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, 20000]), 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, 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', 100, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 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', 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, 1000]), 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, 40000]), 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, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 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', 200, 10000]), 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, 100]), 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, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 20000])
Got a train set of size (60000 * 784)
Built index in 41.37
Index size:  395972.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0687951530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6831770690, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7500000000, query time of that 6.6832892110, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0713452810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6789468550, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1449.44 < 1472.57
  -> Decision False in time 0.2400000000, query time of that 0.2377645710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0680526400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1617.99 < 1621
  -> Decision False in time 0.2800000000, query time of that 0.2349332600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1412.12 < 1444.85
  -> Decision False in time 0.1800000000, query time of that 0.1493849740, 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 65.60000000000002
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6290965440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.1500000000, query time of that 6.1358234570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.6200000000, query time of that 61.5353761870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6261932150, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.2500000000, query time of that 6.2263446750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1892.22 < 1892.98
  -> Decision False in time 5.4300000000, query time of that 5.4248476820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6337076650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.3700000000, query time of that 6.2840924340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 61.6100000000, query time of that 61.4334949250, 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 66.01999999999998
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 0.0690915410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6922964640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.9800000000, query time of that 6.9193652480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0740558950, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7500000000, query time of that 0.7352693590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.3900000000, query time of that 7.2727078230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0862608180, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.2000000000, query time of that 0.9418694230, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1941.61 < 1969.82
  -> Decision False in time 2.0400000000, query time of that 1.9125131440, 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 34.13000000000011
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 0.1089506110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0600000000, query time of that 1.0555596770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.4600000000, query time of that 10.3932543880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0977867580, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0656205870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1859.34 < 1868.71
  -> Decision False in time 8.7900000000, query time of that 8.7356680180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1193238640, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.3500000000, query time of that 1.2347338740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2001.94 < 2011.83
  -> Decision False in time 8.2400000000, query time of that 8.1727632020, 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 18.190000000000055
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 0.0192485230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1834963640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1725.5 < 1816.92
  -> Decision False in time 0.0600000000, query time of that 0.0597073220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0200642890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1320.26 < 1345.42
  -> Decision False in time 0.1400000000, query time of that 0.1381244670, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1499.8 < 1500.31
  -> Decision False in time 0.0800000000, query time of that 0.0796643780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1557.98 < 1628.22
  -> Decision False in time 0.0700000000, query time of that 0.0219087200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1292.72 < 1334.59
  -> Decision False in time 0.1200000000, query time of that 0.0454958150, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1508.29 < 1510.55
  -> Decision False in time 0.0300000000, query time of that 0.0212608900, 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 18.34999999999991
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 0.0101883010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1152.38 < 1180.72
  -> Decision False in time 0.0400000000, query time of that 0.0318295620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1370.45 < 1386.07
  -> Decision False in time 0.0100000000, query time of that 0.0144472700, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1390.12 < 1469.64
  -> Decision False in time 0.0100000000, query time of that 0.0093771110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
896.231 < 1304.08
  -> Decision False in time 0.0200000000, query time of that 0.0138708110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2079.33 < 2090.16
  -> Decision False in time 0.0100000000, query time of that 0.0142915300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1319.34 < 1388.19
  -> Decision False in time 0.0100000000, query time of that 0.0097411910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1453.13 < 1462
  -> Decision False in time 0.0300000000, query time of that 0.0105023250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1635.94 < 1734.01
  -> Decision False in time 0.0200000000, query time of that 0.0112929310, 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 18.309999999999945
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Reject!
