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, 400000]), 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', 100, 20000]), 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', 400, 200000]), 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', 100, 400]), 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, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]), 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', 400, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), 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, 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', 100, 40000]), 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', 200, 400]), 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, 20000]), 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', 200, 100000]), 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, 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', 400, 10000]), 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, 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', 200, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 400000])
Got a train set of size (60000 * 784)
Built index in 45.39
Index size:  395976.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7500000000, query time of that 0.7468062590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.8200000000, query time of that 6.8003226000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 68.3500000000, query time of that 68.2629850710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6971813660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.9400000000, query time of that 6.9206968700, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 69.1900000000, query time of that 69.0851775020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7068866540, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.9800000000, query time of that 6.8828376410, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 69.2200000000, query time of that 68.9910568600, 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 33.76000000000022
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0168453800, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1842.09 < 1878.42
  -> Decision False in time 0.1300000000, query time of that 0.1218817700, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1796.77 < 1818.99
  -> Decision False in time 0.1800000000, query time of that 0.1724890380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0176624220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1467.05 < 1488.08
  -> Decision False in time 0.0600000000, query time of that 0.0584083470, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1357.69 < 1388.77
  -> Decision False in time 0.0600000000, query time of that 0.0580477810, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0190611390, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1300.21 < 1398.98
  -> Decision False in time 0.0800000000, query time of that 0.0195049700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1890.64 < 1998.21
  -> Decision False in time 0.0300000000, query time of that 0.0208288330, 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 18.019999999999982
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0763555720, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1528.61 < 1577.69
  -> Decision False in time 0.2100000000, query time of that 0.2080453160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1552.17 < 1594.1
  -> Decision False in time 1.7800000000, query time of that 1.7620790320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0758138920, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7095465520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.0600000000, query time of that 6.8872923000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0747706080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1400000000, query time of that 0.8782061480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1943.33 < 2004.89
  -> Decision False in time 1.8400000000, query time of that 1.6296820320, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 40000])
Got a train set of size (60000 * 784)
Built index in 64.98000000000002
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1131447810, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0880191400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.6000000000, query time of that 10.5317838870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1033062750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1400000000, query time of that 1.1122515120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1906.79 < 1949.42
  -> Decision False in time 3.5400000000, query time of that 3.5235333580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1119087620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1909.67 < 1939.52
  -> Decision False in time 0.2300000000, query time of that 0.2303028930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2005.11 < 2060.89
  -> Decision False in time 4.7200000000, query time of that 4.6891158630, 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 65.07000000000016
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3512954420, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4700000000, query time of that 3.4654099460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.8700000000, query time of that 33.7800159700, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3493276480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.4300000000, query time of that 3.4085016070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 33.8100000000, query time of that 33.7223120500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.3687236200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.5600000000, query time of that 3.4350018730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.7600000000, query time of that 34.4768195580, 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 64.94999999999982
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0153624080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1608.33 < 1889.15
  -> Decision False in time 0.0600000000, query time of that 0.0635598690, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1492.76 < 1539
  -> Decision False in time 0.1000000000, query time of that 0.0912353640, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1530.95 < 1651.91
  -> Decision False in time 0.0200000000, query time of that 0.0161156500, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1570.33 < 1607.82
  -> Decision False in time 0.0100000000, query time of that 0.0155265160, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1632.7 < 1707.79
  -> Decision False in time 0.0200000000, query time of that 0.0151364270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1565.5 < 1722.09
  -> Decision False in time 0.0200000000, query time of that 0.0172418770, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1078.11 < 1136.36
  -> Decision False in time 0.0200000000, query time of that 0.0157987050, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1769.96 < 1776.35
  -> Decision False in time 0.0200000000, query time of that 0.0167844820, 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 17.99000000000069
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Reject!
