copying files to /scratch...
starting benchmark...
/scratch/knn/venv/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
running only annoy
order: [Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 2000])
Got a train set of size (60000 * 784)
Built index in 23.32
Index size:  305104.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0186881290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1617537830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1311.92 < 1383.89
  -> Decision False in time 0.4900000000, query time of that 0.4857847600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0170236930, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1528.5 < 1572.83
  -> Decision False in time 0.0200000000, query time of that 0.0189139030, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1287.24 < 1356.65
  -> Decision False in time 0.1300000000, query time of that 0.1194206790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0184435620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2109.7 < 2135.02
  -> Decision False in time 0.0200000000, query time of that 0.0197807660, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1026.47 < 1063.3
  -> Decision False in time 0.0400000000, query time of that 0.0197580260, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 400])
Got a train set of size (60000 * 784)
Built index in 18.290000000000006
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0824850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0109555890, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1160.77 < 1191.22
  -> Decision False in time 0.0500000000, query time of that 0.0486523610, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1958.31 < 2125.41
  -> Decision False in time 0.0800000000, query time of that 0.0807677020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
723.537 < 731.393
  -> Decision False in time 0.0100000000, query time of that 0.0116108430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
512.088 < 694.931
  -> Decision False in time 0.0200000000, query time of that 0.0172765630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1823.77 < 1847.98
  -> Decision False in time 0.0200000000, query time of that 0.0111097540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1126.26 < 1138.59
  -> Decision False in time 0.0100000000, query time of that 0.0118426240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
925.739 < 963.916
  -> Decision False in time 0.0500000000, query time of that 0.0129000820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
937.741 < 1057.4
  -> Decision False in time 0.0100000000, query time of that 0.0121757550, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 4000])
Got a train set of size (60000 * 784)
Built index in 65.54999999999998
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0346319230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3169555510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1368.08 < 1377.69
  -> Decision False in time 0.3800000000, query time of that 0.3679715180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0350513240, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3648899520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1481.54 < 1524.54
  -> Decision False in time 0.4500000000, query time of that 0.4453423450, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0400096520, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1155.9 < 1202.38
  -> Decision False in time 0.0400000000, query time of that 0.0421844320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1122.5 < 1130.64
  -> Decision False in time 0.1200000000, query time of that 0.0671392780, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 100])
Got a train set of size (60000 * 784)
Built index in 18.07000000000005
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0115270840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1251.81 < 1311.82
  -> Decision False in time 0.0600000000, query time of that 0.0573827550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1006.42 < 1045.8
  -> Decision False in time 0.0800000000, query time of that 0.0802772950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1981.56 < 2007.89
  -> Decision False in time 0.0200000000, query time of that 0.0102367510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1265.66 < 1472.61
  -> Decision False in time 0.0100000000, query time of that 0.0109448620, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
987.003 < 1002.99
  -> Decision False in time 0.0200000000, query time of that 0.0167992640, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1157.87 < 1187
  -> Decision False in time 0.0200000000, query time of that 0.0113960650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1787.46 < 2108.66
  -> Decision False in time 0.0100000000, query time of that 0.0110808500, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1735.74 < 1760.61
  -> Decision False in time 0.0300000000, query time of that 0.0116853580, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 1000])
Got a train set of size (60000 * 784)
Built index in 33.68000000000001
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0385416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0177256000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1637453050, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1193.03 < 1240.81
  -> Decision False in time 0.2000000000, query time of that 0.1939636870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0190247100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1494.6 < 1507.73
  -> Decision False in time 0.0900000000, query time of that 0.0945797820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1451.12 < 1471.66
  -> Decision False in time 0.1600000000, query time of that 0.1475916780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1196.9 < 1220.31
  -> Decision False in time 0.0200000000, query time of that 0.0197332880, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1663.33 < 1715.37
  -> Decision False in time 0.1000000000, query time of that 0.0343938360, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
691.112 < 733.762
  -> Decision False in time 0.0200000000, query time of that 0.0199566280, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 400])
Got a train set of size (60000 * 784)
Built index in 64.77999999999997
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0217505010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1206.34 < 1276.93
  -> Decision False in time 0.0700000000, query time of that 0.0732867590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1021.38 < 1052.85
  -> Decision False in time 0.1700000000, query time of that 0.1662435630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1468.43 < 1675.62
  -> Decision False in time 0.0200000000, query time of that 0.0188939860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1066.59 < 1168.05
