Repo: pyro
Filename: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/projects/pyro/tests/infer/test_elbo_mapdata.py
ClassName: none
Testname: test_elbo_mapdata[iplate-8]
Params: param1,50,14,ParamType.ITER,7000
param2,89,29,ParamType.LR,0.0008
Assertion: assert_equal(loc_error.item(), 0, prec=0.05)
Original runtime: 53.605
>>Getting original runtime
Optimization Iteration: 1
Running with params: {'param1': 7000, 'param2': 0.0008}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_7000_0.0008
Launching 30 jobs, 30 in parallel
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Timings: Avg: 52.557, Max: 55.309999999999995, Min: 51.279999999999994
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 52.557, Max: 55.309999999999995, Min: 51.279999999999994
Variance (1.8367099231598242e-40) too small, using delta distribution
Variance (0.0) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 52.557
Score: 52.557
Best-score: 52.557
Best-param: {'param1': 7000, 'param2': 0.0008}
>>Setting original runtime to 52.557
Optimization Iteration: 1
Running with params: {'param1': 1100, 'param2': 0.008102331392770765}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_1100_0.008102331392770765
Launching 30 jobs, 30 in parallel
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Timings: Avg: 9.983000000000002, Max: 10.120000000000001, Min: 9.83
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 9.983000000000002, Max: 10.120000000000001, Min: 9.83
Variance (0.0) too small, using delta distribution
Variance (2.7083389842945504e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 9.983000000000002
Score: 9.983000000000002
Best-score: 9.983000000000002
Best-param: {'param1': 1100, 'param2': 0.008102331392770765}
Optimization Iteration: 2
Running with params: {'param1': 3700, 'param2': 0.0005736522889904589}
Higher iteration... returning...
Optimization Iteration: 3
Running with params: {'param1': 100, 'param2': 0.0001358455174464939}
Lower learning rate.. returning... Best: 0.008102331392770765, Proposed: 0.0001358455174464939
Optimization Iteration: 4
Running with params: {'param1': 2200, 'param2': 0.0001102307977508678}
Higher iteration... returning...
Optimization Iteration: 5
Running with params: {'param1': 400, 'param2': 0.00040789629266661125}
Lower learning rate.. returning... Best: 0.008102331392770765, Proposed: 0.00040789629266661125
Optimization Iteration: 6
Running with params: {'param1': 200, 'param2': 0.003097690583710733}
Lower learning rate.. returning... Best: 0.008102331392770765, Proposed: 0.003097690583710733
Optimization Iteration: 7
Running with params: {'param1': 100, 'param2': 0.0040569571330757405}
Lower learning rate.. returning... Best: 0.008102331392770765, Proposed: 0.0040569571330757405
Optimization Iteration: 8
Running with params: {'param1': 400, 'param2': 0.00035182273567276593}
Lower learning rate.. returning... Best: 0.008102331392770765, Proposed: 0.00035182273567276593
Optimization Iteration: 9
Running with params: {'param1': 1100, 'param2': 0.0006923141533690521}
Lower learning rate.. returning... Best: 0.008102331392770765, Proposed: 0.0006923141533690521
Optimization Iteration: 10
Running with params: {'param1': 1000, 'param2': 0.022939450011860804}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_1000_0.022939450011860804
Launching 30 jobs, 30 in parallel
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Timings: Avg: 9.283666666666665, Max: 9.44, Min: 8.96
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 9.283666666666665, Max: 9.44, Min: 8.96
Variance (0.0) too small, using delta distribution
Variance (7.52316384526264e-37) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 9.283666666666665
Score: 9.283666666666665
Best-score: 9.283666666666665
Best-param: {'param1': 1000, 'param2': 0.022939450011860804}
Optimization Iteration: 11
Running with params: {'param1': 700, 'param2': 0.01283618773308617}
Lower learning rate.. returning... Best: 0.022939450011860804, Proposed: 0.01283618773308617
Optimization Iteration: 12
Running with params: {'param1': 200, 'param2': 0.00040774791362071687}
Lower learning rate.. returning... Best: 0.022939450011860804, Proposed: 0.00040774791362071687
Optimization Iteration: 13
Running with params: {'param1': 7000, 'param2': 0.00013496237093764028}
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Optimization Iteration: 14
Running with params: {'param1': 200, 'param2': 0.019651038099148366}
Lower learning rate.. returning... Best: 0.022939450011860804, Proposed: 0.019651038099148366
Optimization Iteration: 15
Running with params: {'param1': 100, 'param2': 0.002945177104314522}
Lower learning rate.. returning... Best: 0.022939450011860804, Proposed: 0.002945177104314522
Optimization Iteration: 16
Running with params: {'param1': 3100, 'param2': 0.000795438893931101}
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Optimization Iteration: 17