1638.63 < 1873.91
  -> Decision False in time 0.0100000000, query time of that 0.0099544410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1930.07 < 2046.06
  -> Decision False in time 0.0300000000, query time of that 0.0234314290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1835.83 < 1839.95
  -> Decision False in time 0.0200000000, query time of that 0.0206167680, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1201.32 < 1213.38
  -> Decision False in time 0.0100000000, query time of that 0.0102214910, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1855.15 < 1869.16
  -> Decision False in time 0.0200000000, query time of that 0.0172767100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1983.01 < 2010.76
  -> Decision False in time 0.0100000000, query time of that 0.0097222130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1437.74 < 1460.4
  -> Decision False in time 0.0100000000, query time of that 0.0100657970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1523.03 < 1597.25
  -> Decision False in time 0.0100000000, query time of that 0.0099725670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1423.68 < 1459.03
  -> Decision False in time 0.0100000000, query time of that 0.0103727940, 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 65.05000000000018
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0216337370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1936358330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1801.22 < 1863.03
  -> Decision False in time 0.1500000000, query time of that 0.1487729940, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1765.12 < 1836.82
  -> Decision False in time 0.0300000000, query time of that 0.0235477190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1359.47 < 1410.13
  -> Decision False in time 0.0300000000, query time of that 0.0294728100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1165.91 < 1202.67
  -> Decision False in time 0.1200000000, query time of that 0.1162119150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1468.59 < 1552.71
  -> Decision False in time 0.0400000000, query time of that 0.0235703240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1355.49 < 1435.17
  -> Decision False in time 0.0200000000, query time of that 0.0220091680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1512.23 < 1515.76
  -> Decision False in time 0.0300000000, query time of that 0.0212951100, 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 18.039999999999964
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0028783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0467372270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4337471560, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1925.25 < 1959.88
  -> Decision False in time 4.0600000000, query time of that 4.0170985440, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0520757860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4617289640, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1561.47 < 1654.01
  -> Decision False in time 2.2300000000, query time of that 2.2114131360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0499768340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0600000000, query time of that 0.6134475530, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1559.72 < 1635.21
  -> Decision False in time 0.6200000000, query time of that 0.4160734460, 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 65.07999999999993
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6500000000, query time of that 0.6529412550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.2900000000, query time of that 6.2823962360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.8000000000, query time of that 61.6983567090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6299635760, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.1900000000, query time of that 6.1779580940, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 61.4600000000, query time of that 61.3470341320, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6329904260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.2400000000, query time of that 6.1531046710, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 61.7300000000, query time of that 61.5043418930, 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 18.039999999999964
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0101539650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2178.55 < 2182.15
  -> Decision False in time 0.0500000000, query time of that 0.0447747940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1363.65 < 1387.59
  -> Decision False in time 0.1100000000, query time of that 0.1079646370, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1332.23 < 1385.78
  -> Decision False in time 0.0100000000, query time of that 0.0094557390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1372.26 < 1401.6
  -> Decision False in time 0.0100000000, query time of that 0.0097504220, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1354.07 < 1369.23
  -> Decision False in time 0.0200000000, query time of that 0.0181271140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1203.69 < 1314.82
  -> Decision False in time 0.0200000000, query time of that 0.0113369790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1541.92 < 1617.27
  -> Decision False in time 0.0100000000, query time of that 0.0112679490, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1174.53 < 1258.01
  -> Decision False in time 0.0100000000, query time of that 0.0106054090, 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: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0321736110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3215813850, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.2600000000, query time of that 3.2045768370, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0367755890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3727223030, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1509.88 < 1529.78
  -> Decision False in time 0.9600000000, query time of that 0.9398128970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1842.49 < 1851.86
  -> Decision False in time 0.0500000000, query time of that 0.0380596570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1580.01 < 1591.36
  -> Decision False in time 0.0500000000, query time of that 0.0419285100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1130.98 < 1156.65
  -> Decision False in time 0.1300000000, query time of that 0.0809353770, 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 33.89000000000033
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0467477980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.4542265360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1520.92 < 1539.29
  -> Decision False in time 1.4800000000, query time of that 1.4668003000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0496124440, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.4790977190, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1586.01 < 1713.98
  -> Decision False in time 2.2200000000, query time of that 2.2006473440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0520418730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0600000000, query time of that 0.6183556790, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1774.73 < 1790.83
  -> Decision False in time 0.7800000000, query time of that 0.5343282580, 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 65.07000000000062
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Reject!
