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[range-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: 48.307
>>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_1597921696/assert_10417934_7000_0.0008
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 12...
Iter 13...
Iter 14...
Iter 15...
Iter 17...
Iter 16...
Iter 18...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 23...
Iter 24...
Iter 25...
Iter 26...
Iter 27...
Iter 29...
Iter 28...
Timings: Avg: 45.407333333333334, Max: 47.01, Min: 44.349999999999994
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 45.407333333333334, Max: 47.01, Min: 44.349999999999994
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: 45.407333333333334
Score: 45.407333333333334
Best-score: 45.407333333333334
Best-param: {'param1': 7000, 'param2': 0.0008}
>>Setting original runtime to 45.407333333333334
Optimization Iteration: 1
Running with params: {'param1': 2400, 'param2': 0.00036418132491193095}
Lower learning rate.. returning... Best: 0.0008, Proposed: 0.00036418132491193095
Optimization Iteration: 2
Running with params: {'param1': 6800, 'param2': 0.004736968059116511}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_6800_0.004736968059116511
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 12...
Iter 13...
Iter 14...
Iter 15...
Iter 16...
Iter 17...
Iter 18...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 23...
Iter 24...
Iter 25...
Iter 27...
Iter 29...
Iter 28...
Iter 26...
Timings: Avg: 44.215, Max: 45.63, Min: 43.54
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 44.215, Max: 45.63, Min: 43.54
Variance (0.0) too small, using delta distribution
Variance (4.70197740328915e-38) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 44.215
Score: 44.215
Best-score: 44.215
Best-param: {'param1': 6800, 'param2': 0.004736968059116511}
Optimization Iteration: 3
Running with params: {'param1': 100, 'param2': 0.0002463247454211165}
Lower learning rate.. returning... Best: 0.004736968059116511, Proposed: 0.0002463247454211165
Optimization Iteration: 4
Running with params: {'param1': 400, 'param2': 0.00017992492605345406}
Lower learning rate.. returning... Best: 0.004736968059116511, Proposed: 0.00017992492605345406
Optimization Iteration: 5
Running with params: {'param1': 200, 'param2': 0.005259522792173358}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_200_0.005259522792173358
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 12...
Iter 13...
Iter 19...
Iter 14...
Iter 20...
Iter 15...
Iter 16...
Iter 21...
Iter 22...
Iter 17...
Iter 18...
Iter 23...
Iter 24...
Iter 25...
Iter 26...
Iter 28...
Iter 27...
Iter 29...
Timings: Avg: 3.3449999999999998, Max: 3.4, Min: 3.3
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 3.3449999999999998, Max: 3.4, Min: 3.3
Variance (1.1754943508222875e-38) 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: 3.3449999999999998
Score: 3.3449999999999998
Best-score: 3.3449999999999998
Best-param: {'param1': 200, 'param2': 0.005259522792173358}
Optimization Iteration: 6
Running with params: {'param1': 100, 'param2': 0.004313000383552728}
Lower learning rate.. returning... Best: 0.005259522792173358, Proposed: 0.004313000383552728
Optimization Iteration: 7
Running with params: {'param1': 3000, 'param2': 0.023147758002654503}
Higher iteration... returning...
Optimization Iteration: 8
Running with params: {'param1': 200, 'param2': 0.0001929614045906569}
Lower learning rate.. returning... Best: 0.005259522792173358, Proposed: 0.0001929614045906569
Optimization Iteration: 9
Running with params: {'param1': 600, 'param2': 0.03893167434419841}
Higher iteration... returning...
Optimization Iteration: 10
Running with params: {'param1': 2500, 'param2': 0.004739977937701594}
Higher iteration... returning...
Optimization Iteration: 11
Running with params: {'param1': 4100, 'param2': 0.00012983749201271608}
Higher iteration... returning...
Optimization Iteration: 12
Running with params: {'param1': 300, 'param2': 0.0008767634634867867}
Higher iteration... returning...
Optimization Iteration: 13
Running with params: {'param1': 300, 'param2': 0.023574703922434423}
Higher iteration... returning...
Optimization Iteration: 14
Running with params: {'param1': 1800, 'param2': 0.0032981366498745566}
Higher iteration... returning...
Optimization Iteration: 15
Running with params: {'param1': 2200, 'param2': 0.0006316271230961931}
Higher iteration... returning...
Optimization Iteration: 16
Running with params: {'param1': 200, 'param2': 0.003764233579843937}
Lower learning rate.. returning... Best: 0.005259522792173358, Proposed: 0.003764233579843937
Optimization Iteration: 17
Running with params: {'param1': 5400, 'param2': 0.0002332313005772167}
Higher iteration... returning...
Optimization Iteration: 18
Running with params: {'param1': 600, 'param2': 0.04838098622073105}
Higher iteration... returning...
Optimization Iteration: 19
Running with params: {'param1': 200, 'param2': 0.005109064067600414}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_200_0.005109064067600414
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 6...
Iter 3...
Iter 7...
Iter 4...
Iter 8...
Iter 5...
Iter 9...
Iter 10...
Iter 11...
Iter 12...
Iter 13...
Iter 19...
Iter 20...
Iter 15...
Iter 21...
Iter 14...
Iter 16...
Iter 17...
Iter 18...
Iter 22...
Iter 23...
Iter 24...
Iter 25...
Iter 26...
Iter 29...
Iter 27...
Iter 28...
