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_reparameterized_three_layers
Params: param1,241,32,ParamType.ITER,10000
param2,241,39,ParamType.LR,0.0015
Assertion: assert_equal(0.0, max_log_sig_error, prec=0.04)
Original runtime: 182.678
>>Getting original runtime
Optimization Iteration: 1
Running with params: {'param1': 10000, 'param2': 0.0015}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_10000_0.0015
Launching 30 jobs, 30 in parallel
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Timings: Avg: 179.40733333333336, Max: 186.6, Min: 174.85
Passed tests : 30
Failed tests : 0
Converged: True
Convergence score: 0.0
updating...
Evaluating 30 values out of 30
Overall-timings: Avg: 179.40733333333336, Max: 186.6, Min: 174.85
Variance (1.88079096131566e-37) too small, using delta distribution
Variance (3.5558704112374197e-37) too small, using delta distribution
Variance (9.018245722714737e-39) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 179.40733333333336
Score: 179.40733333333336
Best-score: 179.40733333333336
Best-param: {'param1': 10000, 'param2': 0.0015}
>>Setting original runtime to 179.40733333333336
Optimization Iteration: 1
Running with params: {'param1': 200, 'param2': 0.0003459306412784036}
Lower learning rate.. returning... Best: 0.0015, Proposed: 0.0003459306412784036
Optimization Iteration: 2
Running with params: {'param1': 4000, 'param2': 0.0003904304240473664}
Lower learning rate.. returning... Best: 0.0015, Proposed: 0.0003904304240473664
Optimization Iteration: 3
Running with params: {'param1': 4000, 'param2': 0.002839041804195645}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_4000_0.002839041804195645
Launching 30 jobs, 30 in parallel
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Timings: Avg: 72.904, Max: 75.98, Min: 71.63000000000001
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: 3.0183970186822937
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 72.92716666666666, Max: 75.98, Min: 71.24
Passed tests : 60
Failed tests : 0
Converged: False
Convergence score: 2.2450867483845744
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 72.78233333333333, Max: 75.98, Min: 70.17
Passed tests : 90
Failed tests : 0
Converged: True
Convergence score: 0.9421114395319916
updating...
Evaluating 90 values out of 90
Overall-timings: Avg: 72.78233333333333, Max: 75.98, Min: 70.17
Variance (2.079736849668161e-34) too small, using delta distribution
Variance (5.884002278282673e-37) too small, using delta distribution
Variance (1.5856929003279815e-38) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 72.78233333333333
Score: 72.78233333333333
Best-score: 72.78233333333333
Best-param: {'param1': 4000, 'param2': 0.002839041804195645}
Optimization Iteration: 4
Running with params: {'param1': 1500, 'param2': 0.00732425376797875}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_1500_0.00732425376797875
Launching 30 jobs, 30 in parallel
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Timings: Avg: 28.901000000000007, Max: 30.72, Min: 28.19
Passed tests : 0
Failed tests : 30
Half of samples failed, exiting...
All-Passed: False
Probabilty of failure: 1.0
Runtime: 10000.0
Score: 3.4028234663852886e+38
Best-score: 72.78233333333333
Best-param: {'param1': 4000, 'param2': 0.002839041804195645}
Optimization Iteration: 5
Running with params: {'param1': 500, 'param2': 0.02726962005885139}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_500_0.02726962005885139
Launching 30 jobs, 30 in parallel
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Timings: Avg: 11.102333333333332, Max: 11.65, Min: 10.77
Passed tests : 0
Failed tests : 30
Half of samples failed, exiting...
All-Passed: False
Probabilty of failure: 1.0
Runtime: 10000.0
Score: 3.4028234663852886e+38
Best-score: 72.78233333333333
Best-param: {'param1': 4000, 'param2': 0.002839041804195645}
Optimization Iteration: 6
Running with params: {'param1': 500, 'param2': 0.05029417367163758}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_500_0.05029417367163758
Launching 30 jobs, 30 in parallel
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Timings: Avg: 10.872999999999998, Max: 11.13, Min: 10.68
Passed tests : 30
Failed tests : 0
Converged: False
Convergence score: 1.7588790717738005
Continuing to next batch...