2004.83 < 2010
  -> Decision False in time 0.0200000000, query time of that 0.0153512730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1545.44 < 1692.69
  -> Decision False in time 0.0600000000, query time of that 0.0621393100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1462.86 < 1565.38
  -> Decision False in time 0.1500000000, query time of that 0.1507245450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2099.5 < 2123.83
  -> Decision False in time 0.0200000000, query time of that 0.0144117740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1373.24 < 1423.62
  -> Decision False in time 0.0400000000, query time of that 0.0465716040, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2030.81 < 2158.22
  -> Decision False in time 0.0400000000, query time of that 0.0305920850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1694.88 < 1830.92
  -> Decision False in time 0.0100000000, query time of that 0.0154761980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1261.49 < 1284.43
  -> Decision False in time 0.0200000000, query time of that 0.0183706950, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1807.31 < 1815.66
  -> Decision False in time 0.0200000000, query time of that 0.0189801970, 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 65.11000000000058
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0184084790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1455.59 < 1528.73
  -> Decision False in time 0.0500000000, query time of that 0.0460418710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1391.75 < 1486.98
  -> Decision False in time 0.0600000000, query time of that 0.0563626660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1360.46 < 1371
  -> Decision False in time 0.0200000000, query time of that 0.0167323710, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1378.99 < 1417.19
  -> Decision False in time 0.0300000000, query time of that 0.0319424120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1822.97 < 1836.95
  -> Decision False in time 0.0400000000, query time of that 0.0353555950, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1918.11 < 1973.39
  -> Decision False in time 0.0100000000, query time of that 0.0166742860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1741.49 < 1756.42
  -> Decision False in time 0.0200000000, query time of that 0.0156279400, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1527.09 < 1548.97
  -> Decision False in time 0.0200000000, query time of that 0.0176067790, 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 33.55999999999949
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3710002250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.7300000000, query time of that 3.7205643980, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.6500000000, query time of that 36.5560383000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3666887050, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.6800000000, query time of that 3.6571276380, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.8200000000, query time of that 36.7238092860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.3803812290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.8300000000, query time of that 3.7122230760, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 37.1200000000, query time of that 36.8912074740, 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 64.93000000000029
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.2026673140, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0200000000, query time of that 2.0086152200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.1100000000, query time of that 20.0314066820, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2158528620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0200000000, query time of that 1.9900049050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.9800000000, query time of that 19.8227333970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2196137660, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.1800000000, query time of that 2.0604914630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.6600000000, query time of that 20.6219834870, 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 33.57999999999993
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0691579670, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6841408020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7000000000, query time of that 6.6333839080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0712962670, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7400000000, query time of that 0.7105518200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.0700000000, query time of that 6.9625447750, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0760078280, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 0.8615978670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1683.9 < 1695.27
  -> Decision False in time 1.5800000000, query time of that 1.3779093120, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 2000])
Got a train set of size (60000 * 784)
Built index in 64.78000000000065
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0172116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0258955530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2503664140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.5200000000, query time of that 2.4636072120, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0287847270, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1792.04 < 1796.21
  -> Decision False in time 0.2900000000, query time of that 0.2808652230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1679.05 < 1688.01
  -> Decision False in time 0.3400000000, query time of that 0.3309996270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0303285100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1411.26 < 1455.84
  -> Decision False in time 0.0700000000, query time of that 0.0319384810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1704.44 < 1722.36
  -> Decision False in time 0.0300000000, query time of that 0.0294113140, 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 33.719999999999345
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Reject!
2091.74 < 2129.76
  -> Decision False in time 0.0100000000, query time of that 0.0118385310, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1102698470, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1430.42 < 1528.42
  -> Decision False in time 0.0100000000, query time of that 0.0156966600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1553.39 < 1563.19
  -> Decision False in time 0.0200000000, query time of that 0.0116917650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1251.85 < 1326.52
  -> Decision False in time 0.0200000000, query time of that 0.0237175420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
978.133 < 1050.97
  -> Decision False in time 0.0200000000, query time of that 0.0135886170, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1304.48 < 1313.37
  -> Decision False in time 0.0100000000, query time of that 0.0124814280, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1366.39 < 1399.5
  -> Decision False in time 0.0100000000, query time of that 0.0121691590, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1300.36 < 1418.09
  -> Decision False in time 0.0200000000, query time of that 0.0131539550, 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 18.139999999999418
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1055957910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.1043969750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.9200000000, query time of that 10.8501900380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1066554630, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1400000000, query time of that 1.1169662080, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.1100000000, query time of that 10.9985325330, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1232060550, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4400000000, query time of that 1.2558952180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1928.93 < 1988.93
  -> Decision False in time 1.1200000000, query time of that 1.1039868840, 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 33.92000000000007
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0289724040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2753769580, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.7700000000, query time of that 2.7161843790, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0296372320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3108238210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1816.25 < 1907.81
  -> Decision False in time 0.2300000000, query time of that 0.2243387120, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1554.73 < 1638.17
  -> Decision False in time 0.0600000000, query time of that 0.0333253330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1600.04 < 1642.6
  -> Decision False in time 0.0300000000, query time of that 0.0321467770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1712.53 < 1822.27
  -> Decision False in time 0.0500000000, query time of that 0.0344924910, 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 33.840000000000146
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Reject!