Running with params: {'param1': 2300, 'param2': 0.009150503177966436}
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Optimization Iteration: 18
Running with params: {'param1': 100, 'param2': 0.0005722294739697407}
Lower learning rate.. returning... Best: 0.022939450011860804, Proposed: 0.0005722294739697407
Optimization Iteration: 19
Running with params: {'param1': 4000, 'param2': 0.004137457868000039}
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Optimization Iteration: 20
Running with params: {'param1': 200, 'param2': 0.03544486075736105}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_200_0.03544486075736105
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.5573333333333332, Max: 3.6100000000000003, Min: 3.43
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 3.5573333333333332, Max: 3.6100000000000003, Min: 3.43
Variance (0.0) too small, using delta distribution
Variance (7.52316384526264e-37) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 3.5573333333333332
Score: 3.5573333333333332
Best-score: 3.5573333333333332
Best-param: {'param1': 200, 'param2': 0.03544486075736105}
Optimization Iteration: 21
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Optimization Iteration: 30
Running with params: {'param1': 300, 'param2': 0.031791578985673766}
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Running with params: {'param1': 800, 'param2': 0.0014826256584979012}
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Optimization Iteration: 32
Running with params: {'param1': 2100, 'param2': 0.01420829802614011}
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Optimization Iteration: 33
Running with params: {'param1': 200, 'param2': 0.049895908395536856}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_200_0.049895908395536856
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.5763333333333334, Max: 3.65, Min: 3.5
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 3.5763333333333334, Max: 3.65, Min: 3.5
Variance (4.81482486096809e-35) too small, using delta distribution
Variance (0.0) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 3.5763333333333334
Score: 3.5763333333333334
Best-score: 3.5573333333333332
Best-param: {'param1': 200, 'param2': 0.03544486075736105}
Optimization Iteration: 34
Running with params: {'param1': 200, 'param2': 0.04460712558523302}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_200_0.04460712558523302
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.5380000000000007, Max: 3.5700000000000003, Min: 3.46
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 3.5380000000000007, Max: 3.5700000000000003, Min: 3.46
Variance (1.2037062152420224e-35) too small, using delta distribution
Variance (7.52316384526264e-37) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 3.5380000000000007
Score: 3.5380000000000007
Best-score: 3.5380000000000007
Best-param: {'param1': 200, 'param2': 0.04460712558523302}
Optimization Iteration: 35
Running with params: {'param1': 100, 'param2': 0.0002315845043346546}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.0002315845043346546
Optimization Iteration: 36
Running with params: {'param1': 300, 'param2': 0.005960792597311897}
Higher iteration... returning...
Optimization Iteration: 37
Running with params: {'param1': 100, 'param2': 0.011486775739316966}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.011486775739316966
Optimization Iteration: 38
Running with params: {'param1': 200, 'param2': 0.039936840688846}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.039936840688846
Optimization Iteration: 39
Running with params: {'param1': 100, 'param2': 0.0014836217665742278}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.0014836217665742278
Optimization Iteration: 40
Running with params: {'param1': 100, 'param2': 0.025151212299324613}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.025151212299324613
Optimization Iteration: 41
Running with params: {'param1': 300, 'param2': 0.005666653383324615}
Higher iteration... returning...
Optimization Iteration: 42
Running with params: {'param1': 200, 'param2': 0.01032892546381351}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.01032892546381351
Optimization Iteration: 43
Running with params: {'param1': 500, 'param2': 0.014574428315175426}
Higher iteration... returning...
Optimization Iteration: 44
Running with params: {'param1': 200, 'param2': 0.0019242670445085183}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.0019242670445085183
Optimization Iteration: 45
Running with params: {'param1': 100, 'param2': 0.038598731432989274}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.038598731432989274
Optimization Iteration: 46
Running with params: {'param1': 400, 'param2': 0.004049495585523206}
Higher iteration... returning...
Optimization Iteration: 47
Running with params: {'param1': 600, 'param2': 0.00259071352916941}
Higher iteration... returning...
