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', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), 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', 100, 4000]), 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', 400, 20000]), 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, 100]), 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', 100, 20000]), 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, 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', 400, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), 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', 100, 400000]), 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, 200]), 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', 400, 40000]), 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, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), 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, 10000]), 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', 200, 1000]), 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', 400, 200000])]
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 35.67
Index size:  396464.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1576057900, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.4800000000, query time of that 1.4657584360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 14.8700000000, query time of that 14.8064252850, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1518185510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5193270910, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.4600000000, query time of that 15.3830036990, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.1640119740, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.6500000000, query time of that 1.5726772840, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1403.22 < 1433.31
  -> Decision False in time 5.0300000000, query time of that 4.9953326410, 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 18.120000000000005
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0006000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0815892440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7868593430, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8500000000, query time of that 7.7864402260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0824289360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8100000000, query time of that 0.7903300140, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.0800000000, query time of that 7.9460345600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0885290390, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.2000000000, query time of that 0.9807739850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1713.04 < 1714.9
  -> Decision False in time 3.4000000000, query time of that 3.2990160580, 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 65.10000000000014
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0202339260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1809.02 < 1834.33
  -> Decision False in time 0.1400000000, query time of that 0.1445111900, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1673.29 < 1809.47
  -> Decision False in time 0.4200000000, query time of that 0.4099906050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0211053210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1183.23 < 1184.17
  -> Decision False in time 0.0600000000, query time of that 0.0605112280, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1353.43 < 1357.59
  -> Decision False in time 0.0600000000, query time of that 0.0541167630, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
986.819 < 1006.44
  -> Decision False in time 0.0200000000, query time of that 0.0235426700, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1125.75 < 1128.97
  -> Decision False in time 0.0300000000, query time of that 0.0215260160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1160.5 < 1198.18
  -> Decision False in time 0.0200000000, query time of that 0.0237753370, 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 17.95999999999981
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0427616667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0147776420, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1318.52 < 1338.01
  -> Decision False in time 0.1300000000, query time of that 0.1283292140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1818.47 < 1823.69
  -> Decision False in time 0.0900000000, query time of that 0.0926497240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0159028810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1971.95 < 2002.21
  -> Decision False in time 0.0200000000, query time of that 0.0217534860, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2187.96 < 2260.36
  -> Decision False in time 0.0200000000, query time of that 0.0147669010, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
767.153 < 812.332
  -> Decision False in time 0.0100000000, query time of that 0.0160748480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1075.46 < 1306.27
  -> Decision False in time 0.0200000000, query time of that 0.0155245700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
995.563 < 1022.24
  -> Decision False in time 0.0300000000, query time of that 0.0162356450, 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 17.99000000000001
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0119383333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0223688830, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2201301130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
633.949 < 712.285
  -> Decision False in time 2.1700000000, query time of that 2.1267883590, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0255180520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2603426100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1461.91 < 1486.85
  -> Decision False in time 0.0900000000, query time of that 0.0804310460, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0267647780, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
633.949 < 712.285
  -> Decision False in time 0.1900000000, query time of that 0.0704128940, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1146.72 < 1176.15
  -> Decision False in time 0.1100000000, query time of that 0.0474858590, 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 17.960000000000036
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0354783790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3317349110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1079.23 < 1138.89
  -> Decision False in time 2.2900000000, query time of that 2.2631093320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0345140750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3577774360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1895.45 < 1995.43
  -> Decision False in time 0.2100000000, query time of that 0.2124514750, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0406375080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1868.75 < 1875.35
  -> Decision False in time 0.1400000000, query time of that 0.0876339300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
964.263 < 977.625
  -> Decision False in time 0.2600000000, query time of that 0.1468663350, 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 33.58999999999992
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0140992890, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1275.19 < 1289.35
  -> Decision False in time 0.0800000000, query time of that 0.0691131130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2421.78 < 2440.85