  -> Decision False in time 0.1000000000, query time of that 0.0981580520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1274.29 < 1274.36
  -> Decision False in time 0.0300000000, query time of that 0.0299579420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
929.436 < 1006.83
  -> Decision False in time 0.0300000000, query time of that 0.0237262620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1242.99 < 1273.56
  -> Decision False in time 0.0300000000, query time of that 0.0212873700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1811.3 < 1828.55
  -> Decision False in time 0.0200000000, query time of that 0.0252726730, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200000])
Got a train set of size (60000 * 784)
Built index in 33.489999999999895
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2884834810, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.8100000000, query time of that 2.7967759990, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.8200000000, query time of that 27.7462772390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2750257230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.7800000000, query time of that 2.7737380500, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 28.0100000000, query time of that 27.9226947730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.2899686110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.0000000000, query time of that 2.8702245800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 28.8300000000, query time of that 28.5301906680, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 400])
Got a train set of size (60000 * 784)
Built index in 33.539999999999964
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Reject!
1249.64 < 1276.35
  -> Decision False in time 0.0100000000, query time of that 0.0145001550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1972.84 < 2122.45
  -> Decision False in time 0.0300000000, query time of that 0.0309027130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1265.4 < 1322.06
  -> Decision False in time 0.0500000000, query time of that 0.0452478580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0156798400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
813.31 < 863.36
  -> Decision False in time 0.0100000000, query time of that 0.0154710810, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1469.81 < 1479.31
  -> Decision False in time 0.0300000000, query time of that 0.0226966560, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1289.96 < 1351.77
  -> Decision False in time 0.0200000000, query time of that 0.0150147840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1040.48 < 1044.89
  -> Decision False in time 0.0300000000, query time of that 0.0165107590, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1016.88 < 1018.26
  -> Decision False in time 0.0100000000, query time of that 0.0158704180, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 200])
Got a train set of size (60000 * 784)
Built index in 17.930000000000064
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0109748490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1588.96 < 1774.5
  -> Decision False in time 0.0900000000, query time of that 0.0934045290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
870.274 < 911.024
  -> Decision False in time 0.0300000000, query time of that 0.0245197670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
923.713 < 936.42
  -> Decision False in time 0.0100000000, query time of that 0.0103963730, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2204.85 < 2220.06
  -> Decision False in time 0.0200000000, query time of that 0.0149504420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1696.07 < 1750.2
  -> Decision False in time 0.0200000000, query time of that 0.0173759510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
660.267 < 779.638
  -> Decision False in time 0.0100000000, query time of that 0.0108004630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1173.29 < 1214
  -> Decision False in time 0.0100000000, query time of that 0.0102410310, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
919.419 < 920.407
  -> Decision False in time 0.0100000000, query time of that 0.0118952330, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 40000])
Got a train set of size (60000 * 784)
Built index in 64.84999999999991
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0840011850, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8277236930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.3600000000, query time of that 8.2995035080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0859845510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8900000000, query time of that 0.8665621360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1479.19 < 1573.35
  -> Decision False in time 3.1500000000, query time of that 3.1302070180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.0963966610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1676.6 < 1848.18
  -> Decision False in time 0.9600000000, query time of that 0.9502680290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1345.04 < 1642.15
  -> Decision False in time 0.0900000000, query time of that 0.0868359610, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 400000])
Got a train set of size (60000 * 784)
Built index in 33.960000000000036
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5616987850, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.4100000000, query time of that 5.3918931940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.7500000000, query time of that 53.6638250980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5351771510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3400000000, query time of that 5.3226744320, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.6500000000, query time of that 53.5459093790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.5463222470, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.5000000000, query time of that 5.4093839970, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1434.01 < 1441.53
  -> Decision False in time 21.8100000000, query time of that 21.7745860830, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 10000])
Got a train set of size (60000 * 784)
Built index in 64.96000000000004
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0452193750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.4321090480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3300000000, query time of that 4.2729062990, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0464136370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1766.98 < 1794.35
  -> Decision False in time 0.3500000000, query time of that 0.3477707450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1664.78 < 1676.22
  -> Decision False in time 0.9400000000, query time of that 0.9288893120, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0550918790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1510.95 < 1526.14
