copying files to /scratch...
starting benchmark...
/scratch/knn/venv/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
running only annoy
order: [Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 10000]), 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, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]), 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, 200]), 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, 2000]), 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, 40000]), 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', 100, 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', 400, 1000]), 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, 40000]), 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', 400, 2000]), 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, 200]), 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, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]), 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, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 40000])
Got a train set of size (60000 * 784)
Built index in 17.95
Index size:  304620.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1123355050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.1096933830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 11.2200000000, query time of that 11.1464922580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1231094060, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1400000000, query time of that 1.1191767300, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.1000000000, query time of that 11.0194000200, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1163182670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.2732879920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1455.44 < 1504.21
  -> Decision False in time 5.9400000000, query time of that 5.8989281550, 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 34.15999999999997
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0222681540, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2054367720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1548.64 < 1565.37
  -> Decision False in time 0.7200000000, query time of that 0.7076109170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0218298510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1169.05 < 1213.72
  -> Decision False in time 0.1100000000, query time of that 0.1061530700, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1557.98 < 1628.22
  -> Decision False in time 0.0700000000, query time of that 0.0719061550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1149.17 < 1178.88
  -> Decision False in time 0.0900000000, query time of that 0.0244559680, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1683.19 < 1744.18
  -> Decision False in time 0.0200000000, query time of that 0.0249092950, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1589.94 < 1621.29
  -> Decision False in time 0.1200000000, query time of that 0.0537461240, 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 65.96000000000004
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0502667530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4955040920, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9100000000, query time of that 4.8535071090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0514744740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1701.6 < 1758.18
  -> Decision False in time 0.4700000000, query time of that 0.4629024570, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1333.6 < 1344.88
  -> Decision False in time 5.1800000000, query time of that 5.1321746630, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0609805340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0800000000, query time of that 0.6934133440, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1582.67 < 1605.9
  -> Decision False in time 1.4400000000, query time of that 1.0822342850, 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 34.09999999999991
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3711383210, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.7400000000, query time of that 3.7327199510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.6700000000, query time of that 36.5834786580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3742508390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.6600000000, query time of that 3.6420504030, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.4400000000, query time of that 36.3446665780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.3694816970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.8600000000, query time of that 3.7723540350, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 37.8000000000, query time of that 37.5705537150, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 10000])
Got a train set of size (60000 * 784)
Built index in 18.289999999999964
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0028783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0428639580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4405125770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3300000000, query time of that 4.2765142720, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1402.89 < 1447.7
  -> Decision False in time 0.0500000000, query time of that 0.0456598360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4716887070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1406.55 < 1466.45
  -> Decision False in time 0.7300000000, query time of that 0.7151260720, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0488003990, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1660.88 < 1777.49
  -> Decision False in time 0.2400000000, query time of that 0.1591034070, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2217.94 < 2234.25
  -> Decision False in time 0.1800000000, query time of that 0.1111538050, 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 33.970000000000255
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0165887290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1786.05 < 1789.65
  -> Decision False in time 0.1200000000, query time of that 0.1111580080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1432.61 < 1573.45
  -> Decision False in time 0.0600000000, query time of that 0.0579510390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1811.28 < 1877.29
  -> Decision False in time 0.0100000000, query time of that 0.0168681630, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1610.58 < 1631.8
  -> Decision False in time 0.0500000000, query time of that 0.0403974950, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1667.47 < 1691.21
  -> Decision False in time 0.0700000000, query time of that 0.0732393050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1671.34 < 1689.14
  -> Decision False in time 0.0200000000, query time of that 0.0159002020, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1707.52 < 1809.87
  -> Decision False in time 0.0300000000, query time of that 0.0190606650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1203.26 < 1270.83
  -> Decision False in time 0.0200000000, query time of that 0.0192006900, 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 65.80000000000018
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0157252040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1460795960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1890.07 < 1948.96
  -> Decision False in time 0.1000000000, query time of that 0.1036322650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1496.99 < 1756.28
  -> Decision False in time 0.0200000000, query time of that 0.0144146430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
977.422 < 1093.22
  -> Decision False in time 0.0400000000, query time of that 0.0447634520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1146.2 < 1156.2
  -> Decision False in time 0.0600000000, query time of that 0.0554788820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1734.54 < 1853.71
  -> Decision False in time 0.0200000000, query time of that 0.0165035660, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1814.8 < 1842.7
  -> Decision False in time 0.0200000000, query time of that 0.0172332800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1126.92 < 1175.61
  -> Decision False in time 0.0100000000, query time of that 0.0158864730, 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 18.16000000000031
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0715640890, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6675629080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1939.2 < 1948.58
  -> Decision False in time 2.7000000000, query time of that 2.6792293860, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0687333450, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.6924928530, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1857 < 1862.6
  -> Decision False in time 1.9100000000, query time of that 1.8941753710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0872746410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1698.82 < 1706.45