Timings: Avg: 3.3536666666666672, Max: 3.4000000000000004, Min: 3.3000000000000003
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 3.3536666666666672, Max: 3.4000000000000004, Min: 3.3000000000000003
Variance (4.70197740328915e-38) 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: 3.3536666666666672
Score: 3.3536666666666672
Best-score: 3.3449999999999998
Best-param: {'param1': 200, 'param2': 0.005259522792173358}
Optimization Iteration: 20
Running with params: {'param1': 400, 'param2': 0.0017780871111912953}
Higher iteration... returning...
Optimization Iteration: 21
Running with params: {'param1': 1100, 'param2': 0.011440757710261136}
Higher iteration... returning...
Optimization Iteration: 22
Running with params: {'param1': 100, 'param2': 0.010345271041079959}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.010345271041079959
Launching 30 jobs, 30 in parallel
Iter 2...
Iter 3...
Iter 4...
Iter 0...
Iter 1...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 15...
Iter 12...
Iter 16...
Iter 17...
Iter 13...
Iter 18...
Iter 14...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 23...
Iter 28...
Iter 29...
Iter 24...
Iter 25...
Iter 26...
Iter 27...
Timings: Avg: 2.7479999999999998, Max: 2.77, Min: 2.69
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.7479999999999998, Max: 2.77, Min: 2.69
Variance (2.938735877055719e-39) 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: 2.7479999999999998
Score: 2.7479999999999998
Best-score: 2.7479999999999998
Best-param: {'param1': 100, 'param2': 0.010345271041079959}
Optimization Iteration: 23
Running with params: {'param1': 100, 'param2': 0.009489215887061843}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.009489215887061843
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 13...
Iter 10...
Iter 14...
Iter 11...
Iter 16...
Iter 17...
Iter 12...
Iter 15...
Iter 18...
Iter 19...
Iter 20...
Iter 21...
Iter 26...
Iter 22...
Iter 23...
Iter 29...
Iter 27...
Iter 28...
Iter 24...
Iter 25...
Timings: Avg: 2.728, Max: 2.7800000000000002, Min: 2.64
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.728, Max: 2.7800000000000002, Min: 2.64
Variance (1.8367099231598242e-40) 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: 2.728
Score: 2.728
Best-score: 2.728
Best-param: {'param1': 100, 'param2': 0.009489215887061843}
Optimization Iteration: 24
Running with params: {'param1': 100, 'param2': 0.010120229959534602}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.010120229959534602
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 10...
Iter 7...
Iter 11...
Iter 12...
Iter 8...
Iter 9...
Iter 13...
Iter 14...
Iter 15...
Iter 16...
Iter 17...
Iter 23...
Iter 18...
Iter 19...
Iter 24...
Iter 20...
Iter 21...
Iter 25...
Iter 22...
Iter 26...
Iter 27...
Iter 29...
Iter 28...
Timings: Avg: 2.739, Max: 2.7800000000000002, Min: 2.69
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.739, Max: 2.7800000000000002, Min: 2.69
Variance (7.346839692639297e-40) 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: 2.739
Score: 2.739
Best-score: 2.728
Best-param: {'param1': 100, 'param2': 0.009489215887061843}
Optimization Iteration: 25
Running with params: {'param1': 100, 'param2': 0.011396425874445436}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.011396425874445436
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 8...
Iter 9...
Iter 6...
Iter 10...
Iter 7...
Iter 11...
Iter 12...
Iter 13...
Iter 14...
Iter 21...
Iter 16...
Iter 22...
Iter 15...
Iter 17...
Iter 18...
Iter 23...
Iter 19...
Iter 24...
Iter 20...
Iter 25...
Iter 26...
Iter 27...
Iter 28...
Iter 29...
Timings: Avg: 2.7336666666666667, Max: 2.78, Min: 2.62
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.7336666666666667, Max: 2.78, Min: 2.62
Variance (1.1754943508222875e-38) 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: 2.7336666666666667
Score: 2.7336666666666667
Best-score: 2.728
Best-param: {'param1': 100, 'param2': 0.009489215887061843}
Optimization Iteration: 26
Running with params: {'param1': 100, 'param2': 0.01763234201796911}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.01763234201796911
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 2...
Iter 1...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 9...
Iter 10...
Iter 8...
Iter 11...
Iter 12...
Iter 14...
Iter 13...
Iter 15...
Iter 16...
Iter 17...
Iter 18...
Iter 24...
Iter 20...
Iter 19...
Iter 21...
Iter 25...
Iter 23...
Iter 22...
Iter 26...
Iter 27...
Iter 29...
Iter 28...
Timings: Avg: 2.731, Max: 2.7800000000000002, Min: 2.67
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.731, Max: 2.7800000000000002, Min: 2.67
Variance (1.88079096131566e-37) 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: 2.731
Score: 2.731
Best-score: 2.728
Best-param: {'param1': 100, 'param2': 0.009489215887061843}
Optimization Iteration: 27
Running with params: {'param1': 1100, 'param2': 0.020456729360150135}
Higher iteration... returning...
Optimization Iteration: 28
Running with params: {'param1': 100, 'param2': 0.03970154096202997}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.03970154096202997
Launching 30 jobs, 30 in parallel
Iter 3...
Iter 0...
Iter 1...
Iter 2...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 16...
Iter 10...
Iter 12...
Iter 11...
Iter 13...
Iter 14...
Iter 17...
Iter 18...
Iter 15...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 29...
Iter 28...
Iter 23...
