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, 40000]), 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, 100000]), 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', 200, 40000]), 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', 400, 100]), 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, 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, 4000]), 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, 400000]), 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', 100, 10000]), 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, 100]), 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, 200]), 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', 200, 100]), 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', 200, 20000]), 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', 100, 200000]), 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', 200, 2000]), 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, 100000]), 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', 100, 400000]), 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', 100, 20000]), 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', 400, 1000])]
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 65.28
Index size:  515224.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0922935470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8700000000, query time of that 0.8588989470, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.4800000000, query time of that 8.4168930050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0889604470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8900000000, query time of that 0.8800026980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2024.44 < 2052.46
  -> Decision False in time 4.0500000000, query time of that 4.0186227020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.0991408820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.2300000000, query time of that 1.0401822510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1294.2 < 1301.64
  -> Decision False in time 2.3500000000, query time of that 2.3229171140, 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 18.0
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 0.0844368790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7887105460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.9000000000, query time of that 7.8380341350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0816295750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8009275090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1700000000, query time of that 8.0617529210, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1834.93 < 1840.92
  -> Decision False in time 0.1200000000, query time of that 0.0888609690, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1000000000, query time of that 0.9409652780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1020.12 < 1121.52
  -> Decision False in time 0.1500000000, query time of that 0.1484041230, 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 65.44999999999993
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 0.1593687480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5200000000, query time of that 1.5073376330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.1700000000, query time of that 15.1118206780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1554156490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5600000000, query time of that 1.5399954370, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.5300000000, query time of that 15.4134699500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.1659806700, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8200000000, query time of that 1.6247507570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1393.14 < 1406.16
  -> Decision False in time 7.8600000000, query time of that 7.8156237900, 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 65.58999999999992
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0317516470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3173231020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1805.71 < 1918.04
  -> Decision False in time 0.3100000000, query time of that 0.3061199810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0373355220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2075.98 < 2135.36
  -> Decision False in time 0.0700000000, query time of that 0.0766770760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1193 < 1235.19
  -> Decision False in time 1.7400000000, query time of that 1.7130636760, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0396381010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1660.73 < 1722.2
  -> Decision False in time 0.2300000000, query time of that 0.1333136060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1369.23 < 1405.1
  -> Decision False in time 0.1000000000, query time of that 0.0537593770, 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 33.819999999999936
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 0.0804593890, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7850902090, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.7900000000, query time of that 7.7379812300, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0828165590, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8200000000, query time of that 0.7974346100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1600000000, query time of that 8.0731637060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0918420220, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1239.13 < 1262.93
  -> Decision False in time 0.6400000000, query time of that 0.6284141760, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1812.7 < 1821.71
  -> Decision False in time 0.6200000000, query time of that 0.5929549160, 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 18.089999999999918
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 0.0238496790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2185352110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1909.81 < 1942.16
  -> Decision False in time 0.6700000000, query time of that 0.6655976390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0252317010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1182.85 < 1209.77
  -> Decision False in time 0.1100000000, query time of that 0.1137008800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1280.82 < 1315.42
  -> Decision False in time 0.1200000000, query time of that 0.1197307590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1320.8 < 1413.62
  -> Decision False in time 0.0300000000, query time of that 0.0246173210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1018.2 < 1035.98
  -> Decision False in time 0.2200000000, query time of that 0.0861404700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1273.01 < 1303.99
  -> Decision False in time 0.1500000000, query time of that 0.0590036230, 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 64.94000000000005
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0203836040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1110.65 < 1113.27
  -> Decision False in time 0.1300000000, query time of that 0.1300759650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1104.31 < 1137.7
  -> Decision False in time 0.1600000000, query time of that 0.1565493930, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0238330970, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1753.5 < 1804.7
  -> Decision False in time 0.0500000000, query time of that 0.0454344880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1336.1 < 1351.78
  -> Decision False in time 0.0300000000, query time of that 0.0286032450, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1051.14 < 1110.8
  -> Decision False in time 0.0300000000, query time of that 0.0254169510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1187.68 < 1221.12
  -> Decision False in time 0.0300000000, query time of that 0.0261539140, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1438.43 < 1507.13
  -> Decision False in time 0.0200000000, query time of that 0.0190193240, 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 33.65000000000009
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2809855910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.7900000000, query time of that 2.7765878210, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.7900000000, query time of that 27.7237956630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2809557570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.8600000000, query time of that 2.8449501770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 28.1400000000, query time of that 28.0593565760, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2890010240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.0500000000, query time of that 2.8703088820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 29.0500000000, query time of that 28.4789920470, 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 33.779999999999745
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 0.0184351830, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1753.05 < 1776.38
  -> Decision False in time 0.0700000000, query time of that 0.0609818560, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1776.34 < 1777.04
  -> Decision False in time 0.2100000000, query time of that 0.2125832300, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0194552810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1192.46 < 1279.64
  -> Decision False in time 0.0300000000, query time of that 0.0253624810, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1569.09 < 1628.61
  -> Decision False in time 0.0300000000, query time of that 0.0325841720, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1156.77 < 1188.25
  -> Decision False in time 0.0500000000, query time of that 0.0189753420, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1253.81 < 1327.63
  -> Decision False in time 0.0200000000, query time of that 0.0216441050, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1627.18 < 1636.06
  -> Decision False in time 0.0200000000, query time of that 0.0198480910, 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 65.57999999999993
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Reject!
