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', 400, 100]), 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', 200, 1000]), 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', 100, 200]), 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, 400000]), 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, 2000]), 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, 10000]), 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', 100, 40000]), 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', 200, 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, 400]), 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', 100, 100]), 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', 200, 4000]), 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', 400, 200]), 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', 400, 400]), 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, 4000]), 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, 4000]), 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, 20000]), 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, 40000]), 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, 10000]), 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, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100])
Got a train set of size (60000 * 784)
Built index in 84.95
Index size:  515224.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Reject!
2031.67 < 2053.8
  -> Decision False in time 0.0300000000, query time of that 0.0212550550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1551.93 < 1578.19
  -> Decision False in time 0.0400000000, query time of that 0.0414856520, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
809.331 < 809.823
  -> Decision False in time 0.0800000000, query time of that 0.0725516230, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0229730250, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1310.74 < 1380.68
  -> Decision False in time 0.0400000000, query time of that 0.0358461160, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
974.458 < 977.753
  -> Decision False in time 0.0500000000, query time of that 0.0486670800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1126.95 < 1181.34
  -> Decision False in time 0.0200000000, query time of that 0.0213903150, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
968.028 < 1002.06
  -> Decision False in time 0.0300000000, query time of that 0.0218304210, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1148.87 < 1264.11
  -> Decision False in time 0.0200000000, query time of that 0.0232548210, 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 18.069999999999993
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 0.0490048000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4980445260, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1233.78 < 1246.59
  -> Decision False in time 3.3600000000, query time of that 3.3181856170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0554439400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5300000000, query time of that 0.5171923790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1225.54 < 1248.76
  -> Decision False in time 1.3100000000, query time of that 1.2984122020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0625433940, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1503.15 < 1505.35
  -> Decision False in time 0.3800000000, query time of that 0.2757846850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2112.58 < 2149.66
  -> Decision False in time 2.5600000000, query time of that 1.8370748140, 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 33.81999999999999
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 0.0184794260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1680610990, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1769.28 < 1836.3
  -> Decision False in time 0.1600000000, query time of that 0.1580176250, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0201998280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1395.05 < 1433.12
  -> Decision False in time 0.0200000000, query time of that 0.0184382920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1790.29 < 1956.66
  -> Decision False in time 0.0400000000, query time of that 0.0389350190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1035.88 < 1111.55
  -> Decision False in time 0.0200000000, query time of that 0.0182761480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1078.52 < 1153.31
  -> Decision False in time 0.0900000000, query time of that 0.0291343750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1235.58 < 1244.85
  -> Decision False in time 0.0200000000, query time of that 0.0222580790, 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 65.25999999999999
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0868535870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8500000000, query time of that 0.8446707930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.3700000000, query time of that 8.3020466500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0883846610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.9000000000, query time of that 0.8781889830, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1749.79 < 1766.38
  -> Decision False in time 1.6700000000, query time of that 1.6564528270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0986040310, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2080.2 < 2118.65
  -> Decision False in time 0.1900000000, query time of that 0.1891929570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1474.74 < 1515.23
  -> Decision False in time 2.2100000000, query time of that 2.1864869660, 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 18.08000000000004
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 0.0118353490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1251 < 1278.08
  -> Decision False in time 0.1000000000, query time of that 0.0994842630, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1153.97 < 1155.25
  -> Decision False in time 0.0400000000, query time of that 0.0364515030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0117369360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1359.62 < 1362.76
  -> Decision False in time 0.0200000000, query time of that 0.0157815480, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1330.21 < 1432.25
  -> Decision False in time 0.0200000000, query time of that 0.0201600420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1073.62 < 1128.02
  -> Decision False in time 0.0200000000, query time of that 0.0111962540, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
816.889 < 829.892
  -> Decision False in time 0.0400000000, query time of that 0.0129068260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
957.923 < 1000.82
  -> Decision False in time 0.0100000000, query time of that 0.0130223750, 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 33.77999999999997
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 0.1554149260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5239701070, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2300000000, query time of that 15.1717039540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1494464290, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5700000000, query time of that 1.5409855390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1387.45 < 1496.03
  -> Decision False in time 8.2700000000, query time of that 8.2339729080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.1701033410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7800000000, query time of that 1.6416671750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 17.1200000000, query time of that 16.4576871790, 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 18.029999999999973