Iter 24...
Iter 25...
Iter 27...
Iter 26...
Timings: Avg: 2.726666666666666, Max: 2.77, Min: 2.6399999999999997
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.726666666666666, Max: 2.77, Min: 2.6399999999999997
Variance (7.52316384526264e-37) 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: 2.726666666666666
Score: 2.726666666666666
Best-score: 2.726666666666666
Best-param: {'param1': 100, 'param2': 0.03970154096202997}
Optimization Iteration: 29
Running with params: {'param1': 200, 'param2': 0.0331400762043912}
Higher iteration... returning...
Optimization Iteration: 30
Running with params: {'param1': 100, 'param2': 0.0019967874825849575}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.0019967874825849575
Optimization Iteration: 31
Running with params: {'param1': 300, 'param2': 0.007941577517525097}
Higher iteration... returning...
Optimization Iteration: 32
Running with params: {'param1': 800, 'param2': 0.04782382600778043}
Higher iteration... returning...
Optimization Iteration: 33
Running with params: {'param1': 100, 'param2': 0.0013986851708984913}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.0013986851708984913
Optimization Iteration: 34
Running with params: {'param1': 400, 'param2': 0.01567006546816359}
Higher iteration... returning...
Optimization Iteration: 35
Running with params: {'param1': 200, 'param2': 0.0074305782988660736}
Higher iteration... returning...
Optimization Iteration: 36
Running with params: {'param1': 100, 'param2': 0.03343157975006448}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.03343157975006448
Optimization Iteration: 37
Running with params: {'param1': 1400, 'param2': 0.0027685077179493123}
Higher iteration... returning...
Optimization Iteration: 38
Running with params: {'param1': 600, 'param2': 0.00642526928671483}
Higher iteration... returning...
Optimization Iteration: 39
Running with params: {'param1': 100, 'param2': 0.0004650033472100014}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.0004650033472100014
Optimization Iteration: 40
Running with params: {'param1': 300, 'param2': 0.02729509914042377}
Higher iteration... returning...
Optimization Iteration: 41
Running with params: {'param1': 200, 'param2': 0.0012171772123695343}
Higher iteration... returning...
Optimization Iteration: 42
Running with params: {'param1': 6900, 'param2': 0.017102158818907313}
Higher iteration... returning...
Optimization Iteration: 43
Running with params: {'param1': 100, 'param2': 0.04947319272703495}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04947319272703495
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 13...
Iter 10...
Iter 14...
Iter 11...
Iter 12...
Iter 15...
Iter 16...
Iter 17...
Iter 18...
Iter 19...
Iter 20...
Iter 22...
Iter 21...
Iter 26...
Iter 23...
Iter 27...
Iter 28...
Iter 29...
Iter 25...
Iter 24...
Timings: Avg: 2.7303333333333333, Max: 2.7600000000000002, Min: 2.6799999999999997
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.7303333333333333, Max: 2.7600000000000002, Min: 2.6799999999999997
Variance (7.52316384526264e-37) 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: 2.7303333333333333
Score: 2.7303333333333333
Best-score: 2.726666666666666
Best-param: {'param1': 100, 'param2': 0.03970154096202997}
Optimization Iteration: 44
Running with params: {'param1': 3500, 'param2': 0.014090945069797496}
Higher iteration... returning...
Optimization Iteration: 45
Running with params: {'param1': 500, 'param2': 0.002600704786342001}
Higher iteration... returning...
Optimization Iteration: 46
Running with params: {'param1': 200, 'param2': 0.00010360332741510575}
Higher iteration... returning...
Optimization Iteration: 47
Running with params: {'param1': 800, 'param2': 0.031524473010149066}
Higher iteration... returning...
Optimization Iteration: 48
Running with params: {'param1': 300, 'param2': 0.006119891599974174}
Higher iteration... returning...
Optimization Iteration: 49
Running with params: {'param1': 100, 'param2': 0.024567898106663273}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.024567898106663273
Optimization Iteration: 50
Running with params: {'param1': 5300, 'param2': 0.003780935873127419}
Higher iteration... returning...
Upto iteration 50: {'param1': 100.0, 'param2': 0.03970154096202997}
Optimization Iteration: 51
Running with params: {'param1': 200, 'param2': 0.00035176512276198746}
Higher iteration... returning...
Optimization Iteration: 52
Running with params: {'param1': 1700, 'param2': 0.04077116843414584}
Higher iteration... returning...
Optimization Iteration: 53
Running with params: {'param1': 500, 'param2': 0.021572905060137832}
Higher iteration... returning...
Optimization Iteration: 54
Running with params: {'param1': 100, 'param2': 0.0009390068423201457}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.0009390068423201457
Optimization Iteration: 55
Running with params: {'param1': 1000, 'param2': 0.00843903389130055}
Higher iteration... returning...
Optimization Iteration: 56
Running with params: {'param1': 200, 'param2': 0.004837861879814856}
Higher iteration... returning...
Optimization Iteration: 57
Running with params: {'param1': 400, 'param2': 0.014126969935606084}
Higher iteration... returning...
Optimization Iteration: 58
Running with params: {'param1': 300, 'param2': 0.03929530174527256}
Higher iteration... returning...
Optimization Iteration: 59
Running with params: {'param1': 100, 'param2': 0.009205079450347188}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.009205079450347188
Optimization Iteration: 60
Running with params: {'param1': 2500, 'param2': 0.011635698182818763}
Higher iteration... returning...