910.311 < 1157.45
  -> Decision False in time 0.0200000000, query time of that 0.0193725320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1920035390, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1159.36 < 1165.03
  -> Decision False in time 0.0900000000, query time of that 0.0847417270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0204096360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1112.55 < 1184.96
  -> Decision False in time 0.0300000000, query time of that 0.0261088020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
907.987 < 969.707
  -> Decision False in time 0.0100000000, query time of that 0.0183297910, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2491 < 2535.64
  -> Decision False in time 0.0300000000, query time of that 0.0231091910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
633.113 < 661.879
  -> Decision False in time 0.0300000000, query time of that 0.0267396020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
782.136 < 798.381
  -> Decision False in time 0.0300000000, query time of that 0.0247223040, 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 33.960000000000036
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0260903530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2453079070, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1170.84 < 1177.42
  -> Decision False in time 0.5000000000, query time of that 0.4834516210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0282900570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1143.62 < 1163.67
  -> Decision False in time 0.2500000000, query time of that 0.2435403410, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1702.85 < 1705.28
  -> Decision False in time 0.3100000000, query time of that 0.3005020980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1483.09 < 1544.01
  -> Decision False in time 0.0900000000, query time of that 0.0312653590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
902.596 < 1036.26
  -> Decision False in time 0.0300000000, query time of that 0.0291059660, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2064.43 < 2068.13
  -> Decision False in time 0.0300000000, query time of that 0.0270872570, 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 18.170000000000073
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 0.0118651140, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1026.27 < 1110.07
  -> Decision False in time 0.0300000000, query time of that 0.0302496420, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1823.71 < 1825.37
  -> Decision False in time 0.0300000000, query time of that 0.0308840770, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0107183710, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1073.57 < 1178.67
  -> Decision False in time 0.0300000000, query time of that 0.0287536130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1276.16 < 1295.44
  -> Decision False in time 0.0200000000, query time of that 0.0139523360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1292.05 < 1371.31
  -> Decision False in time 0.0100000000, query time of that 0.0113489060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1141.85 < 1210.88
  -> Decision False in time 0.0100000000, query time of that 0.0122996390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
995.994 < 1014.49
  -> Decision False in time 0.0500000000, query time of that 0.0128219430, 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 33.820000000000164
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.5625914480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.4800000000, query time of that 5.4726189640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.7100000000, query time of that 53.6317156200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.5541728600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3200000000, query time of that 5.3049519920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.7800000000, query time of that 53.6855886580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.5441491520, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.4700000000, query time of that 5.3532402180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 54.4300000000, query time of that 54.2347778560, 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 33.73000000000047
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0391494680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3607478780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1395.33 < 1429.64
  -> Decision False in time 1.7400000000, query time of that 1.7186318260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0400351410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
932.557 < 1045.96
  -> Decision False in time 0.2000000000, query time of that 0.1992501350, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1025.18 < 1103.1
  -> Decision False in time 0.2900000000, query time of that 0.2855936280, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1671.89 < 1716.85
  -> Decision False in time 0.0400000000, query time of that 0.0438175000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1323.7 < 1481.02
  -> Decision False in time 0.1500000000, query time of that 0.0945763070, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1448.98 < 1574.61
  -> Decision False in time 0.1400000000, query time of that 0.0929223100, 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 17.950000000000728
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 0.0351728560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3306991810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.3700000000, query time of that 3.3288718220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0386212670, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3741252910, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1210.42 < 1243.59
  -> Decision False in time 1.1100000000, query time of that 1.0965484210, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0414713200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1467.51 < 1492.27
  -> Decision False in time 0.4000000000, query time of that 0.2112577380, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1213.88 < 1224.73