  -> Decision False in time 0.0600000000, query time of that 0.0523235990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1293.98 < 1302.82
  -> Decision False in time 0.3200000000, query time of that 0.2232056420, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200])
Got a train set of size (60000 * 784)
Built index in 33.75
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0140990690, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1891.83 < 1999.51
  -> Decision False in time 0.0900000000, query time of that 0.0863190030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1275.55 < 1289.3
  -> Decision False in time 0.0900000000, query time of that 0.0837676220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0145204350, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
992.528 < 1096.96
  -> Decision False in time 0.0300000000, query time of that 0.0264227390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
935.39 < 1104.3
  -> Decision False in time 0.0200000000, query time of that 0.0224307610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1317.05 < 1353.26
  -> Decision False in time 0.0200000000, query time of that 0.0158551490, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1471.27 < 1594.38
  -> Decision False in time 0.0900000000, query time of that 0.0270790630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
993.445 < 1097.05
  -> Decision False in time 0.0200000000, query time of that 0.0167668300, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100])
Got a train set of size (60000 * 784)
Built index in 64.92000000000007
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0209277780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1928195960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1246.85 < 1248.14
  -> Decision False in time 0.6700000000, query time of that 0.6549682290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1306.08 < 1310.16
  -> Decision False in time 0.0200000000, query time of that 0.0202605740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1505.13 < 1509.71
  -> Decision False in time 0.0200000000, query time of that 0.0200842630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
747.282 < 837.034
  -> Decision False in time 0.0500000000, query time of that 0.0453644340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1982.67 < 1989.17
  -> Decision False in time 0.0200000000, query time of that 0.0217139480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
897.312 < 1021.12
  -> Decision False in time 0.0200000000, query time of that 0.0226402370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2080.06 < 2082.61
  -> Decision False in time 0.0300000000, query time of that 0.0240906200, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 400000])
Got a train set of size (60000 * 784)
Built index in 18.06999999999971
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.6214338430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.0600000000, query time of that 6.0530325540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 59.8100000000, query time of that 59.7052188920, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6000000000, query time of that 0.5911408210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.9400000000, query time of that 5.9238571550, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.7600000000, query time of that 59.6626032090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6079395330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.1400000000, query time of that 6.0601653780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 59.6900000000, query time of that 59.4908548940, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 100000])
Got a train set of size (60000 * 784)
Built index in 17.92999999999938
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1675624780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6500000000, query time of that 1.6403688000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.6500000000, query time of that 16.5848095310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1677545970, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6900000000, query time of that 1.6823124880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.7200000000, query time of that 16.6198016650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1838.99 < 1873.08
  -> Decision False in time 0.1800000000, query time of that 0.1837484080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9100000000, query time of that 1.7749581630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 18.1500000000, query time of that 17.7884143850, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 20000])
Got a train set of size (60000 * 784)
Built index in 64.75
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0611092540, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5870864250, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1735.98 < 1754.07
  -> Decision False in time 0.6700000000, query time of that 0.6649268050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0613084400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6207259110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1341.47 < 1383.52
  -> Decision False in time 3.9600000000, query time of that 3.9216523230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0709848160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0500000000, query time of that 0.7794142060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1930.45 < 2018.63
  -> Decision False in time 3.1300000000, query time of that 2.6988140140, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 2000])
Got a train set of size (60000 * 784)
Built index in 64.83999999999924
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0193766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0287104250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2643051200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1341.97 < 1433.25
  -> Decision False in time 0.3600000000, query time of that 0.3522847350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0309808490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1397.22 < 1440.29
  -> Decision False in time 0.3100000000, query time of that 0.2965373180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1838.79 < 1844.61
  -> Decision False in time 0.1200000000, query time of that 0.1169666410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1228.51 < 1251.35
  -> Decision False in time 0.0600000000, query time of that 0.0334119970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1354.15 < 1356.7
  -> Decision False in time 0.0300000000, query time of that 0.0285052670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1150.83 < 1166.75
  -> Decision False in time 0.0300000000, query time of that 0.0284066490, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 200])
Got a train set of size (60000 * 784)
Built index in 64.78999999999996
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Reject!