Launching 30 jobs, 30 in parallel
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Timings: Avg: 10.874833333333335, Max: 11.14, Min: 10.66
Passed tests : 60
Failed tests : 0
Converged: True
Convergence score: 0.9513029883089881
updating...
Evaluating 60 values out of 60
Overall-timings: Avg: 10.874833333333335, Max: 11.14, Min: 10.66
Variance (1.3006045655690052e-33) too small, using delta distribution
Variance (1.720923729603829e-36) too small, using delta distribution
Variance (7.052966104933725e-37) too small, using delta distribution
Probability of fail : 0.0
All-Passed: True
Probabilty of failure: 0.0
Runtime: 10.874833333333335
Score: 10.874833333333335
Best-score: 10.874833333333335
Best-param: {'param1': 500, 'param2': 0.05029417367163758}
Optimization Iteration: 7
Running with params: {'param1': 400, 'param2': 0.0013611683993555053}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0013611683993555053
Optimization Iteration: 8
Running with params: {'param1': 1000, 'param2': 0.0038810983525463904}
Higher iteration... returning...
Optimization Iteration: 9
Running with params: {'param1': 4000, 'param2': 0.002446247403741788}
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Optimization Iteration: 10
Running with params: {'param1': 6500, 'param2': 0.004523124330650011}
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Optimization Iteration: 11
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Optimization Iteration: 12
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Optimization Iteration: 13
Running with params: {'param1': 500, 'param2': 0.0010712990509861764}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0010712990509861764
Optimization Iteration: 14
Running with params: {'param1': 1900, 'param2': 0.004965786699589306}
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Optimization Iteration: 17
Running with params: {'param1': 100, 'param2': 0.0004157960298322195}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0004157960298322195
Optimization Iteration: 18
Running with params: {'param1': 600, 'param2': 0.02593928227845106}
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Optimization Iteration: 19
Running with params: {'param1': 400, 'param2': 0.0003144437586947712}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0003144437586947712
Optimization Iteration: 20
Running with params: {'param1': 600, 'param2': 0.00013355879210730608}
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Optimization Iteration: 21
Running with params: {'param1': 200, 'param2': 0.06409617732799412}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_200_0.06409617732799412
Launching 30 jobs, 30 in parallel
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Timings: Avg: 5.846666666666668, Max: 6.0, Min: 5.66
Passed tests : 0
Failed tests : 30
Half of samples failed, exiting...
All-Passed: False
Probabilty of failure: 1.0
Runtime: 10000.0
Score: 3.4028234663852886e+38
Best-score: 10.874833333333335
Best-param: {'param1': 500, 'param2': 0.05029417367163758}
Optimization Iteration: 22
Running with params: {'param1': 8700, 'param2': 0.011315986230771497}
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Optimization Iteration: 23
Running with params: {'param1': 200, 'param2': 0.0018010879832651896}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0018010879832651896
Optimization Iteration: 24
Running with params: {'param1': 1000, 'param2': 0.013770701783059733}
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Optimization Iteration: 25
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Optimization Iteration: 26
Running with params: {'param1': 100, 'param2': 0.011247539018354936}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.011247539018354936
Optimization Iteration: 27
Running with params: {'param1': 9200, 'param2': 0.0007015793088591266}
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Optimization Iteration: 28
Running with params: {'param1': 300, 'param2': 0.00010737766342349644}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00010737766342349644
Optimization Iteration: 29
Running with params: {'param1': 700, 'param2': 0.0024895138523194165}
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Optimization Iteration: 31
Running with params: {'param1': 300, 'param2': 0.0529150795088984}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_300_0.0529150795088984
Launching 30 jobs, 30 in parallel
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Timings: Avg: 7.572666666666667, Max: 7.65, Min: 7.5
Passed tests : 0
Failed tests : 30
Half of samples failed, exiting...
All-Passed: False
Probabilty of failure: 1.0
Runtime: 10000.0
Score: 3.4028234663852886e+38
Best-score: 10.874833333333335
Best-param: {'param1': 500, 'param2': 0.05029417367163758}
Optimization Iteration: 32
Running with params: {'param1': 3000, 'param2': 0.014919178713650137}
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Optimization Iteration: 35
Running with params: {'param1': 100, 'param2': 0.001633632714016818}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.001633632714016818
Optimization Iteration: 36
Running with params: {'param1': 300, 'param2': 0.09874376436498614}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_300_0.09874376436498614
Launching 30 jobs, 30 in parallel
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Timings: Avg: 7.551333333333334, Max: 7.739999999999999, Min: 7.33
Passed tests : 0
Failed tests : 30
Half of samples failed, exiting...