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6240092180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.0400000000, query time of that 6.0308896830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 60.2000000000, query time of that 60.1041913450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6156941210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.9900000000, query time of that 5.9729599880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.9500000000, query time of that 59.8429223130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6133411270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.0200000000, query time of that 5.9397127520, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 60.6200000000, query time of that 60.4261078480, 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 18.09999999999991
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 0.0153795200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1364199470, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1062.81 < 1076.11
  -> Decision False in time 0.2600000000, query time of that 0.2485708720, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0151615960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
780.647 < 822.234
  -> Decision False in time 0.0600000000, query time of that 0.0535317960, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1053.46 < 1236.64
  -> Decision False in time 0.0500000000, query time of that 0.0458218830, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1333.15 < 1335.81
  -> Decision False in time 0.0200000000, query time of that 0.0155608520, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1112.37 < 1134.44
  -> Decision False in time 0.0900000000, query time of that 0.0259814790, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1611.6 < 1657.21
  -> Decision False in time 0.0200000000, query time of that 0.0166446900, 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 33.789999999999964
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 0.0212422340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1732.17 < 1748.17
  -> Decision False in time 0.1700000000, query time of that 0.1645435180, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1278.75 < 1283.5
  -> Decision False in time 0.0500000000, query time of that 0.0495978380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0231757300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1435.2 < 1489.51
  -> Decision False in time 0.1300000000, query time of that 0.1219273510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
950.916 < 1223.03
  -> Decision False in time 0.0700000000, query time of that 0.0755684040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1331.52 < 1336.83
  -> Decision False in time 0.0300000000, query time of that 0.0244016980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1484.21 < 1516.07
  -> Decision False in time 0.0300000000, query time of that 0.0267201390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1396.45 < 1405.3
  -> Decision False in time 0.0700000000, query time of that 0.0264428800, 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 65.24000000000024
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1547654310, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5200000000, query time of that 1.5110748910, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2100000000, query time of that 15.1450634040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1604954560, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5222397440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.3800000000, query time of that 15.2992607470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1751361960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7500000000, query time of that 1.6473362480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1715.27 < 1717.15
  -> Decision False in time 15.3700000000, query time of that 15.2770624120, 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 18.079999999999927
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0348087290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3270741400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2082.93 < 2123.69
  -> Decision False in time 0.2900000000, query time of that 0.2783275160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0366597830, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3663754440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1654.77 < 1942.49
  -> Decision False in time 0.5100000000, query time of that 0.5027229330, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0420337380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1762.49 < 2022.94
  -> Decision False in time 0.1400000000, query time of that 0.0857418220, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1337.7 < 1384.35
  -> Decision False in time 0.0400000000, query time of that 0.0392656200, 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 33.8700000000008
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 0.2877355080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.7900000000, query time of that 2.7835813680, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.9400000000, query time of that 27.8624188040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2715294340, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.8400000000, query time of that 2.8268039070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 28.1200000000, query time of that 28.0348192550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.2967637990, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.0200000000, query time of that 2.8385564870, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 28.9000000000, query time of that 28.5194704720, 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 18.090000000000146
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 0.0798480570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7899596880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.9200000000, query time of that 7.8583695870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0822290580, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8600000000, query time of that 0.8233977950, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.2500000000, query time of that 8.1096584170, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0884396040, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1343.89 < 1428.48
  -> Decision False in time 0.6900000000, query time of that 0.6648207960, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1401.59 < 1456.17
  -> Decision False in time 0.1100000000, query time of that 0.1084340540, 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 18.109999999999673
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 0.0119030410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1362.77 < 1384.97
  -> Decision False in time 0.0900000000, query time of that 0.0865582770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1231.42 < 1250.67
  -> Decision False in time 0.0700000000, query time of that 0.0694351230, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0110167540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
965.744 < 1001.85
  -> Decision False in time 0.0200000000, query time of that 0.0198645700, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
908.132 < 1045.09
  -> Decision False in time 0.0100000000, query time of that 0.0109314500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1235.15 < 1247.62
  -> Decision False in time 0.0200000000, query time of that 0.0101163520, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
985.667 < 1030.3
  -> Decision False in time 0.0100000000, query time of that 0.0116431640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
825.994 < 889.113
  -> Decision False in time 0.0400000000, query time of that 0.0124548580, 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 33.85999999999967
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Reject!