Optimization Iteration: 48
Running with params: {'param1': 100, 'param2': 0.0008698558142811241}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.0008698558142811241
Optimization Iteration: 49
Running with params: {'param1': 200, 'param2': 0.00023475493365605302}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.00023475493365605302
Optimization Iteration: 50
Running with params: {'param1': 100, 'param2': 0.02384214424207209}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.02384214424207209
Upto iteration 50: {'param1': 200.0, 'param2': 0.04460712558523302}
Optimization Iteration: 51
Running with params: {'param1': 300, 'param2': 0.01708025845758794}
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Optimization Iteration: 52
Running with params: {'param1': 500, 'param2': 0.006997125606832972}
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Optimization Iteration: 53
Running with params: {'param1': 5300, 'param2': 0.003925202061482205}
Higher iteration... returning...
Optimization Iteration: 54
Running with params: {'param1': 200, 'param2': 0.040642968321402795}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_200_0.040642968321402795
Launching 30 jobs, 30 in parallel
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Timings: Avg: 3.5493333333333337, Max: 3.6, Min: 3.5
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 3.5493333333333337, Max: 3.6, Min: 3.5
Variance (1.2037062152420224e-35) too small, using delta distribution
Variance (1.88079096131566e-37) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 3.5493333333333337
Score: 3.5493333333333337
Best-score: 3.5380000000000007
Best-param: {'param1': 200, 'param2': 0.04460712558523302}
Optimization Iteration: 55
Running with params: {'param1': 400, 'param2': 0.00010280611337366428}
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Optimization Iteration: 56
Running with params: {'param1': 700, 'param2': 0.0011559079984279205}
Higher iteration... returning...
Optimization Iteration: 57
Running with params: {'param1': 100, 'param2': 0.02544933102368688}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.02544933102368688
Optimization Iteration: 58
Running with params: {'param1': 200, 'param2': 0.0005447623995033703}
Lower learning rate.. returning... Best: 0.04460712558523302, Proposed: 0.0005447623995033703
Optimization Iteration: 59
Running with params: {'param1': 100, 'param2': 0.045172474786100106}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_100_0.045172474786100106
Launching 30 jobs, 30 in parallel
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Timings: Avg: 2.8386666666666662, Max: 2.88, Min: 2.79
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.8386666666666662, Max: 2.88, Min: 2.79
Variance (3.009265538105056e-36) too small, using delta distribution
Variance (4.81482486096809e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 2.8386666666666662
Score: 2.8386666666666662
Best-score: 2.8386666666666662
Best-param: {'param1': 100, 'param2': 0.045172474786100106}
Optimization Iteration: 60
Running with params: {'param1': 100, 'param2': 0.0051125084684574265}
Lower learning rate.. returning... Best: 0.045172474786100106, Proposed: 0.0051125084684574265
Optimization Iteration: 61
Running with params: {'param1': 100, 'param2': 0.009739900614401846}
Lower learning rate.. returning... Best: 0.045172474786100106, Proposed: 0.009739900614401846
Optimization Iteration: 62
Running with params: {'param1': 100, 'param2': 0.01250341664474698}
Lower learning rate.. returning... Best: 0.045172474786100106, Proposed: 0.01250341664474698
Optimization Iteration: 63
Running with params: {'param1': 1800, 'param2': 0.02040986046766752}
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Optimization Iteration: 64
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Optimization Iteration: 65
Running with params: {'param1': 1200, 'param2': 0.048848830942693426}
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Optimization Iteration: 66
Running with params: {'param1': 200, 'param2': 0.02840579531209094}
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Optimization Iteration: 67
Running with params: {'param1': 300, 'param2': 0.04145607498866588}
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Optimization Iteration: 68
Running with params: {'param1': 200, 'param2': 0.007932482457960055}
Higher iteration... returning...
Optimization Iteration: 69
Running with params: {'param1': 100, 'param2': 0.01690198605531809}
Lower learning rate.. returning... Best: 0.045172474786100106, Proposed: 0.01690198605531809
Optimization Iteration: 70
Running with params: {'param1': 100, 'param2': 0.033383234551788855}
Lower learning rate.. returning... Best: 0.045172474786100106, Proposed: 0.033383234551788855
Optimization Iteration: 71
Running with params: {'param1': 400, 'param2': 0.04168695587889576}
Higher iteration... returning...