Optimization Iteration: 61
Running with params: {'param1': 100, 'param2': 0.0015292424805100856}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.0015292424805100856
Optimization Iteration: 62
Running with params: {'param1': 700, 'param2': 0.003702245169915217}
Higher iteration... returning...
Optimization Iteration: 63
Running with params: {'param1': 200, 'param2': 0.006193102588845474}
Higher iteration... returning...
Optimization Iteration: 64
Running with params: {'param1': 100, 'param2': 0.018878011903757354}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.018878011903757354
Optimization Iteration: 65
Running with params: {'param1': 5000, 'param2': 0.027197010121663135}
Higher iteration... returning...
Optimization Iteration: 66
Running with params: {'param1': 100, 'param2': 0.040266137911887066}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.040266137911887066
Launching 30 jobs, 30 in parallel
Iter 3...
Iter 4...
Iter 1...
Iter 0...
Iter 2...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 12...
Iter 17...
Iter 16...
Iter 13...
Iter 18...
Iter 14...
Iter 15...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 29...
Iter 23...
Iter 28...
Iter 24...
Iter 25...
Iter 26...
Iter 27...
Timings: Avg: 2.7319999999999993, Max: 2.79, Min: 2.5900000000000003
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.7319999999999993, Max: 2.79, Min: 2.5900000000000003
Variance (7.52316384526264e-37) 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: 2.7319999999999993
Score: 2.7319999999999993
Best-score: 2.726666666666666
Best-param: {'param1': 100, 'param2': 0.03970154096202997}
Optimization Iteration: 67
Running with params: {'param1': 100, 'param2': 0.013060342398420698}
Lower learning rate.. returning... Best: 0.03970154096202997, Proposed: 0.013060342398420698
Optimization Iteration: 68
Running with params: {'param1': 100, 'param2': 0.04888963292848058}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04888963292848058
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 13...
Iter 10...
Iter 14...
Iter 11...
Iter 15...
Iter 12...
Iter 16...
Iter 17...
Iter 18...
Iter 19...
Iter 20...
Iter 22...
Iter 21...
Iter 26...
Iter 23...
Iter 27...
Iter 29...
Iter 28...
Iter 25...
Iter 24...
Timings: Avg: 2.727, Max: 2.79, Min: 2.64
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.727, Max: 2.79, Min: 2.64
Variance (7.52316384526264e-37) 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: 2.727
Score: 2.727
Best-score: 2.726666666666666
Best-param: {'param1': 100, 'param2': 0.03970154096202997}
Optimization Iteration: 69
Running with params: {'param1': 100, 'param2': 0.04974505577930725}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04974505577930725
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 11...
Iter 8...
Iter 12...
Iter 9...
Iter 13...
Iter 10...
Iter 14...
Iter 15...
Iter 16...
Iter 17...
Iter 18...
Iter 19...
Iter 24...
Iter 20...
Iter 21...
Iter 25...
Iter 22...
Iter 26...
Iter 23...
Iter 27...
Iter 29...
Iter 28...
Timings: Avg: 2.7190000000000003, Max: 2.7600000000000002, Min: 2.5900000000000003
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.7190000000000003, Max: 2.7600000000000002, Min: 2.5900000000000003
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: 2.7190000000000003
Score: 2.7190000000000003
Best-score: 2.7190000000000003
Best-param: {'param1': 100, 'param2': 0.04974505577930725}
Optimization Iteration: 70
Running with params: {'param1': 100, 'param2': 0.04917428382119167}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04917428382119167
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 9...
Iter 6...
Iter 7...
Iter 10...
Iter 11...
Iter 8...
Iter 12...
Iter 13...
Iter 14...
Iter 15...
Iter 16...
Iter 17...
Iter 18...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 23...
Iter 24...
Iter 25...
Iter 26...
Iter 27...
Iter 28...
Iter 29...
Timings: Avg: 2.7279999999999998, Max: 2.77, Min: 2.67
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.7279999999999998, Max: 2.77, Min: 2.67
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: 2.7279999999999998
Score: 2.7279999999999998
Best-score: 2.7190000000000003
Best-param: {'param1': 100, 'param2': 0.04974505577930725}
Optimization Iteration: 71
Running with params: {'param1': 200, 'param2': 0.03134892146147863}
Higher iteration... returning...
Optimization Iteration: 72
Running with params: {'param1': 100, 'param2': 0.00016671332313910526}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.00016671332313910526
Optimization Iteration: 73
Running with params: {'param1': 300, 'param2': 0.045531937384259015}
Higher iteration... returning...
Optimization Iteration: 74
Running with params: {'param1': 100, 'param2': 0.02378212598077699}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.02378212598077699
Optimization Iteration: 75
Running with params: {'param1': 200, 'param2': 0.03635199112655323}
Higher iteration... returning...
Optimization Iteration: 76
Running with params: {'param1': 100, 'param2': 0.028828964428557577}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.028828964428557577
Optimization Iteration: 77
Running with params: {'param1': 200, 'param2': 0.00031786151185318235}
Higher iteration... returning...
Optimization Iteration: 78
Running with params: {'param1': 400, 'param2': 0.0006513986760709235}
Higher iteration... returning...
Optimization Iteration: 79
Running with params: {'param1': 100, 'param2': 0.016096236573338973}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.016096236573338973
Optimization Iteration: 80
Running with params: {'param1': 200, 'param2': 0.020031847549143025}
Higher iteration... returning...