1583.88 < 1774.91
  -> Decision False in time 0.0100000000, query time of that 0.0144131970, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2238.31 < 2246.33
  -> Decision False in time 0.0200000000, query time of that 0.0207382590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2301.46 < 2303.2
  -> Decision False in time 0.1400000000, query time of that 0.1323303730, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1279.73 < 1331.15
  -> Decision False in time 0.0200000000, query time of that 0.0149129610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1350.66 < 1385.68
  -> Decision False in time 0.0400000000, query time of that 0.0368349310, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1338.06 < 1361.78
  -> Decision False in time 0.0200000000, query time of that 0.0247972790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1184.46 < 1213.86
  -> Decision False in time 0.0200000000, query time of that 0.0152213720, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1430.85 < 1431.36
  -> Decision False in time 0.0200000000, query time of that 0.0156440280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1303.03 < 1378.42
  -> Decision False in time 0.0200000000, query time of that 0.0145111100, 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 65.40000000000055
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2712587100, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6100000000, query time of that 2.6078739890, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.3800000000, query time of that 26.3066662520, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2687646190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6400000000, query time of that 2.6290660450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.6100000000, query time of that 26.5262320650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.2847186070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8300000000, query time of that 2.6967100880, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 27.0800000000, query time of that 26.8201473140, 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 33.720000000000255
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Reject!
1242.92 < 1249.33
  -> Decision False in time 0.0100000000, query time of that 0.0153421040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1315067310, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1291.92 < 1388.61
  -> Decision False in time 0.0500000000, query time of that 0.0455059780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0138599110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1048.48 < 1066.1
  -> Decision False in time 0.0400000000, query time of that 0.0344392510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
920.333 < 1049.63
  -> Decision False in time 0.0600000000, query time of that 0.0519463660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2306.32 < 2363.54
  -> Decision False in time 0.0100000000, query time of that 0.0165140660, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1615.99 < 1629.67
  -> Decision False in time 0.0200000000, query time of that 0.0143989540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1483.67 < 1558.86
  -> Decision False in time 0.0200000000, query time of that 0.0144409490, 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 65.07999999999993
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0193766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0292384960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2669965960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1658.89 < 1720.36
  -> Decision False in time 0.2300000000, query time of that 0.2218686090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
949.55 < 954.188
  -> Decision False in time 0.0300000000, query time of that 0.0307571130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1404.84 < 1439.28
  -> Decision False in time 0.2000000000, query time of that 0.1915143310, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1116.59 < 1150.03
  -> Decision False in time 0.1900000000, query time of that 0.1905076730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0325626100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
909.703 < 959.815
  -> Decision False in time 0.1300000000, query time of that 0.0703980770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1757.71 < 1806.97
  -> Decision False in time 0.0400000000, query time of that 0.0329495470, 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 18.030000000000655
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Reject!
1297.81 < 1299.78
  -> Decision False in time 0.0100000000, query time of that 0.0111242390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1242.85 < 1252.69
  -> Decision False in time 0.0800000000, query time of that 0.0755515960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1016.93 < 1030.58
  -> Decision False in time 0.0700000000, query time of that 0.0710516650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1093.27 < 1211.34
  -> Decision False in time 0.0200000000, query time of that 0.0113939560, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1528.98 < 1537.84
  -> Decision False in time 0.0100000000, query time of that 0.0171313340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1221.23 < 1237.58
  -> Decision False in time 0.0100000000, query time of that 0.0108418000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1347.85 < 1429.72
  -> Decision False in time 0.0200000000, query time of that 0.0106609090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1284.31 < 1444.11
  -> Decision False in time 0.0100000000, query time of that 0.0111438640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
892.635 < 1042.29
  -> Decision False in time 0.0100000000, query time of that 0.0114820030, 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 18.039999999999964
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1758401310, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6700000000, query time of that 1.6588204350, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.6400000000, query time of that 16.5770198460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1799748550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6600000000, query time of that 1.6404381880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.7600000000, query time of that 16.6817912570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1750392620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9100000000, query time of that 1.7862537390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1627.29 < 1695.73
  -> Decision False in time 17.1700000000, query time of that 17.0787079150, 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 33.8700000000008
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 0.0272395370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2528869130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
750.978 < 796.096
  -> Decision False in time 1.9700000000, query time of that 1.9381555340, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0275447790, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1234.53 < 1335.81
  -> Decision False in time 0.0700000000, query time of that 0.0735126300, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1024.4 < 1044.75
  -> Decision False in time 0.1200000000, query time of that 0.1166961840, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0327432590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1246.52 < 1272.21
  -> Decision False in time 0.0700000000, query time of that 0.0307092090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
965.229 < 1012.44