  -> Decision False in time 0.0400000000, query time of that 0.0386069630, 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 33.85999999999967
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0151877910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2448.37 < 2491.63
  -> Decision False in time 0.1100000000, query time of that 0.1033148500, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1552.32 < 1566.84
  -> Decision False in time 0.0400000000, query time of that 0.0375833320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0154637730, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
953.551 < 1071.76
  -> Decision False in time 0.0300000000, query time of that 0.0315708330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1947.26 < 1999.33
  -> Decision False in time 0.0400000000, query time of that 0.0370115370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1379.43 < 1474.53
  -> Decision False in time 0.0200000000, query time of that 0.0162946160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1086.6 < 1148.94
  -> Decision False in time 0.0200000000, query time of that 0.0162360990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
925.935 < 946.675
  -> Decision False in time 0.0300000000, query time of that 0.0182475430, 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 18.07000000000062
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 0.0119785370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1322.02 < 1322.1
  -> Decision False in time 0.0200000000, query time of that 0.0178817590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1516.52 < 1531.19
  -> Decision False in time 0.0400000000, query time of that 0.0418665930, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1476.38 < 1489.61
  -> Decision False in time 0.0200000000, query time of that 0.0112056290, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1405.38 < 1438.9
  -> Decision False in time 0.0100000000, query time of that 0.0115211830, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1951.87 < 1980.78
  -> Decision False in time 0.0600000000, query time of that 0.0561916470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
946.077 < 968.864
  -> Decision False in time 0.0100000000, query time of that 0.0112315830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
846.066 < 989.602
  -> Decision False in time 0.0100000000, query time of that 0.0121311520, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
818.18 < 848.292
  -> Decision False in time 0.0200000000, query time of that 0.0116977050, 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 18.079999999999927
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 0.0179636820, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1666906810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
996.36 < 1009.79
  -> Decision False in time 0.0900000000, query time of that 0.0851552140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0191221070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1235.89 < 1286.66
  -> Decision False in time 0.0500000000, query time of that 0.0463361100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1852.37 < 1859.36
  -> Decision False in time 0.0500000000, query time of that 0.0502009100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1329.9 < 1587.35
  -> Decision False in time 0.0500000000, query time of that 0.0211855830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1795.5 < 1801.64
  -> Decision False in time 0.0500000000, query time of that 0.0211482180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1534.18 < 1596.7
  -> Decision False in time 0.0300000000, query time of that 0.0215797320, 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 18.030000000000655
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 0.0115919490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1025082390, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1845.02 < 1941.45
  -> Decision False in time 0.0300000000, query time of that 0.0275538350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1371.8 < 1410.1
  -> Decision False in time 0.0100000000, query time of that 0.0111341830, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1292.42 < 1374.77
  -> Decision False in time 0.0200000000, query time of that 0.0166169020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2420.72 < 2421.5
  -> Decision False in time 0.0200000000, query time of that 0.0208978180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1184 < 1203.53
  -> Decision False in time 0.0200000000, query time of that 0.0118180930, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
967.426 < 992.895
  -> Decision False in time 0.0200000000, query time of that 0.0128801070, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1459.53 < 1559.3
  -> Decision False in time 0.0100000000, query time of that 0.0117129810, 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 64.93000000000029
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 0.0293421630, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2632962510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1300.26 < 1305.1
  -> Decision False in time 0.2200000000, query time of that 0.2081318520, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0311357860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1307.85 < 1324.24
  -> Decision False in time 0.0500000000, query time of that 0.0470690690, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1238.26 < 1243.58
  -> Decision False in time 0.2900000000, query time of that 0.2840765210, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1204.41 < 1307.03
  -> Decision False in time 0.0400000000, query time of that 0.0348918620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1137.41 < 1143.37
  -> Decision False in time 0.0300000000, query time of that 0.0324374160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1157.41 < 1182.26
  -> Decision False in time 0.0600000000, query time of that 0.0369560880, 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 65.01000000000022
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Reject!