Optimization Iteration: 81
Running with params: {'param1': 500, 'param2': 0.04479298657740954}
Higher iteration... returning...
Optimization Iteration: 82
Running with params: {'param1': 100, 'param2': 0.0028407333073531714}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.0028407333073531714
Optimization Iteration: 83
Running with params: {'param1': 300, 'param2': 0.025410222751505195}
Higher iteration... returning...
Optimization Iteration: 84
Running with params: {'param1': 100, 'param2': 0.03301096496308389}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.03301096496308389
Optimization Iteration: 85
Running with params: {'param1': 3100, 'param2': 0.007203300483973059}
Higher iteration... returning...
Optimization Iteration: 86
Running with params: {'param1': 1500, 'param2': 0.021840498740418837}
Higher iteration... returning...
Optimization Iteration: 87
Running with params: {'param1': 100, 'param2': 0.010874338395703344}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.010874338395703344
Optimization Iteration: 88
Running with params: {'param1': 200, 'param2': 0.012471837232585908}
Higher iteration... returning...
Optimization Iteration: 89
Running with params: {'param1': 100, 'param2': 0.002227103391963843}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.002227103391963843
Optimization Iteration: 90
Running with params: {'param1': 300, 'param2': 0.015033827470509534}
Higher iteration... returning...
Optimization Iteration: 91
Running with params: {'param1': 200, 'param2': 0.0053114693170784036}
Higher iteration... returning...
Optimization Iteration: 92
Running with params: {'param1': 1200, 'param2': 0.03552625695143295}
Higher iteration... returning...
Optimization Iteration: 93
Running with params: {'param1': 100, 'param2': 0.01813220254064444}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.01813220254064444
Optimization Iteration: 94
Running with params: {'param1': 2300, 'param2': 0.0005013946552363869}
Higher iteration... returning...
Optimization Iteration: 95
Running with params: {'param1': 900, 'param2': 0.044010462306415206}
Higher iteration... returning...
Optimization Iteration: 96
Running with params: {'param1': 100, 'param2': 0.009802604837002914}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.009802604837002914
Optimization Iteration: 97
Running with params: {'param1': 200, 'param2': 0.02909581969096446}
Higher iteration... returning...
Optimization Iteration: 98
Running with params: {'param1': 400, 'param2': 0.00010086755606902704}
Higher iteration... returning...
Optimization Iteration: 99
Running with params: {'param1': 600, 'param2': 0.004219640494182887}
Higher iteration... returning...
Optimization Iteration: 100
Running with params: {'param1': 100, 'param2': 0.0010842517216625672}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.0010842517216625672
Upto iteration 100: {'param1': 100.0, 'param2': 0.04974505577930725}
Optimization Iteration: 101
Running with params: {'param1': 700, 'param2': 0.0007454058102212139}
Higher iteration... returning...
Optimization Iteration: 102
Running with params: {'param1': 200, 'param2': 0.001703212550808224}
Higher iteration... returning...
Optimization Iteration: 103
Running with params: {'param1': 100, 'param2': 0.00012431217151188573}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.00012431217151188573
Optimization Iteration: 104
Running with params: {'param1': 100, 'param2': 0.039494314500085434}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.039494314500085434
Optimization Iteration: 105
Running with params: {'param1': 2000, 'param2': 0.008637311588779027}
Higher iteration... returning...
Optimization Iteration: 106
Running with params: {'param1': 4400, 'param2': 0.01771996618100981}
Higher iteration... returning...
Optimization Iteration: 107
Running with params: {'param1': 6200, 'param2': 0.00711843842820505}
Higher iteration... returning...
Optimization Iteration: 108
Running with params: {'param1': 100, 'param2': 0.005372699917356236}
Lower learning rate.. returning... Best: 0.04974505577930725, Proposed: 0.005372699917356236
Optimization Iteration: 109
Running with params: {'param1': 300, 'param2': 0.01342545523305666}
Higher iteration... returning...
Optimization Iteration: 110
Running with params: {'param1': 500, 'param2': 0.00023475408044489954}
Higher iteration... returning...
Optimization Iteration: 111
Running with params: {'param1': 200, 'param2': 0.0031582017167030066}
Higher iteration... returning...
Optimization Iteration: 112
Running with params: {'param1': 100, 'param2': 0.04884813830063751}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04884813830063751
Launching 30 jobs, 30 in parallel
Iter 5...
Iter 0...
Iter 1...
Iter 6...
Iter 2...
Iter 3...
Iter 7...
Iter 4...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 12...
Iter 13...
Iter 18...
Iter 14...
Iter 19...
Iter 15...
Iter 16...
Iter 20...
Iter 17...
Iter 21...
Iter 22...
Iter 23...
Iter 24...
Iter 25...
Iter 26...
Iter 27...
Iter 29...
Iter 28...
Timings: Avg: 2.708333333333333, Max: 2.77, Min: 2.61
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.708333333333333, Max: 2.77, Min: 2.61
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: 2.708333333333333
Score: 2.708333333333333
Best-score: 2.708333333333333
Best-param: {'param1': 100, 'param2': 0.04884813830063751}
Optimization Iteration: 113
Running with params: {'param1': 100, 'param2': 0.00027823794111031693}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.00027823794111031693
Optimization Iteration: 114
Running with params: {'param1': 100, 'param2': 0.021561695505439387}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.021561695505439387
Optimization Iteration: 115
Running with params: {'param1': 300, 'param2': 0.026502964108260217}
Higher iteration... returning...