  -> Decision False in time 0.7200000000, query time of that 0.6422824730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1662.39 < 1672.32
  -> Decision False in time 1.9400000000, query time of that 1.8132987350, 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 33.92000000000007
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2318707820, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0700000000, query time of that 2.0642443680, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.3900000000, query time of that 20.3223245730, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1936814940, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.1200000000, query time of that 2.0977757990, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.3500000000, query time of that 20.2402183920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.2431015110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3800000000, query time of that 2.1910567970, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 22.1500000000, query time of that 21.5704103240, 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 18.170000000000073
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2287355460, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3300000000, query time of that 2.3145338470, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 22.8600000000, query time of that 22.7839061280, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2335556470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.3000000000, query time of that 2.2884806260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 22.8000000000, query time of that 22.6929036850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.2474408740, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.5200000000, query time of that 2.3891164430, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1514.4 < 1664.69
  -> Decision False in time 14.3200000000, query time of that 14.2626768400, 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 33.67000000000007
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0286275870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2756307540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.7700000000, query time of that 2.7133794150, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1600.19 < 1612.84
  -> Decision False in time 0.0300000000, query time of that 0.0293155070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3062917200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1836.72 < 1844.58
  -> Decision False in time 0.9800000000, query time of that 0.9593948480, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0307666410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1645.75 < 1666.14
  -> Decision False in time 0.0500000000, query time of that 0.0343258170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1137.15 < 1281.52
  -> Decision False in time 0.3700000000, query time of that 0.1659913070, 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 65.74000000000069
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3597022960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4500000000, query time of that 3.4381957230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.6100000000, query time of that 33.5309743750, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3376702330, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.3600000000, query time of that 3.3394555200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 33.5400000000, query time of that 33.4481510350, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.3493116880, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.5300000000, query time of that 3.4349858970, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.4000000000, query time of that 34.1453503330, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 1000])
Got a train set of size (60000 * 784)
Built index in 18.3100000000004
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Reject!
1793.14 < 1876.37
  -> Decision False in time 0.0100000000, query time of that 0.0148514010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1488.18 < 1495.98
  -> Decision False in time 0.1100000000, query time of that 0.1000245510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1825.83 < 1895.81
  -> Decision False in time 0.2200000000, query time of that 0.2142046760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0145033010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1624.85 < 1647.18
  -> Decision False in time 0.0200000000, query time of that 0.0161257590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1665.33 < 1715.51
  -> Decision False in time 0.0300000000, query time of that 0.0261446500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1449.4 < 1605.16
  -> Decision False in time 0.0100000000, query time of that 0.0156374090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1405.27 < 1420.94
  -> Decision False in time 0.1400000000, query time of that 0.0325298590, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1091.99 < 1272.45
  -> Decision False in time 0.0200000000, query time of that 0.0168504580, 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 66.09000000000015
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0152455760, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1886.44 < 1919.86
  -> Decision False in time 0.0500000000, query time of that 0.0473199240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1626.95 < 1737.51
  -> Decision False in time 0.0600000000, query time of that 0.0628116870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1630.43 < 1678.19
  -> Decision False in time 0.0200000000, query time of that 0.0153768010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1612.73 < 1613.25
  -> Decision False in time 0.0400000000, query time of that 0.0396805170, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1713.36 < 1951.39
  -> Decision False in time 0.0200000000, query time of that 0.0168739270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1217.43 < 1245.21
  -> Decision False in time 0.0100000000, query time of that 0.0165207750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1875.2 < 1970.22
  -> Decision False in time 0.0200000000, query time of that 0.0167649740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1193.59 < 1258.03
  -> Decision False in time 0.0300000000, query time of that 0.0204633690, 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 34.19000000000051
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0128549470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1979.84 < 1996.27
  -> Decision False in time 0.0600000000, query time of that 0.0594697090, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1938.74 < 1963.6
  -> Decision False in time 0.1300000000, query time of that 0.1287618500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1596.63 < 1686.12
  -> Decision False in time 0.0200000000, query time of that 0.0118932640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1690.57 < 1693.41
  -> Decision False in time 0.0400000000, query time of that 0.0424632820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1554.34 < 1573.07
  -> Decision False in time 0.0100000000, query time of that 0.0122350610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1591.12 < 1591.9
  -> Decision False in time 0.0200000000, query time of that 0.0118573190, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1415.96 < 1569.31
  -> Decision False in time 0.0200000000, query time of that 0.0133784890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1418.22 < 1571.47
  -> Decision False in time 0.0200000000, query time of that 0.0138097650, 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 18.18000000000029
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0229533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0192130780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1822852670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1558.68 < 1620.74
  -> Decision False in time 0.1300000000, query time of that 0.1203415000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0196320620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1681.38 < 1706.63
  -> Decision False in time 0.1300000000, query time of that 0.1238698970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1605.8 < 1636.18
  -> Decision False in time 0.2000000000, query time of that 0.1925412300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1749.88 < 1790.19
  -> Decision False in time 0.0200000000, query time of that 0.0188360270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1776.33 < 1861.18
  -> Decision False in time 0.0200000000, query time of that 0.0219368260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1172.98 < 1204.25
  -> Decision False in time 0.0300000000, query time of that 0.0213357750, 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 34.01000000000022
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Reject!