  -> Decision False in time 0.0900000000, query time of that 0.0903454960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1059.51 < 1100.33
  -> Decision False in time 0.0100000000, query time of that 0.0145102390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
957.404 < 996.591
  -> Decision False in time 0.0300000000, query time of that 0.0210152020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
713.89 < 726.276
  -> Decision False in time 0.0400000000, query time of that 0.0422075250, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1320.75 < 1331.24
  -> Decision False in time 0.0200000000, query time of that 0.0166432800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1689.4 < 1716.5
  -> Decision False in time 0.0100000000, query time of that 0.0158200280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1135.71 < 1160.55
  -> Decision False in time 0.0300000000, query time of that 0.0162340640, 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 65.04999999999995
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0588093560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5904211330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.8600000000, query time of that 5.7938362000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0624418620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6195877580, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1386.68 < 1450.33
  -> Decision False in time 0.3600000000, query time of that 0.3501621300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0687421300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1526.71 < 1546.42
  -> Decision False in time 0.2800000000, query time of that 0.2384325500, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
830.544 < 836.39
  -> Decision False in time 0.2500000000, query time of that 0.2189839680, 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 65.21000000000004
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1580430470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5363563230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2000000000, query time of that 15.1277332970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1527955840, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5700000000, query time of that 1.5588890170, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.6100000000, query time of that 15.4929532360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1653191260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8500000000, query time of that 1.6345177600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
894.963 < 924.149
  -> Decision False in time 1.9900000000, query time of that 1.9746210140, 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 17.9699999999998
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0112249800, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1170.21 < 1320.21
  -> Decision False in time 0.0300000000, query time of that 0.0328322920, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
847.647 < 855.679
  -> Decision False in time 0.0800000000, query time of that 0.0777795030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0119745510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1269.08 < 1286.45
  -> Decision False in time 0.0200000000, query time of that 0.0192671680, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1531.32 < 1562.24
  -> Decision False in time 0.0100000000, query time of that 0.0114447360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
990.661 < 1062.06
  -> Decision False in time 0.0200000000, query time of that 0.0112202270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
914.157 < 1012.56
  -> Decision False in time 0.0100000000, query time of that 0.0126800250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1223.37 < 1224.84
  -> Decision False in time 0.0400000000, query time of that 0.0124725210, 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 64.98000000000002
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0241014470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2331155040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1547.45 < 1554.36
  -> Decision False in time 0.4500000000, query time of that 0.4350239680, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0278612400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
883.685 < 966.162
  -> Decision False in time 0.2800000000, query time of that 0.2654672820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1293.7 < 1331.04
  -> Decision False in time 0.0600000000, query time of that 0.0671315870, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1401.22 < 1420.49
  -> Decision False in time 0.0300000000, query time of that 0.0258317610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1327.62 < 1336.71
  -> Decision False in time 0.0300000000, query time of that 0.0251916170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
897.792 < 948.209
  -> Decision False in time 0.0500000000, query time of that 0.0281967270, 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 18.0
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0510560500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5064607560, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9300000000, query time of that 4.8768999880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0561259140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
881.263 < 959.2
  -> Decision False in time 0.3100000000, query time of that 0.3056937410, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2070.16 < 2107.34
  -> Decision False in time 2.1100000000, query time of that 2.0839659730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0600558840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1100000000, query time of that 0.6503457370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1469.38 < 1470.09
  -> Decision False in time 0.2600000000, query time of that 0.1901708500, 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:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1615074620, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6500000000, query time of that 1.6516272680, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.6400000000, query time of that 16.5730976250, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1646981440, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6500000000, query time of that 1.6428531760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.8200000000, query time of that 16.7273276600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1846896970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9300000000, query time of that 1.7569561920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 18.4200000000, query time of that 17.5688203530, 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 33.7199999999998
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0140874590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1295293780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1265.33 < 1282.32
  -> Decision False in time 0.2700000000, query time of that 0.2631346850, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0157658590, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1409.89 < 1423.37
  -> Decision False in time 0.0700000000, query time of that 0.0694764380, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1056.56 < 1057.88
  -> Decision False in time 0.0200000000, query time of that 0.0190152010, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1237.4 < 1252.54
  -> Decision False in time 0.0200000000, query time of that 0.0156827590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
831.826 < 900.779