Optimization Iteration: 116
Running with params: {'param1': 200, 'param2': 0.00045805129547663254}
Higher iteration... returning...
Optimization Iteration: 117
Running with params: {'param1': 100, 'param2': 0.03599473850084472}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.03599473850084472
Optimization Iteration: 118
Running with params: {'param1': 400, 'param2': 0.0488813783494932}
Higher iteration... returning...
Optimization Iteration: 119
Running with params: {'param1': 200, 'param2': 0.00020260058757379858}
Higher iteration... returning...
Optimization Iteration: 120
Running with params: {'param1': 100, 'param2': 0.01586025366431755}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.01586025366431755
Optimization Iteration: 121
Running with params: {'param1': 100, 'param2': 0.030395053000474063}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.030395053000474063
Optimization Iteration: 122
Running with params: {'param1': 200, 'param2': 0.024900090232933113}
Higher iteration... returning...
Optimization Iteration: 123
Running with params: {'param1': 1300, 'param2': 0.019995049143742286}
Higher iteration... returning...
Optimization Iteration: 124
Running with params: {'param1': 300, 'param2': 0.04246131853396521}
Higher iteration... returning...
Optimization Iteration: 125
Running with params: {'param1': 100, 'param2': 0.010963803657729069}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.010963803657729069
Optimization Iteration: 126
Running with params: {'param1': 2800, 'param2': 0.00136516469115342}
Higher iteration... returning...
Optimization Iteration: 127
Running with params: {'param1': 400, 'param2': 0.0023865865155524146}
Higher iteration... returning...
Optimization Iteration: 128
Running with params: {'param1': 100, 'param2': 0.004087851499987134}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.004087851499987134
Optimization Iteration: 129
Running with params: {'param1': 200, 'param2': 0.012319531607678548}
Higher iteration... returning...
Optimization Iteration: 130
Running with params: {'param1': 700, 'param2': 0.006167923080789473}
Higher iteration... returning...
Optimization Iteration: 131
Running with params: {'param1': 500, 'param2': 0.023187574604783153}
Higher iteration... returning...
Optimization Iteration: 132
Running with params: {'param1': 100, 'param2': 0.04962557684386893}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04962557684386893
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 10...
Iter 7...
Iter 11...
Iter 8...
Iter 9...
Iter 12...
Iter 13...
Iter 14...
Iter 15...
Iter 16...
Iter 20...
Iter 17...
Iter 18...
Iter 19...
Iter 23...
Iter 24...
Iter 21...
Iter 25...
Iter 22...
Iter 26...
Iter 27...
Iter 29...
Iter 28...
Timings: Avg: 2.727333333333333, Max: 2.77, Min: 2.62
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.727333333333333, Max: 2.77, Min: 2.62
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: 2.727333333333333
Score: 2.727333333333333
Best-score: 2.708333333333333
Best-param: {'param1': 100, 'param2': 0.04884813830063751}
Optimization Iteration: 133
Running with params: {'param1': 200, 'param2': 0.03523763129029094}
Higher iteration... returning...
Optimization Iteration: 134
Running with params: {'param1': 100, 'param2': 0.0019618552463175087}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.0019618552463175087
Optimization Iteration: 135
Running with params: {'param1': 900, 'param2': 0.02876057912133692}
Higher iteration... returning...
Optimization Iteration: 136
Running with params: {'param1': 100, 'param2': 0.007964673561906584}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.007964673561906584
Optimization Iteration: 137
Running with params: {'param1': 3600, 'param2': 0.00992617504106851}
Higher iteration... returning...
Optimization Iteration: 138
Running with params: {'param1': 300, 'param2': 0.018008269088833743}
Higher iteration... returning...
Optimization Iteration: 139
Running with params: {'param1': 100, 'param2': 0.014263605602123168}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.014263605602123168
Optimization Iteration: 140
Running with params: {'param1': 200, 'param2': 0.03232955563010594}
Higher iteration... returning...
Optimization Iteration: 141
Running with params: {'param1': 100, 'param2': 0.04569229328932203}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04569229328932203
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 13...
Iter 14...
Iter 15...
Iter 10...
Iter 16...
Iter 12...
Iter 11...
Iter 17...
Iter 18...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 26...
Iter 23...
Iter 27...
Iter 29...
Iter 28...
Iter 24...
Iter 25...
Timings: Avg: 2.773333333333334, Max: 2.8000000000000003, Min: 2.7
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.773333333333334, Max: 2.8000000000000003, Min: 2.7
Variance (0.0) 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: 2.773333333333334
Score: 2.773333333333334
Best-score: 2.708333333333333
Best-param: {'param1': 100, 'param2': 0.04884813830063751}
Optimization Iteration: 142
Running with params: {'param1': 1900, 'param2': 0.0008270038426418585}
Higher iteration... returning...
Optimization Iteration: 143
Running with params: {'param1': 200, 'param2': 0.0010500272827017555}
Higher iteration... returning...
Optimization Iteration: 144
Running with params: {'param1': 1500, 'param2': 0.03802765063538697}
Higher iteration... returning...