1965.54 < 2139.27
  -> Decision False in time 0.0200000000, query time of that 0.0126181860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1830.34 < 1849.55
  -> Decision False in time 0.0500000000, query time of that 0.0547229430, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1300.44 < 1393.65
  -> Decision False in time 0.0700000000, query time of that 0.0638696660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1928.65 < 1947.6
  -> Decision False in time 0.0100000000, query time of that 0.0123364120, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1192.74 < 1262.28
  -> Decision False in time 0.0600000000, query time of that 0.0559334070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1462.25 < 1505.78
  -> Decision False in time 0.0200000000, query time of that 0.0122653850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1421.71 < 1444.55
  -> Decision False in time 0.0100000000, query time of that 0.0127785370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1257.04 < 1268.33
  -> Decision False in time 0.0200000000, query time of that 0.0141052700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1207.5 < 1218.94
  -> Decision False in time 0.0100000000, query time of that 0.0123756390, 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 18.170000000000073
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7838259060, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.5000000000, query time of that 7.4888483900, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 75.9400000000, query time of that 75.8437911740, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7522508610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.5900000000, query time of that 7.5785327920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 77.2100000000, query time of that 77.0979026600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8500000000, query time of that 0.7723625040, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.8200000000, query time of that 7.7211805660, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.2900000000, query time of that 77.1142246600, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 20000])
Got a train set of size (60000 * 784)
Built index in 64.95999999999913
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0735556920, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6972704730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.1500000000, query time of that 7.0863393320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0798372790, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7500000000, query time of that 0.7347804000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1750.91 < 1819.28
  -> Decision False in time 2.3200000000, query time of that 2.2994740530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0850617390, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1464.13 < 1536.05
  -> Decision False in time 0.2200000000, query time of that 0.1983818560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1731.82 < 1747.84
  -> Decision False in time 0.9000000000, query time of that 0.8554548560, 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 33.51999999999862
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1065823770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0600000000, query time of that 1.0528632620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.5000000000, query time of that 10.4404996220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1152836050, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0673550940, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 10.7600000000, query time of that 10.6772688750, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1261132670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1938.48 < 1950.91
  -> Decision False in time 0.2200000000, query time of that 0.2229581470, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 13.0200000000, query time of that 12.1462940550, 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 33.600000000000364
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2274842410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0200000000, query time of that 2.0049654360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.3300000000, query time of that 20.2553223780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2059304440, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0700000000, query time of that 2.0241991460, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.5100000000, query time of that 20.4005873030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2098759610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2900000000, query time of that 2.1562413170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.8800000000, query time of that 21.4395363870, 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 17.969999999999345
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0139745210, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1426.27 < 1437.81
  -> Decision False in time 0.0800000000, query time of that 0.0752390680, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
935.352 < 987.707
  -> Decision False in time 0.1100000000, query time of that 0.1073623160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1903.8 < 1938.26
  -> Decision False in time 0.0200000000, query time of that 0.0151237280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1387.92 < 1541.23
  -> Decision False in time 0.0400000000, query time of that 0.0421742350, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1503.6 < 1594.51
  -> Decision False in time 0.0200000000, query time of that 0.0151961310, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1659.01 < 1724.49
  -> Decision False in time 0.0200000000, query time of that 0.0162860590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1534.37 < 1591.34
  -> Decision False in time 0.0100000000, query time of that 0.0153079600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1645.24 < 1682.24
  -> Decision False in time 0.0800000000, query time of that 0.0158870870, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 4000])
Got a train set of size (60000 * 784)
Built index in 18.030000000000655
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0283389580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2621487390, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1651.15 < 1655
  -> Decision False in time 1.2200000000, query time of that 1.2019305090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0290313900, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1604.98 < 1652.52
  -> Decision False in time 0.1500000000, query time of that 0.1509904660, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1810.26 < 1818.38
  -> Decision False in time 0.4900000000, query time of that 0.4764888940, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1452.57 < 1594.89
  -> Decision False in time 0.0500000000, query time of that 0.0304586040, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1633.83 < 1650.15
  -> Decision False in time 0.0400000000, query time of that 0.0341631830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1351.9 < 1503.19
  -> Decision False in time 0.2300000000, query time of that 0.0998807650, 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 17.98999999999978