1645.31 < 1668.54
  -> Decision False in time 0.0200000000, query time of that 0.0104607680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1847.11 < 1861.52
  -> Decision False in time 0.0200000000, query time of that 0.0246782640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1179.48 < 1199.01
  -> Decision False in time 0.0700000000, query time of that 0.0687773080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1930.76 < 2106.29
  -> Decision False in time 0.0100000000, query time of that 0.0098604400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1709.81 < 1734.78
  -> Decision False in time 0.0200000000, query time of that 0.0099435870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1097.4 < 1162.79
  -> Decision False in time 0.0100000000, query time of that 0.0140369430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1423.04 < 1428.54
  -> Decision False in time 0.0100000000, query time of that 0.0101605380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1215.44 < 1248.5
  -> Decision False in time 0.0100000000, query time of that 0.0094306580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1269.96 < 1461.4
  -> Decision False in time 0.0100000000, query time of that 0.0100162190, 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 66.4699999999998
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 0.0168019160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1448498570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1819.28 < 1887.88
  -> Decision False in time 0.1100000000, query time of that 0.1061245870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1467.5 < 1515.82
  -> Decision False in time 0.0100000000, query time of that 0.0164400290, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1255.81 < 1295.04
  -> Decision False in time 0.0200000000, query time of that 0.0200977450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1930.33 < 2007.24
  -> Decision False in time 0.0400000000, query time of that 0.0361819770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1758.08 < 1841.23
  -> Decision False in time 0.0200000000, query time of that 0.0152440110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1423.15 < 1580.69
  -> Decision False in time 0.0100000000, query time of that 0.0155455780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1240.18 < 1254.98
  -> Decision False in time 0.0400000000, query time of that 0.0185840310, 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 66.44000000000005
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 0.0157081630, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1960.49 < 1981.52
  -> Decision False in time 0.0300000000, query time of that 0.0339197890, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1552.01 < 1571.01
  -> Decision False in time 0.0400000000, query time of that 0.0397374580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1464.29 < 1482.28
  -> Decision False in time 0.0200000000, query time of that 0.0156805840, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1323.72 < 1400.44
  -> Decision False in time 0.0400000000, query time of that 0.0412518290, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1663.85 < 1684.35
  -> Decision False in time 0.0200000000, query time of that 0.0182518900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1473.72 < 1506.82
  -> Decision False in time 0.0200000000, query time of that 0.0188413010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1877.3 < 2053.49
  -> Decision False in time 0.0200000000, query time of that 0.0160113560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1368.61 < 1373.51
  -> Decision False in time 0.0200000000, query time of that 0.0189941700, 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 18.370000000000346
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 0.7851365320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.6400000000, query time of that 7.6260409490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 76.4300000000, query time of that 76.3481111960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7850227160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.6800000000, query time of that 7.6635144440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 76.6500000000, query time of that 76.5431050660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8600000000, query time of that 0.7830182500, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.7600000000, query time of that 7.6665130410, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.2300000000, query time of that 76.9160977300, 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 34.029999999999745
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0163594680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1456.15 < 1483.43
  -> Decision False in time 0.1200000000, query time of that 0.1142398920, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1785.9 < 1841.75
  -> Decision False in time 0.2200000000, query time of that 0.2138362410, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0174430940, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1509.98 < 1515.99
  -> Decision False in time 0.0800000000, query time of that 0.0708882710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1400.46 < 1438.43
  -> Decision False in time 0.0300000000, query time of that 0.0367580440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0191057320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1195.18 < 1213.58
  -> Decision False in time 0.0200000000, query time of that 0.0179840480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1275.39 < 1306.76
  -> Decision False in time 0.0300000000, query time of that 0.0181665160, 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 18.230000000000473
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0643835460, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6657463870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7300000000, query time of that 6.6695518100, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0699833690, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.6913009030, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1883.14 < 1896.93
  -> Decision False in time 4.5100000000, query time of that 4.4747854130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0755552190, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 0.8908199320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1639.55 < 1670.23
  -> Decision False in time 1.1700000000, query time of that 1.0404739490, 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 65.25
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 0.0201353230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1909646650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1718.3 < 1768.26
  -> Decision False in time 0.0900000000, query time of that 0.0937643820, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1766.68 < 1787.5
  -> Decision False in time 0.0200000000, query time of that 0.0200530620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1412.74 < 1429.83
  -> Decision False in time 0.0500000000, query time of that 0.0427024410, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1545.25 < 1564.24
  -> Decision False in time 0.2200000000, query time of that 0.2207965710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1393.25 < 1451.89
  -> Decision False in time 0.0700000000, query time of that 0.0234357540, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1604.08 < 1626.1
  -> Decision False in time 0.0500000000, query time of that 0.0247137750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1422.5 < 1445.49
  -> Decision False in time 0.0300000000, query time of that 0.0236807580, 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 18.230000000000473