1222.12 < 1483.39
  -> Decision False in time 0.0100000000, query time of that 0.0116215710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1099158190, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1429.36 < 1630.58
  -> Decision False in time 0.0200000000, query time of that 0.0175490400, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1353.4 < 1430.25
  -> Decision False in time 0.0100000000, query time of that 0.0123539610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1225.28 < 1279.62
  -> Decision False in time 0.0300000000, query time of that 0.0245428890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1006.07 < 1039.42
  -> Decision False in time 0.0100000000, query time of that 0.0118965320, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1520.74 < 1546.03
  -> Decision False in time 0.0200000000, query time of that 0.0122924130, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1310.57 < 1435.28
  -> Decision False in time 0.0100000000, query time of that 0.0138603270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1428.41 < 1436.1
  -> Decision False in time 0.0200000000, query time of that 0.0121694530, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 40000])
Got a train set of size (60000 * 784)
Built index in 65.78000000000065
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1087095020, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0794687590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.6400000000, query time of that 10.5754475550, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1099245470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1200000000, query time of that 1.1085310410, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.0000000000, query time of that 10.9170799300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1257739300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.3900000000, query time of that 1.2345119660, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1890.31 < 1920
  -> Decision False in time 6.4600000000, query time of that 6.4152939480, 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 33.92000000000007
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0136180300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1439.9 < 1648.88
  -> Decision False in time 0.0100000000, query time of that 0.0184039320, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2019.42 < 2150.41
  -> Decision False in time 0.0600000000, query time of that 0.0554088860, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1191.16 < 1265.03
  -> Decision False in time 0.0100000000, query time of that 0.0107721620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1559.75 < 1566.73
  -> Decision False in time 0.0400000000, query time of that 0.0299291790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1314.08 < 1487.73
  -> Decision False in time 0.0200000000, query time of that 0.0231462510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1402.97 < 1807.05
  -> Decision False in time 0.0100000000, query time of that 0.0122504160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1574.65 < 1642.96
  -> Decision False in time 0.0200000000, query time of that 0.0125448580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
915.35 < 985.166
  -> Decision False in time 0.0100000000, query time of that 0.0122267480, 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 18.13000000000011
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0101476390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1582.72 < 1595.25
  -> Decision False in time 0.0200000000, query time of that 0.0150820260, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1062.19 < 1088.98
  -> Decision False in time 0.0600000000, query time of that 0.0551612200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1782.52 < 1872.05
  -> Decision False in time 0.0100000000, query time of that 0.0097695080, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1498.24 < 1556.45
  -> Decision False in time 0.0200000000, query time of that 0.0206332010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1065.15 < 1079.39
  -> Decision False in time 0.0200000000, query time of that 0.0244155090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1621.77 < 1633.21
  -> Decision False in time 0.0100000000, query time of that 0.0102611520, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1577.9 < 1583.84
  -> Decision False in time 0.0200000000, query time of that 0.0099993490, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1319.64 < 1460.07
  -> Decision False in time 0.0100000000, query time of that 0.0105953700, 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 34.11999999999989
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0463054080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4454991630, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4600000000, query time of that 4.4064540170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0465746760, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4802313840, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1786.6 < 1801.45
  -> Decision False in time 2.5100000000, query time of that 2.4778728320, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1350.26 < 1360.87
  -> Decision False in time 0.0900000000, query time of that 0.0505470320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1917.94 < 1932.49
  -> Decision False in time 0.7800000000, query time of that 0.5290064260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1643.65 < 1644.41
  -> Decision False in time 0.0400000000, query time of that 0.0467178080, 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 34.11999999999989
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0680123450, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6600000000, query time of that 0.6535454160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7200000000, query time of that 6.6545730210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0666968270, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6885995510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1582.46 < 1601.28