1499.81 < 1516.34
  -> Decision False in time 0.0200000000, query time of that 0.0202628730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1976.01 < 2016.48
  -> Decision False in time 0.1900000000, query time of that 0.1793404150, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1258.15 < 1259.08
  -> Decision False in time 0.0500000000, query time of that 0.0580758550, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0217168700, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1132.66 < 1153.25
  -> Decision False in time 0.0800000000, query time of that 0.0735621880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1100.12 < 1119.75
  -> Decision False in time 0.0600000000, query time of that 0.0574997530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1414.13 < 1440.44
  -> Decision False in time 0.0400000000, query time of that 0.0253408200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1183.16 < 1190.85
  -> Decision False in time 0.0300000000, query time of that 0.0266771290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1000.7 < 1073.71
  -> Decision False in time 0.0200000000, query time of that 0.0227537040, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 200000])
Got a train set of size (60000 * 784)
Built index in 64.80000000000018
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2634588900, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6800000000, query time of that 2.6791196840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.4400000000, query time of that 26.3652062210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2605290380, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6600000000, query time of that 2.6424229370, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1910.14 < 2002.84
  -> Decision False in time 14.2200000000, query time of that 14.1743382890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.2806772270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8400000000, query time of that 2.7073969340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1434.01 < 1441.53
  -> Decision False in time 1.6400000000, query time of that 1.6281188570, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 100])
Got a train set of size (60000 * 784)
Built index in 33.70000000000073
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0144130930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1837.46 < 1865.94
  -> Decision False in time 0.0900000000, query time of that 0.0791168290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1297.28 < 1370.07
  -> Decision False in time 0.0400000000, query time of that 0.0440122240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1221.09 < 1294.98
  -> Decision False in time 0.0200000000, query time of that 0.0143818940, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1556.73 < 1640.48
  -> Decision False in time 0.0200000000, query time of that 0.0192405240, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1512.73 < 1543.41
  -> Decision False in time 0.0700000000, query time of that 0.0717701940, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1400 < 1446.35
  -> Decision False in time 0.0200000000, query time of that 0.0132996910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1235.54 < 1253.95
  -> Decision False in time 0.0200000000, query time of that 0.0156319670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1177.68 < 1216.89
  -> Decision False in time 0.0200000000, query time of that 0.0144216980, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 2000])
Got a train set of size (60000 * 784)
Built index in 33.719999999999345
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0209989310, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1714.17 < 1726.94
  -> Decision False in time 0.0600000000, query time of that 0.0495141620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1333.41 < 1344.6
  -> Decision False in time 1.5800000000, query time of that 1.5514807580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0223437980, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1932.5 < 1964.69
  -> Decision False in time 0.0700000000, query time of that 0.0662671230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1492.51 < 1528.89
  -> Decision False in time 0.1500000000, query time of that 0.1460106660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1038.22 < 1077.2
  -> Decision False in time 0.0200000000, query time of that 0.0205955510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1705.28 < 1708.65
  -> Decision False in time 0.1900000000, query time of that 0.0669154940, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1165.07 < 1234.5
  -> Decision False in time 0.0700000000, query time of that 0.0243850330, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 1000])
Got a train set of size (60000 * 784)
Built index in 65.02000000000044
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0249033380, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1660.61 < 1666.05
  -> Decision False in time 0.1800000000, query time of that 0.1746984310, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1703.89 < 1724.25
  -> Decision False in time 0.5100000000, query time of that 0.5054606550, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1269.44 < 1295.39
  -> Decision False in time 0.0200000000, query time of that 0.0237815670, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1006.42 < 1022.54
  -> Decision False in time 0.1000000000, query time of that 0.0900636130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1315.93 < 1325.08
  -> Decision False in time 0.0700000000, query time of that 0.0667897790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1143.32 < 1175.57
  -> Decision False in time 0.0200000000, query time of that 0.0272908890, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
963.261 < 995.015
  -> Decision False in time 0.0900000000, query time of that 0.0356083860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
977.693 < 1015
  -> Decision False in time 0.0300000000, query time of that 0.0301718160, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 40000])
Got a train set of size (60000 * 784)
Built index in 33.92000000000007
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0841068420, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7782315190, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8100000000, query time of that 7.7472889910, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0872507760, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8700000000, query time of that 0.8243948250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.0700000000, query time of that 7.9761358730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0846297180, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