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0229533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0191771160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1855292040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1729.09 < 1735.94
  -> Decision False in time 0.4800000000, query time of that 0.4696269420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0197058100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1630.5 < 1649.45
  -> Decision False in time 0.0300000000, query time of that 0.0322805520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1570.6 < 1626.81
  -> Decision False in time 0.1800000000, query time of that 0.1707544360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1599.2 < 1601.72
  -> Decision False in time 0.0500000000, query time of that 0.0214567620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1405.68 < 1522.31
  -> Decision False in time 0.0200000000, query time of that 0.0222905590, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1640.55 < 1700.33
  -> Decision False in time 0.0200000000, query time of that 0.0190652760, 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 18.039999999999054
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4385458390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.2400000000, query time of that 4.2282946850, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.2100000000, query time of that 42.1170441890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4394904500, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.2200000000, query time of that 4.2038571030, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.6700000000, query time of that 42.5622254550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.4389583630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.4300000000, query time of that 4.3297646470, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.4200000000, query time of that 43.1572224830, 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 65.38999999999942
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0518115980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4965678870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.8900000000, query time of that 4.8322770510, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0560400240, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5209554360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1669.88 < 1713.86
  -> Decision False in time 0.6900000000, query time of that 0.6817278550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0540266330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1691.88 < 1704.7
  -> Decision False in time 0.2600000000, query time of that 0.2025684770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1606.18 < 1631.57
  -> Decision False in time 1.4300000000, query time of that 1.0405748860, 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 18.100000000002183
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2236587400, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3300000000, query time of that 2.3183204780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 23.0300000000, query time of that 22.9442874340, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2154689980, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.3200000000, query time of that 2.2904517160, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 22.9000000000, query time of that 22.8171463980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.2517762340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.5800000000, query time of that 2.4337420760, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.0700000000, query time of that 23.7584986340, 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 34.13999999999942
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0121939510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1078215930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1388.49 < 1556.78
  -> Decision False in time 0.1400000000, query time of that 0.1356398450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1401.64 < 1616.58
  -> Decision False in time 0.0100000000, query time of that 0.0114314300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1145.36 < 1204.51
  -> Decision False in time 0.0200000000, query time of that 0.0174161630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1331.48 < 1518.94
  -> Decision False in time 0.0100000000, query time of that 0.0121194340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1017.46 < 1067.44
  -> Decision False in time 0.0400000000, query time of that 0.0129628620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1588.18 < 1616.5
  -> Decision False in time 0.0100000000, query time of that 0.0136730750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1560.71 < 1566.38
  -> Decision False in time 0.0200000000, query time of that 0.0138249970, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 2000])
Got a train set of size (60000 * 784)
Built index in 33.86000000000058
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0219750440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2015538730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1504.88 < 1520.88
  -> Decision False in time 0.1200000000, query time of that 0.1197629680, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1924.34 < 1942.62
  -> Decision False in time 0.0200000000, query time of that 0.0226150570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1523.99 < 1576.04
  -> Decision False in time 0.1700000000, query time of that 0.1581056310, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1629.28 < 1708.36
  -> Decision False in time 0.1700000000, query time of that 0.1753340430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1496.06 < 1510.54
  -> Decision False in time 0.0900000000, query time of that 0.0252167200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1244.97 < 1307.73
  -> Decision False in time 0.0400000000, query time of that 0.0264726080, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1077.98 < 1106.27
  -> Decision False in time 0.1500000000, query time of that 0.0522723700, 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 18.020000000000437
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0103499980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1357.59 < 1392.77
  -> Decision False in time 0.0700000000, query time of that 0.0737472080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1982.76 < 2008.93
  -> Decision False in time 0.0200000000, query time of that 0.0184122580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0100698000, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1379.75 < 1462.41
  -> Decision False in time 0.0100000000, query time of that 0.0105786400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1040.98 < 1164.25
  -> Decision False in time 0.0200000000, query time of that 0.0186712020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1516.11 < 1600.18
  -> Decision False in time 0.0100000000, query time of that 0.0104976540, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1600.59 < 1847.17
  -> Decision False in time 0.0200000000, query time of that 0.0101871750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1815.28 < 1817.66
  -> Decision False in time 0.0100000000, query time of that 0.0099170900, with c1=5.0000000000, c2=0.1000000000