All-Passed: False
Probabilty of failure: 1.0
Runtime: 10000.0
Score: 3.4028234663852886e+38
Best-score: 10.874833333333335
Best-param: {'param1': 500, 'param2': 0.05029417367163758}
Optimization Iteration: 37
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Optimization Iteration: 38
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Optimization Iteration: 45
Running with params: {'param1': 400, 'param2': 0.021808804273431653}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.021808804273431653
Optimization Iteration: 46
Running with params: {'param1': 200, 'param2': 0.04008007564100418}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.04008007564100418
Optimization Iteration: 47
Running with params: {'param1': 3500, 'param2': 0.0004518696651949728}
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Optimization Iteration: 48
Running with params: {'param1': 100, 'param2': 0.00026928714836609914}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00026928714836609914
Optimization Iteration: 49
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Optimization Iteration: 50
Running with params: {'param1': 1600, 'param2': 0.0029924842819479625}
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Upto iteration 50: {'param1': 500.0, 'param2': 0.05029417367163758}
Optimization Iteration: 51
Running with params: {'param1': 500, 'param2': 0.09924369880313232}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_500_0.09924369880313232
Launching 30 jobs, 30 in parallel
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Timings: Avg: 11.124, Max: 11.34, Min: 10.88
Passed tests : 0
Failed tests : 30
Half of samples failed, exiting...
All-Passed: False
Probabilty of failure: 1.0
Runtime: 10000.0
Score: 3.4028234663852886e+38
Best-score: 10.874833333333335
Best-param: {'param1': 500, 'param2': 0.05029417367163758}
Optimization Iteration: 52
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Optimization Iteration: 55
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Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.004046194581677083
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Optimization Iteration: 57
Running with params: {'param1': 200, 'param2': 0.002421622699202028}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.002421622699202028
Optimization Iteration: 58
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Optimization Iteration: 60
Running with params: {'param1': 500, 'param2': 0.0012843942889190212}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0012843942889190212
Optimization Iteration: 61
Running with params: {'param1': 300, 'param2': 0.009793863797611334}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.009793863797611334
Optimization Iteration: 62
Running with params: {'param1': 100, 'param2': 0.01763308739596586}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.01763308739596586
Optimization Iteration: 63
Running with params: {'param1': 3500, 'param2': 0.006146084072936561}
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Optimization Iteration: 64
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Optimization Iteration: 65
Running with params: {'param1': 700, 'param2': 0.012605710618091072}
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Optimization Iteration: 66
Running with params: {'param1': 200, 'param2': 0.00023181556753151418}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00023181556753151418
Optimization Iteration: 67
Running with params: {'param1': 200, 'param2': 0.00011154649116420919}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00011154649116420919
Optimization Iteration: 68
Running with params: {'param1': 100, 'param2': 0.00033857498490724757}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00033857498490724757
Optimization Iteration: 69
Running with params: {'param1': 100, 'param2': 0.0005444672831224452}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0005444672831224452
Optimization Iteration: 70
Running with params: {'param1': 300, 'param2': 0.0008423613931925138}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0008423613931925138
Optimization Iteration: 71
Running with params: {'param1': 200, 'param2': 0.0004788045256512722}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0004788045256512722
Optimization Iteration: 72
Running with params: {'param1': 100, 'param2': 0.00014129833364505466}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00014129833364505466
Optimization Iteration: 73
Running with params: {'param1': 400, 'param2': 0.0002026451441824213}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0002026451441824213
Optimization Iteration: 74
Running with params: {'param1': 500, 'param2': 0.025049676070191696}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.025049676070191696
Optimization Iteration: 75
Running with params: {'param1': 300, 'param2': 0.0044837991533916}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0044837991533916
Optimization Iteration: 76
Running with params: {'param1': 900, 'param2': 0.0003460723046183964}
Higher iteration... returning...