961.881 < 1020.85
  -> Decision False in time 0.5700000000, query time of that 0.5591945120, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1148.15 < 1172.89
  -> Decision False in time 2.1800000000, query time of that 2.1177329410, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100000])
Got a train set of size (60000 * 784)
Built index in 65.19999999999891
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1581128680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5249140510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2300000000, query time of that 15.1631594580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1540298790, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5800000000, query time of that 1.5432826910, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.6000000000, query time of that 15.5116191720, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1222.61 < 1227.92
  -> Decision False in time 0.1700000000, query time of that 0.1669942480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1396.49 < 1424.99
  -> Decision False in time 0.3400000000, query time of that 0.3333151360, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1087.12 < 1088.84
  -> Decision False in time 1.2600000000, query time of that 1.2497001390, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 40000])
Got a train set of size (60000 * 784)
Built index in 18.149999999999636
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0006000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0801674180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8100000000, query time of that 0.7965641400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8500000000, query time of that 7.7941422030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0893633430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8200000000, query time of that 0.7961295280, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1340.51 < 1359.1
  -> Decision False in time 5.8700000000, query time of that 5.8302116370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0856324730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1353.18 < 1385.27
  -> Decision False in time 0.1900000000, query time of that 0.1849418370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1619.26 < 1660.79
  -> Decision False in time 3.9300000000, query time of that 3.7968792400, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 400000])
Got a train set of size (60000 * 784)
Built index in 64.65999999999985
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4938555830, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9800000000, query time of that 4.9664678850, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.5300000000, query time of that 49.4503595760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4933888980, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9700000000, query time of that 4.9604517560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.5200000000, query time of that 49.4200745880, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5800000000, query time of that 0.5065153090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.0300000000, query time of that 4.9406781570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1942.47 < 1976.41
  -> Decision False in time 35.0100000000, query time of that 34.9385864410, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 20000])
Got a train set of size (60000 * 784)
Built index in 18.140000000001237
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0513418660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4948284580, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.0000000000, query time of that 4.9371659750, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0526941970, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5153887970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1350.91 < 1533.68
  -> Decision False in time 2.2800000000, query time of that 2.2579685470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0614763020, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1075.67 < 1128.62
  -> Decision False in time 0.1300000000, query time of that 0.1024922510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1214.04 < 1298.01
  -> Decision False in time 0.3900000000, query time of that 0.2790694400, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 10000])
Got a train set of size (60000 * 784)
Built index in 17.909999999999854
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0350964260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3357003120, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1540.04 < 1543.88
  -> Decision False in time 1.4400000000, query time of that 1.4234436190, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0363963480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
975.548 < 992.639
  -> Decision False in time 0.1800000000, query time of that 0.1717965590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1072.14 < 1170.57
  -> Decision False in time 1.5800000000, query time of that 1.5655749560, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1042.99 < 1086.7
  -> Decision False in time 0.1000000000, query time of that 0.0410143270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1265.33 < 1280.31
  -> Decision False in time 0.4400000000, query time of that 0.2321244080, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1342.29 < 1345.79
  -> Decision False in time 0.8300000000, query time of that 0.4189697260, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 1000])
Got a train set of size (60000 * 784)
Built index in 17.909999999999854
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0427616667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0147683990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1348840930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1315.62 < 1402.6
  -> Decision False in time 0.0400000000, query time of that 0.0425605230, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0154491540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1394.52 < 1433.19
  -> Decision False in time 0.0700000000, query time of that 0.0613188430, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1014 < 1036.39
  -> Decision False in time 0.0600000000, query time of that 0.0583892030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1044.06 < 1071.15