  -> Decision False in time 4.3600000000, query time of that 4.3211346980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0820746700, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1300000000, query time of that 0.8971818090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1562.93 < 1595.64
  -> Decision False in time 9.5000000000, query time of that 8.3758072590, 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 65.8100000000004
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0210898500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1953574470, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1684.69 < 1697.68
  -> Decision False in time 0.0800000000, query time of that 0.0753233120, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0216938100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1429.61 < 1526.12
  -> Decision False in time 0.0500000000, query time of that 0.0496454160, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1406.81 < 1479.9
  -> Decision False in time 0.1100000000, query time of that 0.1062567630, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1843.17 < 1843.91
  -> Decision False in time 0.0400000000, query time of that 0.0250306590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1839.2 < 1839.33
  -> Decision False in time 0.0300000000, query time of that 0.0253054540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1502.66 < 1632.95
  -> Decision False in time 0.0400000000, query time of that 0.0226205080, 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 33.779999999999745
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.7101778150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.9300000000, query time of that 6.9235017110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 69.0800000000, query time of that 68.9879150840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6850356490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.8800000000, query time of that 6.8614108550, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 68.7900000000, query time of that 68.6935743680, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7188550570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.0000000000, query time of that 6.9138095340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 69.3500000000, query time of that 69.1558069560, 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 33.659999999999854
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1114571250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0600000000, query time of that 1.0584055650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.2200000000, query time of that 10.1566304550, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1021192080, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.0800000000, query time of that 1.0641664530, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1787.41 < 1818.04
  -> Decision False in time 3.9000000000, query time of that 3.8716964770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1189854130, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1784.18 < 1819.94
  -> Decision False in time 0.2400000000, query time of that 0.2312807680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1763.7 < 1805.48
  -> Decision False in time 2.4000000000, query time of that 2.3809392340, 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 18.020000000000437
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7747224700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.6600000000, query time of that 7.6500997070, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 75.3900000000, query time of that 75.2945567630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7547984270, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.5700000000, query time of that 7.5579059440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 76.2100000000, query time of that 76.1013912200, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8700000000, query time of that 0.7905091330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.7600000000, query time of that 7.6694770700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 76.9700000000, query time of that 76.5934475360, 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 65.25
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0172116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0261653050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2414789040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1760.23 < 1795.15
  -> Decision False in time 0.0500000000, query time of that 0.0474096020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0268294520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1824.11 < 1888.41
  -> Decision False in time 0.0900000000, query time of that 0.0892971680, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1812.2 < 1820.61
  -> Decision False in time 0.1500000000, query time of that 0.1439520180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1357.29 < 1477.27
  -> Decision False in time 0.0400000000, query time of that 0.0296064460, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1479.12 < 1526.9
  -> Decision False in time 0.0300000000, query time of that 0.0311832160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1435.91 < 1501.38
  -> Decision False in time 0.0300000000, query time of that 0.0270800510, 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 18.020000000000437
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4333220910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.2500000000, query time of that 4.2403661480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.6900000000, query time of that 42.6042816630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4286668020, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.2400000000, query time of that 4.2294981690, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.1200000000, query time of that 42.0210965000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4292603440, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.3400000000, query time of that 4.2487193740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 42.9900000000, query time of that 42.8223814430, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 200])
Got a train set of size (60000 * 784)
Built index in 17.909999999999854
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Reject!