  -> Decision False in time 0.0200000000, query time of that 0.0155376810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
714.352 < 797.737
  -> Decision False in time 0.0300000000, query time of that 0.0180801060, 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 33.7800000000002
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2847893740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.8000000000, query time of that 2.7959767370, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.8700000000, query time of that 27.7875185070, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2833464890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.8400000000, query time of that 2.8213220930, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 27.9300000000, query time of that 27.8396425260, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3069087730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.9500000000, query time of that 2.8588353980, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1618.77 < 1619.5
  -> Decision False in time 18.6900000000, query time of that 18.6309051710, 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 65.19999999999982
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0353760160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3157575850, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1175.93 < 1191.44
  -> Decision False in time 0.5100000000, query time of that 0.5088783460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2299.74 < 2499.69
  -> Decision False in time 0.0400000000, query time of that 0.0337968090, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1494.39 < 1593.22
  -> Decision False in time 0.0800000000, query time of that 0.0834141040, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1062.69 < 1120.73
  -> Decision False in time 0.1700000000, query time of that 0.1614151870, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0391001620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1183.95 < 1238.53
  -> Decision False in time 0.0800000000, query time of that 0.0439283730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1229 < 1280.79
  -> Decision False in time 0.4700000000, query time of that 0.2489624490, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 200])
Got a train set of size (60000 * 784)
Built index in 64.97000000000025
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0201138160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1770.09 < 1776.43
  -> Decision False in time 0.1600000000, query time of that 0.1595253530, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1234.48 < 1237.68
  -> Decision False in time 0.5400000000, query time of that 0.5316457640, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1277.66 < 1281.82
  -> Decision False in time 0.0200000000, query time of that 0.0244205480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2105.94 < 2120.18
  -> Decision False in time 0.0800000000, query time of that 0.0782491560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1219.4 < 1258.83
  -> Decision False in time 0.0200000000, query time of that 0.0206895210, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1563.68 < 1565.52
  -> Decision False in time 0.0300000000, query time of that 0.0248290150, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1188.82 < 1190.34
  -> Decision False in time 0.0200000000, query time of that 0.0244616280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1247.98 < 1251.37
  -> Decision False in time 0.0200000000, query time of that 0.0198270950, 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 65.22000000000025
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5101719160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9700000000, query time of that 4.9586632850, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.2000000000, query time of that 49.1259853290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5100756350, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9900000000, query time of that 4.9685486850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.3900000000, query time of that 49.2964140980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.4918122970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.1100000000, query time of that 4.9854214230, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 51.0300000000, query time of that 49.9843327150, 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 33.55000000000018
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0777978560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7808045800, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8000000000, query time of that 7.7345496230, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0810084520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1501.1 < 1513.23
  -> Decision False in time 0.3700000000, query time of that 0.3731150380, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1107.84 < 1188.36
  -> Decision False in time 2.3900000000, query time of that 2.3652520960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0905278600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1300000000, query time of that 0.9804969360, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1361.42 < 1369.79
  -> Decision False in time 1.4900000000, query time of that 1.4339495240, 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 17.93000000000029
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3218179160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1400000000, query time of that 3.1331984420, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.3500000000, query time of that 31.2688103730, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3312081690, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1600000000, query time of that 3.1451826980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.5000000000, query time of that 31.4066692290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3309562810, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.3200000000, query time of that 3.2385972340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.3600000000, query time of that 32.0200243080, 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 18.289999999999054
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6000000000, query time of that 0.5963628640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.9600000000, query time of that 5.9497757460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 59.6500000000, query time of that 59.5544044010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.6096367860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.0200000000, query time of that 5.9996896820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.6300000000, query time of that 59.5288150630, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6094469970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.0700000000, query time of that 5.9792190900, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 59.9500000000, query time of that 59.6977837850, 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 34.3799999999992
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0216631990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1963892970, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
916.915 < 932.003
  -> Decision False in time 0.1300000000, query time of that 0.1320558880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0230369600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1740.13 < 1797.54
  -> Decision False in time 0.1500000000, query time of that 0.1486554340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1740.02 < 1746.6