  -> Decision False in time 0.0100000000, query time of that 0.0151280730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1069.99 < 1094.43
  -> Decision False in time 0.0300000000, query time of that 0.0160054580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1141.2 < 1211.1
  -> Decision False in time 0.0300000000, query time of that 0.0170070040, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 10000])
Got a train set of size (60000 * 784)
Built index in 33.69999999999891
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0395295450, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3642067000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1238.38 < 1283.17
  -> Decision False in time 0.6200000000, query time of that 0.6152158430, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0383223160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4100000000, query time of that 0.3901366760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1010.47 < 1068.68
  -> Decision False in time 0.1800000000, query time of that 0.1775532760, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0463921570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1840.87 < 1858.02
  -> Decision False in time 0.0500000000, query time of that 0.0424633890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1321.95 < 1356.02
  -> Decision False in time 0.3300000000, query time of that 0.1980814950, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 100000])
Got a train set of size (60000 * 784)
Built index in 33.72999999999956
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1510881890, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5200000000, query time of that 1.5081027290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2200000000, query time of that 15.1543569200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1558114370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5700000000, query time of that 1.5408648900, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.4300000000, query time of that 15.3516988180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1630881270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8600000000, query time of that 1.6605862240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1292.23 < 1301.39
  -> Decision False in time 9.5300000000, query time of that 9.4843141680, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 200000])
Got a train set of size (60000 * 784)
Built index in 18.05999999999949
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3100000000, query time of that 0.3066933400, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1700000000, query time of that 3.1660005990, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.4600000000, query time of that 31.3766969060, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3237159720, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1500000000, query time of that 3.1341793960, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.2300000000, query time of that 31.1334513100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3236547770, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.4100000000, query time of that 3.2216130370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.2800000000, query time of that 32.0484546220, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 20000])
Got a train set of size (60000 * 784)
Built index in 33.63999999999942
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0562880930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5128350200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1500000000, query time of that 5.1016605420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0575205900, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5800000000, query time of that 0.5401439230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1240.72 < 1251.16
  -> Decision False in time 3.9200000000, query time of that 3.8810503700, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1574.61 < 1639.34
  -> Decision False in time 0.0700000000, query time of that 0.0610205880, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1216.71 < 1250.39
  -> Decision False in time 0.0700000000, query time of that 0.0633571690, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1036.59 < 1040.75
  -> Decision False in time 0.3100000000, query time of that 0.2288159380, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 4000])
Got a train set of size (60000 * 784)
Built index in 18.030000000000655
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0119383333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0229605380, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2209175230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
977.22 < 1035.82
  -> Decision False in time 1.0800000000, query time of that 1.0596270200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0249668800, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1450.58 < 1472.25
  -> Decision False in time 0.1800000000, query time of that 0.1735141340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1731.63 < 1774.56
  -> Decision False in time 0.2200000000, query time of that 0.2119937220, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0257318210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1118.71 < 1164.71
  -> Decision False in time 0.0500000000, query time of that 0.0270682910, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1197.23 < 1216.87
  -> Decision False in time 0.1300000000, query time of that 0.0527777460, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 4000])
Got a train set of size (60000 * 784)
Built index in 33.45000000000073
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0254396560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2501060730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.5100000000, query time of that 2.4610965870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0255545300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1253.4 < 1299.73
  -> Decision False in time 0.0500000000, query time of that 0.0459843890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
873.137 < 998.763
  -> Decision False in time 0.5300000000, query time of that 0.5246000310, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0318910600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1881.54 < 1902.65
  -> Decision False in time 0.1900000000, query time of that 0.0727861130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1810.6 < 1817.39
  -> Decision False in time 0.0400000000, query time of that 0.0290636480, with c1=5.0000000000, c2=0.1000000000