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.4219247470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.3000000000, query time of that 4.2886736640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.7900000000, query time of that 42.7086797140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4294428200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.2300000000, query time of that 4.2115671090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.5100000000, query time of that 42.4128461510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4255362730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.5000000000, query time of that 4.3793926030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.1500000000, query time of that 42.9142036160, 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 65.03000000000065
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1072348740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0500000000, query time of that 1.0455433060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.6700000000, query time of that 10.6043766710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1139152810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1000000000, query time of that 1.0813576670, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.0000000000, query time of that 10.9177183060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1193016630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4500000000, query time of that 1.2157320550, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1928.34 < 1951.56
  -> Decision False in time 5.8700000000, query time of that 5.8272900580, 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 18.06999999999971
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0146484590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1333076930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2058.01 < 2140.1
  -> Decision False in time 0.0900000000, query time of that 0.0911146190, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0150201780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1728.29 < 1861.39
  -> Decision False in time 0.0900000000, query time of that 0.0854916390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1743 < 1769.39
  -> Decision False in time 0.0600000000, query time of that 0.0622562710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1498.35 < 1543.33
  -> Decision False in time 0.0200000000, query time of that 0.0159656600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1802.64 < 1816.92
  -> Decision False in time 0.0200000000, query time of that 0.0150818340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1609.43 < 1701.15
  -> Decision False in time 0.0200000000, query time of that 0.0156532080, 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 65.11000000000058
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0331808920, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3259917320, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1455.34 < 1549.96
  -> Decision False in time 2.6500000000, query time of that 2.6127599080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0359697810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3525610790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2308.01 < 2332.46
  -> Decision False in time 0.5600000000, query time of that 0.5566230590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0385099840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1486.71 < 1496.87
  -> Decision False in time 0.0400000000, query time of that 0.0404116930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1810.42 < 1825.84
  -> Decision False in time 0.2000000000, query time of that 0.1062595520, 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 33.73000000000138
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6916677660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.8800000000, query time of that 6.8653544030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 68.6000000000, query time of that 68.5086192030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.7103717190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.9300000000, query time of that 6.9149654220, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 69.1600000000, query time of that 69.0643611050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8100000000, query time of that 0.7320929070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.1000000000, query time of that 6.9341357010, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 70.1000000000, query time of that 69.6599479540, 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 34.02000000000044
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 0.0302012720, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2040.14 < 2065.73
  -> Decision False in time 0.1000000000, query time of that 0.1010431920, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1418.47 < 1450.63
  -> Decision False in time 0.9900000000, query time of that 0.9750145960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0302251360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1786.12 < 1821.19
  -> Decision False in time 0.1300000000, query time of that 0.1233479430, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1774.94 < 1789.85
  -> Decision False in time 0.4200000000, query time of that 0.4078780510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1207.78 < 1248.66
  -> Decision False in time 0.1000000000, query time of that 0.0375639310, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1354.98 < 1398.14
  -> Decision False in time 0.3100000000, query time of that 0.1446602740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1404.8 < 1459.78
  -> Decision False in time 0.1600000000, query time of that 0.0711257740, 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 18.329999999999927
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 0.0445548950, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4337072940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3100000000, query time of that 4.2650608300, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0455221400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4638398050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1977.89 < 1986.39
  -> Decision False in time 1.8300000000, query time of that 1.8093176400, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0499695680, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1437.09 < 1459.38
  -> Decision False in time 0.2800000000, query time of that 0.1868230280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1587.27 < 1599.66
  -> Decision False in time 0.0500000000, query time of that 0.0514208470, 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 34.17000000000007
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3749199750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.7300000000, query time of that 3.7212385270, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.5600000000, query time of that 36.4846792810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3766278360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.7200000000, query time of that 3.7079250840, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.9200000000, query time of that 36.8191908800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.3833497710, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.8500000000, query time of that 3.7353779090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 37.3700000000, query time of that 37.1555001750, 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 34.04999999999927
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 0.0118755780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1078041610, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1647.65 < 1648.27
  -> Decision False in time 0.0300000000, query time of that 0.0305120800, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1273.39 < 1327.32
  -> Decision False in time 0.0100000000, query time of that 0.0111531150, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1631.93 < 1675.98
  -> Decision False in time 0.0100000000, query time of that 0.0150339230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1431.24 < 1745.47