907.357 < 982.808
  -> Decision False in time 0.0200000000, query time of that 0.0207137240, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1467.53 < 1472.36
  -> Decision False in time 0.1800000000, query time of that 0.1756291360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1977.12 < 2032.46
  -> Decision False in time 0.2000000000, query time of that 0.1867893360, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0219223190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1046.17 < 1090.93
  -> Decision False in time 0.0800000000, query time of that 0.0776571540, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1559.96 < 1576.17
  -> Decision False in time 0.0900000000, query time of that 0.0883750230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1389.84 < 1411.61
  -> Decision False in time 0.0300000000, query time of that 0.0240902280, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1597.53 < 1609.3
  -> Decision False in time 0.0300000000, query time of that 0.0244452610, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1108.13 < 1175.57
  -> Decision False in time 0.0200000000, query time of that 0.0227008980, 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 33.63000000000011
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 0.0157747980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1284481160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1573.59 < 1604.44
  -> Decision False in time 0.0500000000, query time of that 0.0447303600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1254.06 < 1340.98
  -> Decision False in time 0.0100000000, query time of that 0.0150605420, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1083.57 < 1217.38
  -> Decision False in time 0.0400000000, query time of that 0.0385071050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1131.2 < 1137.2
  -> Decision False in time 0.0500000000, query time of that 0.0463242130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1483.34 < 1486.01
  -> Decision False in time 0.0200000000, query time of that 0.0143655590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1230.91 < 1250.25
  -> Decision False in time 0.0100000000, query time of that 0.0155442990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
641.647 < 691.659
  -> Decision False in time 0.0200000000, query time of that 0.0156882350, 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 65.28000000000065
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5015313680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9700000000, query time of that 4.9655642210, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.4400000000, query time of that 49.3561138930, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4958618190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9300000000, query time of that 4.9094700510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.5600000000, query time of that 49.4792126020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5059300800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.1200000000, query time of that 4.9893067200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 49.8700000000, query time of that 49.4864791300, 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 33.590000000000146
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 0.0554115660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5180035570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1500000000, query time of that 5.0888998460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0564078210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5432606390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1538.19 < 1616.22
  -> Decision False in time 2.7300000000, query time of that 2.7010369300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0614749720, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1187.31 < 1336.7
  -> Decision False in time 0.9600000000, query time of that 0.6856782090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1674.73 < 1689.78
  -> Decision False in time 0.1600000000, query time of that 0.1272971310, 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 65.23999999999978
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 0.2728410320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6500000000, query time of that 2.6455454260, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.4300000000, query time of that 26.3574700200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2733061690, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6600000000, query time of that 2.6455077120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.5500000000, query time of that 26.4772914770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2785205420, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8100000000, query time of that 2.7136739370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 27.4200000000, query time of that 27.0530383800, 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 18.100000000000364
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3292872470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1700000000, query time of that 3.1648296690, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.7200000000, query time of that 31.6510510860, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3141864810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1200000000, query time of that 3.1082037130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.5700000000, query time of that 31.4897175610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4200000000, query time of that 0.3345363930, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.3500000000, query time of that 3.2393327440, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.5300000000, query time of that 32.2773607110, 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 65.04000000000087
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 0.0600290970, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6000000000, query time of that 0.5923849700, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.8800000000, query time of that 5.8172644130, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0634679600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1762.49 < 2022.94
  -> Decision False in time 0.4000000000, query time of that 0.4003556790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1801.3 < 1822.61
  -> Decision False in time 5.2900000000, query time of that 5.2405508730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0727937500, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1810.6 < 1817.39
  -> Decision False in time 0.3500000000, query time of that 0.2955092030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2019.41 < 2370.8
  -> Decision False in time 1.1500000000, query time of that 0.9476884570, 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 33.79999999999927
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 0.0216410020, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2037433700, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
862.897 < 893.41
  -> Decision False in time 0.7400000000, query time of that 0.7277860640, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0217048380, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1295.82 < 1313.12
  -> Decision False in time 0.2100000000, query time of that 0.2033536200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
744.743 < 753.351
  -> Decision False in time 0.0600000000, query time of that 0.0596511590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1179.22 < 1226.62
  -> Decision False in time 0.0200000000, query time of that 0.0227502190, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1466 < 1480.97
  -> Decision False in time 0.0200000000, query time of that 0.0209458370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1357.9 < 1557.72
  -> Decision False in time 0.0300000000, query time of that 0.0236158370, 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 18.020000000000437