Optimization Iteration: 72
Running with params: {'param1': 100, 'param2': 0.04917300190876369}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_100_0.04917300190876369
Launching 30 jobs, 30 in parallel
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Timings: Avg: 2.866333333333334, Max: 2.9000000000000004, Min: 2.8
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.866333333333334, Max: 2.9000000000000004, Min: 2.8
Variance (6.770847460736376e-36) too small, using delta distribution
Variance (0.0) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 2.866333333333334
Score: 2.866333333333334
Best-score: 2.8386666666666662
Best-param: {'param1': 100, 'param2': 0.045172474786100106}
Optimization Iteration: 73
Running with params: {'param1': 100, 'param2': 0.04931992007188151}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_100_0.04931992007188151
Launching 30 jobs, 30 in parallel
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Timings: Avg: 2.8316666666666666, Max: 2.8800000000000003, Min: 2.73
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.8316666666666666, Max: 2.8800000000000003, Min: 2.73
Variance (3.009265538105056e-36) too small, using delta distribution
Variance (4.81482486096809e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 2.8316666666666666
Score: 2.8316666666666666
Best-score: 2.8316666666666666
Best-param: {'param1': 100, 'param2': 0.04931992007188151}
Optimization Iteration: 74
Running with params: {'param1': 100, 'param2': 0.02911827536771145}
Lower learning rate.. returning... Best: 0.04931992007188151, Proposed: 0.02911827536771145
Optimization Iteration: 75
Running with params: {'param1': 100, 'param2': 0.019891438637319472}
Lower learning rate.. returning... Best: 0.04931992007188151, Proposed: 0.019891438637319472
Optimization Iteration: 76
Running with params: {'param1': 100, 'param2': 0.015408521274790102}
Lower learning rate.. returning... Best: 0.04931992007188151, Proposed: 0.015408521274790102
Optimization Iteration: 77
Running with params: {'param1': 3800, 'param2': 0.0032941934547317535}
Higher iteration... returning...
Optimization Iteration: 78
Running with params: {'param1': 100, 'param2': 0.04970147225194485}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_100_0.04970147225194485
Launching 30 jobs, 30 in parallel
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Timings: Avg: 2.8126666666666664, Max: 2.8600000000000003, Min: 2.55
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.8126666666666664, Max: 2.8600000000000003, Min: 2.55
Variance (6.770847460736376e-36) too small, using delta distribution
Variance (4.81482486096809e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 2.8126666666666664
Score: 2.8126666666666664
Best-score: 2.8126666666666664
Best-param: {'param1': 100, 'param2': 0.04970147225194485}
Optimization Iteration: 79
Running with params: {'param1': 100, 'param2': 0.021913274803738864}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.021913274803738864
Optimization Iteration: 80
Running with params: {'param1': 100, 'param2': 0.010862015038222135}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.010862015038222135
Optimization Iteration: 81
Running with params: {'param1': 300, 'param2': 0.0002316133682364183}
Higher iteration... returning...
Optimization Iteration: 82
Running with params: {'param1': 200, 'param2': 0.035209013826290284}
Higher iteration... returning...
Optimization Iteration: 83
Running with params: {'param1': 5000, 'param2': 0.00013901568362569033}
Higher iteration... returning...
Optimization Iteration: 84
Running with params: {'param1': 100, 'param2': 0.012819150132335292}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.012819150132335292
Optimization Iteration: 85
Running with params: {'param1': 1000, 'param2': 0.02657244714171071}
Higher iteration... returning...
Optimization Iteration: 86
Running with params: {'param1': 100, 'param2': 0.0070292036844892105}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0070292036844892105
Optimization Iteration: 87
Running with params: {'param1': 200, 'param2': 0.03202547522746539}
Higher iteration... returning...
Optimization Iteration: 88
Running with params: {'param1': 100, 'param2': 0.04979347112971755}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_100_0.04979347112971755
Launching 30 jobs, 30 in parallel
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Timings: Avg: 2.829333333333333, Max: 2.87, Min: 2.78
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.829333333333333, Max: 2.87, Min: 2.78
Variance (3.009265538105056e-36) too small, using delta distribution
Variance (4.81482486096809e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 2.829333333333333
Score: 2.829333333333333
Best-score: 2.8126666666666664
Best-param: {'param1': 100, 'param2': 0.04970147225194485}
Optimization Iteration: 89
Running with params: {'param1': 200, 'param2': 0.004942008633816942}
Higher iteration... returning...