Optimization Iteration: 77
Running with params: {'param1': 9900, 'param2': 0.047858425789983734}
Higher iteration... returning...
Optimization Iteration: 78
Running with params: {'param1': 1900, 'param2': 0.0021470566833411064}
Higher iteration... returning...
Optimization Iteration: 79
Running with params: {'param1': 100, 'param2': 0.0588638177535499}
Logdir: /mnt/batch/tasks/workitems/optwseed/job-1/Task_pyro/wd/borntobeflaky/tool/logs/optim_1597896455_pyro/run_1597910580/assert_65698759_100_0.0588638177535499
Launching 30 jobs, 30 in parallel
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Timings: Avg: 4.125666666666667, Max: 4.180000000000001, Min: 4.05
Passed tests : 0
Failed tests : 30
Half of samples failed, exiting...
All-Passed: False
Probabilty of failure: 1.0
Runtime: 10000.0
Score: 3.4028234663852886e+38
Best-score: 10.874833333333335
Best-param: {'param1': 500, 'param2': 0.05029417367163758}
Optimization Iteration: 80
Running with params: {'param1': 200, 'param2': 0.007561409002242461}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.007561409002242461
Optimization Iteration: 81
Running with params: {'param1': 600, 'param2': 0.034889053391076716}
Higher iteration... returning...
Optimization Iteration: 82
Running with params: {'param1': 300, 'param2': 0.0013035286977605457}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0013035286977605457
Optimization Iteration: 83
Running with params: {'param1': 8200, 'param2': 0.0008060569186595335}
Higher iteration... returning...
Optimization Iteration: 84
Running with params: {'param1': 5800, 'param2': 0.015304804073679984}
Higher iteration... returning...
Optimization Iteration: 85
Running with params: {'param1': 400, 'param2': 0.00028295320979514216}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00028295320979514216
Optimization Iteration: 86
Running with params: {'param1': 1100, 'param2': 0.0035703035267599004}
Higher iteration... returning...
Optimization Iteration: 87
Running with params: {'param1': 200, 'param2': 0.001698107287692194}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.001698107287692194
Optimization Iteration: 88
Running with params: {'param1': 700, 'param2': 0.00039732943298335173}
Higher iteration... returning...
Optimization Iteration: 89
Running with params: {'param1': 100, 'param2': 0.010368452976034573}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.010368452976034573
Optimization Iteration: 90
Running with params: {'param1': 1800, 'param2': 0.0027600753993768322}
Higher iteration... returning...
Optimization Iteration: 91
Running with params: {'param1': 400, 'param2': 0.0011189771989024062}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0011189771989024062
Optimization Iteration: 92
Running with params: {'param1': 500, 'param2': 0.0005853573156519268}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0005853573156519268
Optimization Iteration: 93
Running with params: {'param1': 1400, 'param2': 0.02233665400597815}
Higher iteration... returning...
Optimization Iteration: 94
Running with params: {'param1': 4500, 'param2': 0.001947419108396519}
Higher iteration... returning...
Optimization Iteration: 95
Running with params: {'param1': 300, 'param2': 0.0009832085803283474}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.0009832085803283474
Optimization Iteration: 96
Running with params: {'param1': 900, 'param2': 0.0001016187336153071}
Higher iteration... returning...
Optimization Iteration: 97
Running with params: {'param1': 600, 'param2': 0.00012008561648112491}
Higher iteration... returning...
Optimization Iteration: 98
Running with params: {'param1': 2400, 'param2': 0.08573474037610682}
Higher iteration... returning...
Optimization Iteration: 99
Running with params: {'param1': 200, 'param2': 0.00017518256619969582}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.00017518256619969582
Optimization Iteration: 100
Running with params: {'param1': 100, 'param2': 0.006518295221404302}
Lower learning rate.. returning... Best: 0.05029417367163758, Proposed: 0.006518295221404302
Upto iteration 100: {'param1': 500.0, 'param2': 0.05029417367163758}
Breaking...
{'param1': 500.0, 'param2': 0.05029417367163758}
Best score: 10.874833333333335
Repeated params: 0
Trials: 101
Best param {'param1': 500.0, 'param2': 0.05029417367163758}
Reduction: 93.93846776980503%
Speedup: 16.497478888565343x
Optimizer time: 518.6832683086395
