running with params: {'param1': 200, 'param2': 0.023986997772465754}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.023986997772465754
Optimization Iteration: 99
Running with params: {'param1': 300, 'param2': 0.010071584309049832}
Higher iteration... returning...
Optimization Iteration: 100
Running with params: {'param1': 100, 'param2': 0.0014933533908198695}
Lower learning rate.. returning... Best: 0.049455703676788, Proposed: 0.0014933533908198695
Upto iteration 100: {'param1': 200.0, 'param2': 0.049455703676788}
Breaking...
{'param1': 200.0, 'param2': 0.049455703676788}
Best score: 3.6815555555555552
Repeated params: 0
Trials: 101
Best param {'param1': 200.0, 'param2': 0.049455703676788}
Reduction: 94.46593444769577%
Speedup: 18.069897989980085x
Optimizer time: 164.05761098861694