Optimization Iteration: 90
Running with params: {'param1': 600, 'param2': 0.008488347535674554}
Higher iteration... returning...
Optimization Iteration: 91
Running with params: {'param1': 300, 'param2': 0.018445864806580965}
Higher iteration... returning...
Optimization Iteration: 92
Running with params: {'param1': 100, 'param2': 0.0002791011763328907}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0002791011763328907
Optimization Iteration: 93
Running with params: {'param1': 3100, 'param2': 0.01514567694412047}
Higher iteration... returning...
Optimization Iteration: 94
Running with params: {'param1': 400, 'param2': 0.00042331661920992555}
Higher iteration... returning...
Optimization Iteration: 95
Running with params: {'param1': 1500, 'param2': 0.0369464226588157}
Higher iteration... returning...
Optimization Iteration: 96
Running with params: {'param1': 200, 'param2': 0.0009478659331824706}
Higher iteration... returning...
Optimization Iteration: 97
Running with params: {'param1': 100, 'param2': 0.00015932799634495024}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.00015932799634495024
Optimization Iteration: 98
Running with params: {'param1': 800, 'param2': 0.022731512444997628}
Higher iteration... returning...
Optimization Iteration: 99
Running with params: {'param1': 100, 'param2': 0.011743342555359007}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.011743342555359007
Optimization Iteration: 100
Running with params: {'param1': 200, 'param2': 0.0027153727171072522}
Higher iteration... returning...
Upto iteration 100: {'param1': 100.0, 'param2': 0.04970147225194485}
Optimization Iteration: 101
Running with params: {'param1': 100, 'param2': 0.006626728567302194}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.006626728567302194
Optimization Iteration: 102
Running with params: {'param1': 300, 'param2': 0.0016756582851065141}
Higher iteration... returning...
Optimization Iteration: 103
Running with params: {'param1': 100, 'param2': 0.009229126512270808}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.009229126512270808
Optimization Iteration: 104
Running with params: {'param1': 500, 'param2': 0.003507167247376355}
Higher iteration... returning...
Optimization Iteration: 105
Running with params: {'param1': 700, 'param2': 0.04989761289870167}
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Optimization Iteration: 106
Running with params: {'param1': 200, 'param2': 0.0007051176952017347}
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Optimization Iteration: 107
Running with params: {'param1': 1900, 'param2': 0.02970949186953812}
Higher iteration... returning...
Optimization Iteration: 108
Running with params: {'param1': 100, 'param2': 0.004964224615666531}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.004964224615666531
Optimization Iteration: 109
Running with params: {'param1': 100, 'param2': 0.0011245449780849588}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0011245449780849588
Optimization Iteration: 110
Running with params: {'param1': 400, 'param2': 0.013900379270620952}
Higher iteration... returning...
Optimization Iteration: 111
Running with params: {'param1': 300, 'param2': 0.02553463154987457}
Higher iteration... returning...
Optimization Iteration: 112
Running with params: {'param1': 100, 'param2': 0.04329183158571057}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.04329183158571057
Optimization Iteration: 113
Running with params: {'param1': 200, 'param2': 0.02110102804140488}
Higher iteration... returning...
Optimization Iteration: 114
Running with params: {'param1': 900, 'param2': 0.01659333822049171}
Higher iteration... returning...
Optimization Iteration: 115
Running with params: {'param1': 100, 'param2': 0.007575354272542051}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.007575354272542051
Optimization Iteration: 116
Running with params: {'param1': 100, 'param2': 0.03618425364840304}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.03618425364840304
Optimization Iteration: 117
Running with params: {'param1': 1300, 'param2': 0.000512020286273526}
Higher iteration... returning...
Optimization Iteration: 118
Running with params: {'param1': 200, 'param2': 0.04976973506523657}
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Running with params: {'param1': 6600, 'param2': 0.010762370819209388}
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Optimization Iteration: 120
Running with params: {'param1': 500, 'param2': 0.030221134978693307}
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Optimization Iteration: 121
Running with params: {'param1': 2400, 'param2': 0.018907667407075737}
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Optimization Iteration: 122
Running with params: {'param1': 4500, 'param2': 0.013259719782715926}
Higher iteration... returning...
Optimization Iteration: 123
Running with params: {'param1': 100, 'param2': 0.002220521063864964}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.002220521063864964
Optimization Iteration: 124
Running with params: {'param1': 200, 'param2': 0.005759336786258745}
Higher iteration... returning...