  -> Decision False in time 0.1500000000, query time of that 0.0658701830, 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, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 2000])
Got a train set of size (60000 * 784)
Built index in 18.110000000000582
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0192102180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1693768160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1563.88 < 1613.86
  -> Decision False in time 0.3200000000, query time of that 0.3113668440, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0181949530, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1425.86 < 1470.49
  -> Decision False in time 0.0900000000, query time of that 0.0834011180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
894.477 < 896.165
  -> Decision False in time 0.0700000000, query time of that 0.0730648540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0198158720, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
938.77 < 1007.6
  -> Decision False in time 0.1000000000, query time of that 0.0383807990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1131.85 < 1136.42
  -> Decision False in time 0.0800000000, query time of that 0.0254256600, 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 65.38999999999942
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0211033260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1148.93 < 1156.24
  -> Decision False in time 0.1100000000, query time of that 0.1048719920, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
957.66 < 1010.83
  -> Decision False in time 0.1400000000, query time of that 0.1361172090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0219048630, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
805.457 < 843.45
  -> Decision False in time 0.0700000000, query time of that 0.0706662650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1374.68 < 1375.19
  -> Decision False in time 0.0500000000, query time of that 0.0516812780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1499.11 < 1501.56
  -> Decision False in time 0.0200000000, query time of that 0.0198541260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1022.14 < 1037.44
  -> Decision False in time 0.0300000000, query time of that 0.0214495430, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1243.71 < 1264.23
  -> Decision False in time 0.0200000000, query time of that 0.0221170430, 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 33.86999999999898
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0145575870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1052.8 < 1105
  -> Decision False in time 0.0700000000, query time of that 0.0666043330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1306.81 < 1344.77
  -> Decision False in time 0.0200000000, query time of that 0.0164854600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0143165610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1326.5 < 1399.17
  -> Decision False in time 0.0400000000, query time of that 0.0417742220, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1169.36 < 1229.68
  -> Decision False in time 0.0300000000, query time of that 0.0323640810, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1379.67 < 1392.07
  -> Decision False in time 0.0300000000, query time of that 0.0162955660, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
844.321 < 846.031
  -> Decision False in time 0.0700000000, query time of that 0.0160689330, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1477.7 < 1478.54
  -> Decision False in time 0.0300000000, query time of that 0.0164328840, 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 65.39000000000124
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0196823050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1153.67 < 1219.55
  -> Decision False in time 0.0700000000, query time of that 0.0633610280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1520.78 < 1589.47
  -> Decision False in time 0.2600000000, query time of that 0.2565923690, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0210711780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1235.42 < 1313.99
  -> Decision False in time 0.0800000000, query time of that 0.0850688650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
914.697 < 929.495
  -> Decision False in time 0.0500000000, query time of that 0.0415176250, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
907.904 < 958.821
  -> Decision False in time 0.0200000000, query time of that 0.0256296980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1602.87 < 1685.45
  -> Decision False in time 0.0300000000, query time of that 0.0218996840, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1110.96 < 1151.66
  -> Decision False in time 0.0200000000, query time of that 0.0237425900, 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 65.38000000000102
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5220139720, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9800000000, query time of that 4.9651693040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.7600000000, query time of that 49.6731292350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5127053340, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9400000000, query time of that 4.9202442360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.4300000000, query time of that 49.3388141820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5104509610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.0800000000, query time of that 4.9756265100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 49.8200000000, query time of that 49.4814600520, 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 17.900000000001455
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 0.0239343200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2212442000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1344.35 < 1355.4
  -> Decision False in time 0.4900000000, query time of that 0.4825553880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0232733030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2501149020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1085.56 < 1136.66
  -> Decision False in time 0.1200000000, query time of that 0.1175997770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1422.48 < 1437.89
  -> Decision False in time 0.0800000000, query time of that 0.0271498590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1762.49 < 2022.94
  -> Decision False in time 0.3900000000, query time of that 0.1449167600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1365.85 < 1382.41
  -> Decision False in time 0.0400000000, query time of that 0.0274195250, 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 33.529999999998836
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5386299980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.3800000000, query time of that 5.3706453330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.8400000000, query time of that 53.7393538950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5800000000, query time of that 0.5721775390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3300000000, query time of that 5.3095097270, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.5400000000, query time of that 53.4415877470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.5566984110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.5100000000, query time of that 5.4103913060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 55.0500000000, query time of that 54.4711542150, 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 64.71000000000095
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Reject!