1301.82 < 1488.48
  -> Decision False in time 0.0100000000, query time of that 0.0101786720, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1497.33 < 1550.18
  -> Decision False in time 0.0300000000, query time of that 0.0224604860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1294.92 < 1318.59
  -> Decision False in time 0.0100000000, query time of that 0.0105896360, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1514.19 < 1523.59
  -> Decision False in time 0.0100000000, query time of that 0.0097726750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1557.06 < 1593.86
  -> Decision False in time 0.0100000000, query time of that 0.0100458570, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1836.76 < 1930.92
  -> Decision False in time 0.0100000000, query time of that 0.0099501340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1651.41 < 1742.02
  -> Decision False in time 0.0100000000, query time of that 0.0096946970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1475.67 < 1481.33
  -> Decision False in time 0.0200000000, query time of that 0.0106361330, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1126.29 < 1168.5
  -> Decision False in time 0.0100000000, query time of that 0.0106709020, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 400])
Got a train set of size (60000 * 784)
Built index in 64.90999999999985
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0167573600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1444.62 < 1636.49
  -> Decision False in time 0.1400000000, query time of that 0.1414181820, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1227.68 < 1264.88
  -> Decision False in time 0.1200000000, query time of that 0.1164706840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1792.94 < 1796.53
  -> Decision False in time 0.0200000000, query time of that 0.0163407230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1259.63 < 1454.34
  -> Decision False in time 0.0300000000, query time of that 0.0280051740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1755.93 < 1787.67
  -> Decision False in time 0.0200000000, query time of that 0.0169198510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1586.02 < 1592.52
  -> Decision False in time 0.0200000000, query time of that 0.0162387240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1560.08 < 1599.08
  -> Decision False in time 0.0200000000, query time of that 0.0178604190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1535.55 < 1606.48
  -> Decision False in time 0.0100000000, query time of that 0.0180658640, 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 18.139999999999418
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0112472860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1759.02 < 1788.72
  -> Decision False in time 0.0600000000, query time of that 0.0579149620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1904.31 < 1936.25
  -> Decision False in time 0.0800000000, query time of that 0.0703649000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1014.76 < 1035.44
  -> Decision False in time 0.0100000000, query time of that 0.0101519710, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1273.8 < 1317.75
  -> Decision False in time 0.0200000000, query time of that 0.0185404110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1623.96 < 1682.75
  -> Decision False in time 0.0100000000, query time of that 0.0103498190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1474.71 < 1634.09
  -> Decision False in time 0.0100000000, query time of that 0.0102217790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
950.835 < 1116.29
  -> Decision False in time 0.0100000000, query time of that 0.0102422350, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1420.88 < 1563.76
  -> Decision False in time 0.0100000000, query time of that 0.0109788160, 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:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6368041710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.1100000000, query time of that 6.1033581270, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.2600000000, query time of that 61.1614202970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.6148033100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.1700000000, query time of that 6.1517788940, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 61.5200000000, query time of that 61.4224932290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7400000000, query time of that 0.6638424670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.3400000000, query time of that 6.2602931520, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 62.0100000000, query time of that 61.7694178610, 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 65.34000000000015
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0339590590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3213845300, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1419.54 < 1482.86
  -> Decision False in time 1.3600000000, query time of that 1.3435613730, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0337359130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2006.96 < 2033.84
  -> Decision False in time 0.1800000000, query time of that 0.1769665260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2060.89 < 2094.53
  -> Decision False in time 0.3600000000, query time of that 0.3547160700, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0424147570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1541.29 < 1644.18
  -> Decision False in time 0.4600000000, query time of that 0.2425931460, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1888.65 < 1889.02
  -> Decision False in time 0.2100000000, query time of that 0.1169721930, 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 65.10000000000218
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1943686990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0200000000, query time of that 2.0088087420, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.7000000000, query time of that 19.6240470930, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2110849020, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.9800000000, query time of that 1.9579326760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.8200000000, query time of that 19.7330461890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3100000000, query time of that 0.2343958760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3300000000, query time of that 2.1267796290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1940.55 < 1969.4
  -> Decision False in time 14.0900000000, query time of that 14.0256895050, 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 65.4800000000032
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0769810130, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.7072436350, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.1200000000, query time of that 7.0599199440, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0807282930, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7489768180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1906.79 < 1950.53
  -> Decision False in time 0.2700000000, query time of that 0.2665905030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0819054280, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1457.71 < 1471.65
  -> Decision False in time 0.7800000000, query time of that 0.7345977070, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1906.01 < 1997.82
  -> Decision False in time 0.9100000000, query time of that 0.8437608250, 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 18.0
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0250045830, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2606091540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1774.23 < 1842.21
  -> Decision False in time 0.4100000000, query time of that 0.4032513770, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0277230160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1463.65 < 1540.99
  -> Decision False in time 0.1500000000, query time of that 0.1485228130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1785.95 < 1870.66
  -> Decision False in time 0.1300000000, query time of that 0.1329016080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1622.03 < 1622.94
  -> Decision False in time 0.0700000000, query time of that 0.0310668300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1833.01 < 1835.3
  -> Decision False in time 0.0900000000, query time of that 0.0347678650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1585.95 < 1600.31
  -> Decision False in time 0.0300000000, query time of that 0.0305436560, with c1=5.0000000000, c2=0.1000000000