  -> Decision False in time 0.0500000000, query time of that 0.0429889980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1202.16 < 1217.25
  -> Decision False in time 0.0300000000, query time of that 0.0257739070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1684.58 < 1697.82
  -> Decision False in time 0.0300000000, query time of that 0.0250449860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1280.56 < 1312.9
  -> Decision False in time 0.0200000000, query time of that 0.0262755080, 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 18.350000000000364
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0109505590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1115.16 < 1116.88
  -> Decision False in time 0.0300000000, query time of that 0.0274862000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
661.748 < 723.492
  -> Decision False in time 0.0500000000, query time of that 0.0464644400, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0103947650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1790.33 < 1832.55
  -> Decision False in time 0.0300000000, query time of that 0.0209956370, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1653.2 < 1764.27
  -> Decision False in time 0.0300000000, query time of that 0.0297370090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1742.87 < 1745.44
  -> Decision False in time 0.0100000000, query time of that 0.0119962830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1700.5 < 1734.45
  -> Decision False in time 0.0100000000, query time of that 0.0127660340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1487.7 < 1594.01
  -> Decision False in time 0.0200000000, query time of that 0.0105396240, 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 66.46000000000095
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0450234100, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.4254490680, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
881.381 < 961.553
  -> Decision False in time 2.6700000000, query time of that 2.6374167010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0453219370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5300000000, query time of that 0.4801910260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1582.63 < 1607.3
  -> Decision False in time 0.7500000000, query time of that 0.7395570380, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0534395430, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1323.78 < 1364.96
  -> Decision False in time 0.5300000000, query time of that 0.3652136240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1430.27 < 1433.44
  -> Decision False in time 0.0500000000, query time of that 0.0506225370, 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 66.44000000000051
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0867570050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8356042200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.4100000000, query time of that 8.3435795180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0878228580, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.9300000000, query time of that 0.8837712440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1070.13 < 1080.26
  -> Decision False in time 7.3200000000, query time of that 7.2693629770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0990606390, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1600000000, query time of that 1.0373012650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1593.74 < 1632.9
  -> Decision False in time 1.1500000000, query time of that 1.1428279840, 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 33.6299999999992
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0147039250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1272.72 < 1274.67
  -> Decision False in time 0.0300000000, query time of that 0.0278002130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1659.62 < 1685.33
  -> Decision False in time 0.0600000000, query time of that 0.0661838340, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0148139780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1243.97 < 1258.89
  -> Decision False in time 0.0400000000, query time of that 0.0384700460, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1275.31 < 1289.3
  -> Decision False in time 0.1000000000, query time of that 0.0966346700, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1439.3 < 1440.59
  -> Decision False in time 0.0100000000, query time of that 0.0155674320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1681.01 < 1738.84
  -> Decision False in time 0.0200000000, query time of that 0.0152232090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1357.81 < 1627.08
  -> Decision False in time 0.0200000000, query time of that 0.0167892010, 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:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0193766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0295962870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2686844760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1125.05 < 1137.05
  -> Decision False in time 1.9700000000, query time of that 1.9387754460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0310235040, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
880.705 < 978.865
  -> Decision False in time 0.2100000000, query time of that 0.1989015630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1365.06 < 1378.68
  -> Decision False in time 0.2600000000, query time of that 0.2597338540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1500.89 < 1506.15
  -> Decision False in time 0.0400000000, query time of that 0.0329726220, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1411.41 < 1436.48
  -> Decision False in time 0.0400000000, query time of that 0.0375166510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1003.09 < 1036.49
  -> Decision False in time 0.2500000000, query time of that 0.1180070460, 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 17.979999999999563
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0189624350, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1737018010, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1317.96 < 1382.55
  -> Decision False in time 0.4900000000, query time of that 0.4813055780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0183615300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1071.85 < 1076.45
  -> Decision False in time 0.0200000000, query time of that 0.0192729030, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1171.2 < 1195.68
  -> Decision False in time 0.2800000000, query time of that 0.2654470230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1057.69 < 1058.16
  -> Decision False in time 0.0200000000, query time of that 0.0186684600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1016.3 < 1078.09
  -> Decision False in time 0.0500000000, query time of that 0.0207874210, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
915.086 < 1184.07
  -> Decision False in time 0.0300000000, query time of that 0.0205401890, 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 17.98999999999978
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0824850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0116668850, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
962.418 < 972.127
  -> Decision False in time 0.0800000000, query time of that 0.0699475580, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1559.4 < 1580.79
  -> Decision False in time 0.1200000000, query time of that 0.1226617040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0114287830, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1260.88 < 1268.59