Optimization Iteration: 145
Running with params: {'param1': 100, 'param2': 0.025910299457714205}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.025910299457714205
Optimization Iteration: 146
Running with params: {'param1': 100, 'param2': 0.04229656297217707}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.04229656297217707
Optimization Iteration: 147
Running with params: {'param1': 100, 'param2': 0.020612698676054787}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.020612698676054787
Optimization Iteration: 148
Running with params: {'param1': 100, 'param2': 0.016493898759448476}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.016493898759448476
Optimization Iteration: 149
Running with params: {'param1': 100, 'param2': 0.03126379258634991}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.03126379258634991
Optimization Iteration: 150
Running with params: {'param1': 100, 'param2': 0.04815566537839198}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04815566537839198
Launching 30 jobs, 30 in parallel
Iter 3...
Iter 0...
Iter 4...
Iter 1...
Iter 2...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 16...
Iter 12...
Iter 13...
Iter 14...
Iter 19...
Iter 15...
Iter 20...
Iter 21...
Iter 22...
Iter 17...
Iter 18...
Iter 23...
Iter 28...
Iter 29...
Iter 24...
Iter 25...
Iter 26...
Iter 27...
Timings: Avg: 2.714, Max: 2.75, Min: 2.6300000000000003
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.714, Max: 2.75, Min: 2.6300000000000003
Variance (7.52316384526264e-37) too small, using delta distribution
Variance (1.0833355937178202e-34) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 2.714
Score: 2.714
Best-score: 2.708333333333333
Best-param: {'param1': 100, 'param2': 0.04884813830063751}
Upto iteration 150: {'param1': 100.0, 'param2': 0.04884813830063751}
Optimization Iteration: 151
Running with params: {'param1': 100, 'param2': 0.04893152981808612}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04893152981808612
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 3...
Iter 4...
Iter 5...
Iter 6...
Iter 7...
Iter 8...
Iter 9...
Iter 10...
Iter 14...
Iter 11...
Iter 12...
Iter 15...
Iter 16...
Iter 17...
Iter 13...
Iter 18...
Iter 19...
Iter 20...
Iter 21...
Iter 22...
Iter 27...
Iter 28...
Iter 29...
Iter 23...
Iter 24...
Iter 25...
Iter 26...
Timings: Avg: 2.7316666666666665, Max: 2.7600000000000002, Min: 2.67
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.7316666666666665, Max: 2.7600000000000002, Min: 2.67
Variance (6.770847460736376e-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: 2.7316666666666665
Score: 2.7316666666666665
Best-score: 2.708333333333333
Best-param: {'param1': 100, 'param2': 0.04884813830063751}
Optimization Iteration: 152
Running with params: {'param1': 200, 'param2': 0.04998188511836793}
Higher iteration... returning...
Optimization Iteration: 153
Running with params: {'param1': 100, 'param2': 0.02320273443721974}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.02320273443721974
Optimization Iteration: 154
Running with params: {'param1': 100, 'param2': 0.03750965879485499}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.03750965879485499
Optimization Iteration: 155
Running with params: {'param1': 200, 'param2': 0.032816473146870535}
Higher iteration... returning...
Optimization Iteration: 156
Running with params: {'param1': 100, 'param2': 0.02738315169441084}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.02738315169441084
Optimization Iteration: 157
Running with params: {'param1': 200, 'param2': 0.04173215970191323}
Higher iteration... returning...
Optimization Iteration: 158
Running with params: {'param1': 100, 'param2': 0.04977925308381479}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04977925308381479
Launching 30 jobs, 30 in parallel
Iter 0...
Iter 1...
Iter 2...
Iter 6...
Iter 3...
Iter 7...
Iter 4...
Iter 5...
Iter 8...
Iter 9...
Iter 10...
Iter 11...
Iter 12...
Iter 13...
Iter 19...
Iter 14...
Iter 15...
Iter 20...
Iter 21...
Iter 17...
Iter 22...
Iter 18...
Iter 16...
Iter 23...
Iter 25...
Iter 24...
Iter 26...
Iter 29...
Iter 28...
Iter 27...
Timings: Avg: 2.724666666666667, Max: 2.77, Min: 2.6
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.724666666666667, Max: 2.77, Min: 2.6
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: 2.724666666666667
Score: 2.724666666666667
Best-score: 2.708333333333333
Best-param: {'param1': 100, 'param2': 0.04884813830063751}
Optimization Iteration: 159
Running with params: {'param1': 100, 'param2': 0.019092137939384548}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.019092137939384548
Optimization Iteration: 160
Running with params: {'param1': 100, 'param2': 0.012491629891296341}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.012491629891296341
Optimization Iteration: 161
Running with params: {'param1': 100, 'param2': 0.00015062807835126735}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.00015062807835126735
Optimization Iteration: 162
Running with params: {'param1': 300, 'param2': 0.015590968764938633}
Higher iteration... returning...
Optimization Iteration: 163
Running with params: {'param1': 200, 'param2': 0.049942973780962685}
Higher iteration... returning...
Optimization Iteration: 164
Running with params: {'param1': 100, 'param2': 0.008837584740616125}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.008837584740616125
Optimization Iteration: 165
Running with params: {'param1': 100, 'param2': 0.028577646602021257}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.028577646602021257
Optimization Iteration: 166
Running with params: {'param1': 200, 'param2': 0.022525017493734055}
Higher iteration... returning...
Optimization Iteration: 167
Running with params: {'param1': 100, 'param2': 0.004729767866515336}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.004729767866515336
Optimization Iteration: 168
Running with params: {'param1': 100, 'param2': 0.03760091797818772}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.03760091797818772
Optimization Iteration: 169
Running with params: {'param1': 600, 'param2': 0.034228515808569705}
Higher iteration... returning...