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 0.1766126410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6900000000, query time of that 1.6851676940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.6100000000, query time of that 16.5492778900, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1762530640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6900000000, query time of that 1.6691955590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.7700000000, query time of that 16.6902688570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.1784034870, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9600000000, query time of that 1.7679309540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1557.68 < 1615.41
  -> Decision False in time 6.8400000000, query time of that 6.8051308990, 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 0.1554092510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5173295010, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2000000000, query time of that 15.1434208710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1579226030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5241841850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.3300000000, query time of that 15.2614391040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1652382210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1427.29 < 1452.49
  -> Decision False in time 0.5700000000, query time of that 0.5617672860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1234.55 < 1282.95
  -> Decision False in time 3.2200000000, query time of that 3.2065296410, 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 65.22999999999956
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0471830300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4360576280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1319.75 < 1324.14
  -> Decision False in time 1.8000000000, query time of that 1.7841816490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0463090010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1876.96 < 1943.71
  -> Decision False in time 0.0700000000, query time of that 0.0736738710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1475.98 < 1547.13
  -> Decision False in time 0.5100000000, query time of that 0.4988041620, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1453.92 < 1455.55
  -> Decision False in time 0.0500000000, query time of that 0.0487796060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0100000000, query time of that 0.5897280830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1142.96 < 1199.76
  -> Decision False in time 0.2700000000, query time of that 0.1918111320, 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 18.110000000000582
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6000000000, query time of that 0.6028600540, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.0200000000, query time of that 6.0069700310, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 60.0900000000, query time of that 60.0078026050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6100000000, query time of that 0.5994554950, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.0200000000, query time of that 5.9961233430, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.9000000000, query time of that 59.8161881970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6148037830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.1500000000, query time of that 6.0537886780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 60.4800000000, query time of that 60.3036725120, 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 33.600000000000364
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 0.0145458420, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1305510650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1712.05 < 1715.92
  -> Decision False in time 0.0400000000, query time of that 0.0332860210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0136914920, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1313.49 < 1345.22
  -> Decision False in time 0.0900000000, query time of that 0.0865362650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1410.77 < 1419.44
  -> Decision False in time 0.0900000000, query time of that 0.0920122460, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1058.55 < 1097.21
  -> Decision False in time 0.0200000000, query time of that 0.0167454760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1395.47 < 1396.83
  -> Decision False in time 0.0200000000, query time of that 0.0165057810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
898.284 < 975.328
  -> Decision False in time 0.0200000000, query time of that 0.0148941400, 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 17.98999999999978
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 0.0521880210, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1250.45 < 1260.2
  -> Decision False in time 0.4700000000, query time of that 0.4623213410, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1125.52 < 1146.9
  -> Decision False in time 4.4900000000, query time of that 4.4512094260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0527712440, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5216202410, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1497.82 < 1513.1
  -> Decision False in time 2.8000000000, query time of that 2.7794838740, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2160.08 < 2160.54
  -> Decision False in time 0.0800000000, query time of that 0.0601728510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1622.58 < 1625.01
  -> Decision False in time 0.4800000000, query time of that 0.3570677580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2210.18 < 2229.4
  -> Decision False in time 0.4000000000, query time of that 0.2618953430, 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 17.970000000001164
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0427616667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0156764700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1279.38 < 1303.43
  -> Decision False in time 0.1000000000, query time of that 0.0944261970, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1654.52 < 1738.68
  -> Decision False in time 0.0800000000, query time of that 0.0767200280, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0154423230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
957.084 < 1029.88
  -> Decision False in time 0.0800000000, query time of that 0.0718660740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1026.22 < 1046.3
  -> Decision False in time 0.0200000000, query time of that 0.0220233420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1378.3 < 1393.1
  -> Decision False in time 0.0200000000, query time of that 0.0155853510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
758.995 < 780.987
  -> Decision False in time 0.0200000000, query time of that 0.0167534870, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1385.59 < 1528.92
  -> Decision False in time 0.0100000000, query time of that 0.0157055970, 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 65.04000000000087
Index size:  514396.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Reject!
1094.97 < 1184.3
  -> Decision False in time 0.0300000000, query time of that 0.0245354330, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1037.09 < 1041.32
  -> Decision False in time 0.1200000000, query time of that 0.1179571310, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
807.699 < 835.425
  -> Decision False in time 1.0600000000, query time of that 1.0380179430, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0273703730, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1375.73 < 1443.82
  -> Decision False in time 0.0400000000, query time of that 0.0345139590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
968.901 < 969.01
  -> Decision False in time 0.2100000000, query time of that 0.2059015340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0286775100, 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 0.0269601190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
977.164 < 1035.1
  -> Decision False in time 0.0300000000, query time of that 0.0245547790, with c1=5.0000000000, c2=0.1000000000