Optimization Iteration: 125
Running with params: {'param1': 100, 'param2': 0.023720999967521614}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.023720999967521614
Optimization Iteration: 126
Running with params: {'param1': 300, 'param2': 0.026916822914451393}
Higher iteration... returning...
Optimization Iteration: 127
Running with params: {'param1': 600, 'param2': 0.044632337280220424}
Higher iteration... returning...
Optimization Iteration: 128
Running with params: {'param1': 100, 'param2': 0.03841591511095461}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.03841591511095461
Optimization Iteration: 129
Running with params: {'param1': 200, 'param2': 0.0002992341308139914}
Higher iteration... returning...
Optimization Iteration: 130
Running with params: {'param1': 100, 'param2': 0.0338666574669819}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0338666574669819
Optimization Iteration: 131
Running with params: {'param1': 100, 'param2': 0.0043516047873781785}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0043516047873781785
Optimization Iteration: 132
Running with params: {'param1': 200, 'param2': 0.015650428191589436}
Higher iteration... returning...
Optimization Iteration: 133
Running with params: {'param1': 3300, 'param2': 0.009139860673561014}
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Running with params: {'param1': 300, 'param2': 0.01829194262134386}
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Optimization Iteration: 135
Running with params: {'param1': 400, 'param2': 0.00181744008846215}
Higher iteration... returning...
Optimization Iteration: 136
Running with params: {'param1': 100, 'param2': 0.0013486124728609458}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0013486124728609458
Optimization Iteration: 137
Running with params: {'param1': 100, 'param2': 0.0001609182264592878}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0001609182264592878
Optimization Iteration: 138
Running with params: {'param1': 100, 'param2': 0.022281357215128722}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.022281357215128722
Optimization Iteration: 139
Running with params: {'param1': 200, 'param2': 0.032346735786268906}
Higher iteration... returning...
Optimization Iteration: 140
Running with params: {'param1': 100, 'param2': 0.0029117764439398207}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0029117764439398207
Optimization Iteration: 141
Running with params: {'param1': 5700, 'param2': 0.011869321056127254}
Higher iteration... returning...
Optimization Iteration: 142
Running with params: {'param1': 300, 'param2': 0.0036235872057112594}
Higher iteration... returning...
Optimization Iteration: 143
Running with params: {'param1': 100, 'param2': 0.006510533631021723}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.006510533631021723
Optimization Iteration: 144
Running with params: {'param1': 200, 'param2': 0.047700982545210206}
Higher iteration... returning...
Optimization Iteration: 145
Running with params: {'param1': 100, 'param2': 0.0403938089620479}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.0403938089620479
Optimization Iteration: 146
Running with params: {'param1': 100, 'param2': 0.027829723522925617}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.027829723522925617
Optimization Iteration: 147
Running with params: {'param1': 100, 'param2': 0.04313752093592605}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.04313752093592605
Optimization Iteration: 148
Running with params: {'param1': 100, 'param2': 0.04960386483262591}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921184/assert_14062485_100_0.04960386483262591
Launching 30 jobs, 30 in parallel
Iter 0...
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Timings: Avg: 2.8396666666666666, Max: 2.89, Min: 2.79
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.8396666666666666, Max: 2.89, Min: 2.79
Variance (3.009265538105056e-36) too small, using delta distribution
Variance (1.2037062152420224e-35) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 2.8396666666666666
Score: 2.8396666666666666
Best-score: 2.8126666666666664
Best-param: {'param1': 100, 'param2': 0.04970147225194485}
Optimization Iteration: 149
Running with params: {'param1': 100, 'param2': 0.034101546422055116}
Lower learning rate.. returning... Best: 0.04970147225194485, Proposed: 0.034101546422055116
Optimization Iteration: 150
Running with params: {'param1': 200, 'param2': 0.02002503591763183}
Higher iteration... returning...
Upto iteration 150: {'param1': 100.0, 'param2': 0.04970147225194485}
Breaking...
{'param1': 100.0, 'param2': 0.04970147225194485}
Best score: 2.8126666666666664
Repeated params: 0
Trials: 151
Best param {'param1': 100.0, 'param2': 0.04970147225194485}
Reduction: 94.64835004534758%
Speedup: 18.685826025124438x
Optimizer time: 111.1245505809784