1089.69 < 1148.22
  -> Decision False in time 0.0400000000, query time of that 0.0341437200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3241660820, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.2400000000, query time of that 3.1921506890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0369532280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1321.34 < 1338.83
  -> Decision False in time 0.3500000000, query time of that 0.3455766210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1201.99 < 1265.3
  -> Decision False in time 0.0700000000, query time of that 0.0644034460, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1566.53 < 1582.33
  -> Decision False in time 0.0900000000, query time of that 0.0417963580, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2097.18 < 2113.37
  -> Decision False in time 0.0400000000, query time of that 0.0392599250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1612.05 < 1750.66
  -> Decision False in time 0.0400000000, query time of that 0.0396570500, 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 65.32999999999993
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0237524220, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
888.713 < 958.167
  -> Decision False in time 0.0900000000, query time of that 0.0911414820, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1281.15 < 1332.77
  -> Decision False in time 0.3600000000, query time of that 0.3558167450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0261450200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1355.07 < 1363.91
  -> Decision False in time 0.1800000000, query time of that 0.1759887790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1512.99 < 1532.74
  -> Decision False in time 0.0700000000, query time of that 0.0709462420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
857.953 < 886.153
  -> Decision False in time 0.0500000000, query time of that 0.0301867300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1050.76 < 1052.49
  -> Decision False in time 0.0300000000, query time of that 0.0296287680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
958.168 < 1008.63
  -> Decision False in time 0.0300000000, query time of that 0.0259247990, 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 33.82999999999993
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 0.0565873050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5078899770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1700000000, query time of that 5.1097609650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0568775870, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1073.5 < 1084.09
  -> Decision False in time 0.3000000000, query time of that 0.2947090980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1384.49 < 1473.98
  -> Decision False in time 0.3000000000, query time of that 0.2973807240, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0616177730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1225.54 < 1248.76
  -> Decision False in time 0.6000000000, query time of that 0.4421154420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1693.38 < 1781.26
  -> Decision False in time 1.0500000000, query time of that 0.7748923870, 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 65.34000000000015
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0434413300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4298145590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3300000000, query time of that 4.2841032980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0467844880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.4787289470, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1341.94 < 1390.01
  -> Decision False in time 0.2300000000, query time of that 0.2248198610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0542906130, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1352.39 < 1386.8
  -> Decision False in time 0.7800000000, query time of that 0.5397591790, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1313.88 < 1322.43
  -> Decision False in time 0.1100000000, query time of that 0.0707706110, 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 33.82999999999993
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0797002600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7772477220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8000000000, query time of that 7.7394904140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0777353930, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8200000000, query time of that 0.8043185110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1600000000, query time of that 8.0775041570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0889082000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1760.04 < 1760.53
  -> Decision False in time 0.4300000000, query time of that 0.4134955250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1326.73 < 1333.42
  -> Decision False in time 0.4100000000, query time of that 0.4068660620, 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 18.079999999999927
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3250301430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1600000000, query time of that 3.1507266100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.5800000000, query time of that 31.4984061240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3232786920, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.2100000000, query time of that 3.1966308540, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.7300000000, query time of that 31.6372883300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4100000000, query time of that 0.3328570610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.3100000000, query time of that 3.1942203780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.3500000000, query time of that 32.0261099820, 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 33.840000000000146
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 0.0376176590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3618915440, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.6300000000, query time of that 3.5872890310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0398268640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4200000000, query time of that 0.3910758970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1083.95 < 1236.63
  -> Decision False in time 1.0800000000, query time of that 1.0673920900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0426401170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1266.57 < 1273.04
  -> Decision False in time 0.1800000000, query time of that 0.1029787460, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
880.622 < 896.625
  -> Decision False in time 0.1800000000, query time of that 0.1025692950, 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 64.73999999999978
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0615355460, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5869088160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
845.183 < 849.281
  -> Decision False in time 2.3300000000, query time of that 2.3089908340, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0624547400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6242685910, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1358.47 < 1381.43
  -> Decision False in time 0.4900000000, query time of that 0.4862905570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0702164320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1180.81 < 1242.44
  -> Decision False in time 0.1900000000, query time of that 0.1570223090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1218.09 < 1236.07
  -> Decision False in time 1.4800000000, query time of that 1.2674056000, with c1=5.0000000000, c2=0.1000000000