  -> Decision False in time 0.0500000000, query time of that 0.0453903420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
942.125 < 1021.89
  -> Decision False in time 0.0300000000, query time of that 0.0325780660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
852.5 < 872.533
  -> Decision False in time 0.0200000000, query time of that 0.0119290540, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
926.295 < 970.812
  -> Decision False in time 0.0200000000, query time of that 0.0119096930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1614.1 < 1623.08
  -> Decision False in time 0.0100000000, query time of that 0.0114669870, 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 33.70999999999913
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5508085910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.3900000000, query time of that 5.3838582880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 54.0100000000, query time of that 53.9226676280, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5452868040, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3800000000, query time of that 5.3547852920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.7900000000, query time of that 53.7036852970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.5633948940, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.5900000000, query time of that 5.4489381240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 54.4100000000, query time of that 54.1313632670, 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 65.21000000000095
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0212882740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1905905890, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
890.146 < 907.371
  -> Decision False in time 0.2200000000, query time of that 0.2139048910, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1349.31 < 1398.72
  -> Decision False in time 0.0200000000, query time of that 0.0226835230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1655.79 < 1693.32
  -> Decision False in time 0.0900000000, query time of that 0.0787276780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1643.55 < 1651.02
  -> Decision False in time 0.0700000000, query time of that 0.0734980010, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
895.943 < 924.595
  -> Decision False in time 0.0300000000, query time of that 0.0227604600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
850.439 < 945.172
  -> Decision False in time 0.0200000000, query time of that 0.0222460070, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1096.36 < 1125.78
  -> Decision False in time 0.0300000000, query time of that 0.0247871270, 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 33.72999999999956
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0392955390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3599594550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.6500000000, query time of that 3.6070432870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0411112870, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.3997857060, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
801.731 < 842.343
  -> Decision False in time 0.5500000000, query time of that 0.5455486370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0445078230, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1262.12 < 1369.38
  -> Decision False in time 0.4400000000, query time of that 0.2603487300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1235.56 < 1248.1
  -> Decision False in time 0.1400000000, query time of that 0.0889305160, 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 33.789999999999054
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0516916350, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5166734020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1800000000, query time of that 5.1247976770, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0531793130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.5446418150, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 5.5400000000, query time of that 5.3919970140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0604835550, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1200000000, query time of that 0.6695167210, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2082.93 < 2123.69
  -> Decision False in time 0.2700000000, query time of that 0.2017947060, 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 33.8700000000008
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0385416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0182762800, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1636513190, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2202.42 < 2205.09
  -> Decision False in time 0.7600000000, query time of that 0.7381167010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1518.11 < 1539.46
  -> Decision False in time 0.0200000000, query time of that 0.0182043820, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1041.23 < 1050.73
  -> Decision False in time 0.1000000000, query time of that 0.0968873490, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1642.66 < 1658.19
  -> Decision False in time 0.0200000000, query time of that 0.0222596680, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
825.302 < 830.624
  -> Decision False in time 0.0200000000, query time of that 0.0191736190, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1379.65 < 1452.98
  -> Decision False in time 0.0200000000, query time of that 0.0194903110, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
889.857 < 918.855
  -> Decision False in time 0.0300000000, query time of that 0.0206505760, 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 33.80999999999949
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0273424480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2487669600, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.5500000000, query time of that 2.5130063590, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0298587390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1893.36 < 1943.71
  -> Decision False in time 0.1100000000, query time of that 0.1053662930, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1393.72 < 1414.66
  -> Decision False in time 0.0400000000, query time of that 0.0306516220, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0321293010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1164.56 < 1178.3
  -> Decision False in time 0.1400000000, query time of that 0.0688668640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1122.4 < 1141.64
  -> Decision False in time 0.0300000000, query time of that 0.0289740770, 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 65.0
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2667058970, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6400000000, query time of that 2.6265857750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.3800000000, query time of that 26.3112630650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2688270570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6800000000, query time of that 2.6644816180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.4800000000, query time of that 26.3938574550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2760165160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8200000000, query time of that 2.7000699350, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1387.45 < 1496.03
  -> Decision False in time 3.3300000000, query time of that 3.3209296270, with c1=5.0000000000, c2=0.1000000000