Optimization Iteration: 170
Running with params: {'param1': 200, 'param2': 0.0005750628463997328}
Higher iteration... returning...
Optimization Iteration: 171
Running with params: {'param1': 100, 'param2': 0.0003839552272780404}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.0003839552272780404
Optimization Iteration: 172
Running with params: {'param1': 300, 'param2': 0.006900882718863281}
Higher iteration... returning...
Optimization Iteration: 173
Running with params: {'param1': 100, 'param2': 0.024927888682624456}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.024927888682624456
Optimization Iteration: 174
Running with params: {'param1': 200, 'param2': 0.0031497578537458847}
Higher iteration... returning...
Optimization Iteration: 175
Running with params: {'param1': 400, 'param2': 0.010907904069260479}
Higher iteration... returning...
Optimization Iteration: 176
Running with params: {'param1': 1100, 'param2': 0.04287420950491051}
Higher iteration... returning...
Optimization Iteration: 177
Running with params: {'param1': 100, 'param2': 0.013687528928854801}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.013687528928854801
Optimization Iteration: 178
Running with params: {'param1': 100, 'param2': 0.01968071528063742}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.01968071528063742
Optimization Iteration: 179
Running with params: {'param1': 200, 'param2': 0.02856670043785736}
Higher iteration... returning...
Optimization Iteration: 180
Running with params: {'param1': 100, 'param2': 0.015164693826638856}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.015164693826638856
Optimization Iteration: 181
Running with params: {'param1': 300, 'param2': 0.04513203034657019}
Higher iteration... returning...
Optimization Iteration: 182
Running with params: {'param1': 100, 'param2': 0.005665723211860151}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.005665723211860151
Optimization Iteration: 183
Running with params: {'param1': 100, 'param2': 0.04930052610319491}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597921696/assert_10417934_100_0.04930052610319491
Launching 30 jobs, 30 in parallel
Iter 1...
Iter 0...
Iter 2...
Iter 6...
Iter 3...
Iter 7...
Iter 4...
Iter 8...
Iter 5...
Iter 11...
Iter 9...
Iter 12...
Iter 10...
Iter 14...
Iter 13...
Iter 15...
Iter 19...
Iter 17...
Iter 16...
Iter 18...
Iter 20...
Iter 23...
Iter 24...
Iter 25...
Iter 21...
Iter 22...
Iter 26...
Iter 27...
Iter 29...
Iter 28...
Timings: Avg: 2.717999999999999, Max: 2.78, Min: 2.5700000000000003
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 2.717999999999999, Max: 2.78, Min: 2.5700000000000003
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: 2.717999999999999
Score: 2.717999999999999
Best-score: 2.708333333333333
Best-param: {'param1': 100, 'param2': 0.04884813830063751}
Optimization Iteration: 184
Running with params: {'param1': 200, 'param2': 0.01808174646266928}
Higher iteration... returning...
Optimization Iteration: 185
Running with params: {'param1': 100, 'param2': 0.0035818608154801913}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.0035818608154801913
Optimization Iteration: 186
Running with params: {'param1': 100, 'param2': 0.032656875910734386}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.032656875910734386
Optimization Iteration: 187
Running with params: {'param1': 200, 'param2': 0.02272792434721605}
Higher iteration... returning...
Optimization Iteration: 188
Running with params: {'param1': 100, 'param2': 0.039447639555905294}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.039447639555905294
Optimization Iteration: 189
Running with params: {'param1': 300, 'param2': 0.011765821531798538}
Higher iteration... returning...
Optimization Iteration: 190
Running with params: {'param1': 100, 'param2': 0.025957222698660853}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.025957222698660853
Optimization Iteration: 191
Running with params: {'param1': 200, 'param2': 0.049790353024305574}
Higher iteration... returning...
Optimization Iteration: 192
Running with params: {'param1': 100, 'param2': 0.0001151352084463388}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.0001151352084463388
Optimization Iteration: 193
Running with params: {'param1': 6300, 'param2': 0.01688984429181367}
Higher iteration... returning...
Optimization Iteration: 194
Running with params: {'param1': 100, 'param2': 0.03611085114101447}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.03611085114101447
Optimization Iteration: 195
Running with params: {'param1': 200, 'param2': 0.022048846574802935}
Higher iteration... returning...
Optimization Iteration: 196
Running with params: {'param1': 100, 'param2': 0.009990249825291335}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.009990249825291335
Optimization Iteration: 197
Running with params: {'param1': 100, 'param2': 0.04381245734856821}
Lower learning rate.. returning... Best: 0.04884813830063751, Proposed: 0.04381245734856821
Optimization Iteration: 198
Running with params: {'param1': 400, 'param2': 0.029933348666242986}
Higher iteration... returning...
Optimization Iteration: 199
Running with params: {'param1': 500, 'param2': 0.008615996138771963}
Higher iteration... returning...
Optimization Iteration: 200
Running with params: {'param1': 200, 'param2': 0.0016754537838466466}
Higher iteration... returning...
Upto iteration 200: {'param1': 100.0, 'param2': 0.04884813830063751}
Breaking...
{'param1': 100.0, 'param2': 0.04884813830063751}
Best score: 2.708333333333333
Repeated params: 0
Trials: 201
Best param {'param1': 100.0, 'param2': 0.04884813830063751}
Reduction: 94.03547150974144%
Speedup: 16.765784615384618x
Optimizer time: 157.15998673439026