  -> Decision False in time 0.0200000000, query time of that 0.0141365910, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1524.88 < 1603.45
  -> Decision False in time 0.0200000000, query time of that 0.0117835600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1466.44 < 1500.43
  -> Decision False in time 0.0100000000, query time of that 0.0133987020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1345.13 < 1352.52
  -> Decision False in time 0.0100000000, query time of that 0.0131743610, 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 65.97999999999956
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3552350680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4200000000, query time of that 3.4108328800, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 34.0400000000, query time of that 33.9619484510, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3502152160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.3600000000, query time of that 3.3389681650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 34.0400000000, query time of that 33.9500508830, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.3512218670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.4800000000, query time of that 3.3952641180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.5800000000, query time of that 34.2755926440, 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 18.270000000000437
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0244522710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1547.69 < 1551.25
  -> Decision False in time 0.2600000000, query time of that 0.2536193790, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1668.14 < 1675.92
  -> Decision False in time 1.6300000000, query time of that 1.6029240270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0270029880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1995.61 < 1996.73
  -> Decision False in time 0.1000000000, query time of that 0.0960718450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1866.37 < 1894.53
  -> Decision False in time 0.8200000000, query time of that 0.8005329550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1920.75 < 1996.37
  -> Decision False in time 0.0300000000, query time of that 0.0294382260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1481.9 < 1490.55
  -> Decision False in time 0.0300000000, query time of that 0.0280844170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1584.68 < 1597.47
  -> Decision False in time 0.0500000000, query time of that 0.0321116060, 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 65.95000000000073
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 0.0280100400, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2431823660, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1657.2 < 1777.02
  -> Decision False in time 1.9000000000, query time of that 1.8658203680, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0267068890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1780.77 < 1790.28
  -> Decision False in time 0.2500000000, query time of that 0.2470931070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1447.75 < 1456.19
  -> Decision False in time 0.1500000000, query time of that 0.1377119790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1480.2 < 1565.26
  -> Decision False in time 0.0200000000, query time of that 0.0280769370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1312.9 < 1393.55
  -> Decision False in time 0.1000000000, query time of that 0.0359595940, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1759.63 < 1910.08
  -> Decision False in time 0.3000000000, query time of that 0.1285924260, 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 18.1299999999992
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 0.0106415150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1653.58 < 1655.66
  -> Decision False in time 0.0700000000, query time of that 0.0639968380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1490.45 < 1517.46
  -> Decision False in time 0.0700000000, query time of that 0.0702776830, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1661.32 < 1688.21
  -> Decision False in time 0.0100000000, query time of that 0.0097416320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1913.71 < 2001.54
  -> Decision False in time 0.0400000000, query time of that 0.0333022510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1412.91 < 1423.42
  -> Decision False in time 0.0200000000, query time of that 0.0259899520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1416.13 < 1416.4
  -> Decision False in time 0.0400000000, query time of that 0.0100579870, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1411.78 < 1567.7
  -> Decision False in time 0.0100000000, query time of that 0.0109093680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1436.66 < 1505.4
  -> Decision False in time 0.0100000000, query time of that 0.0096893940, 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 33.960000000000946
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0126472200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1083.24 < 1132.23
  -> Decision False in time 0.0100000000, query time of that 0.0118704050, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2068.19 < 2101.98
  -> Decision False in time 0.0800000000, query time of that 0.0834577250, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1025.37 < 1054.31
  -> Decision False in time 0.0200000000, query time of that 0.0115722370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1506.86 < 1528.1
  -> Decision False in time 0.0100000000, query time of that 0.0113226260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1569.75 < 1601.74
  -> Decision False in time 0.0200000000, query time of that 0.0187375890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1409.83 < 1458.98
  -> Decision False in time 0.0100000000, query time of that 0.0115320030, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1464.27 < 1516.5
  -> Decision False in time 0.0100000000, query time of that 0.0116983050, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1279.03 < 1315.39
  -> Decision False in time 0.0200000000, query time of that 0.0133346380, 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 33.82999999999993
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0121633730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1620.29 < 1726.25
  -> Decision False in time 0.0500000000, query time of that 0.0422721350, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1742.98 < 1935.86
  -> Decision False in time 0.0800000000, query time of that 0.0808194090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0117990140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1769.13 < 1796.01
  -> Decision False in time 0.0300000000, query time of that 0.0264029070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1199.56 < 1444.22
  -> Decision False in time 0.0100000000, query time of that 0.0116756040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1930.76 < 2013.96
  -> Decision False in time 0.0200000000, query time of that 0.0123359970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1483.32 < 1535.96
  -> Decision False in time 0.0100000000, query time of that 0.0133796480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1656.5 < 1784.67
  -> Decision False in time 0.0200000000, query time of that 0.0126334080, 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 33.82999999999993
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 0.0463672170, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4428802410, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4200000000, query time of that 4.3721317290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0457151600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4595768680, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1977.89 < 1981.11
  -> Decision False in time 0.4700000000, query time of that 0.4688499150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0507015320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1498.94 < 1535.96
  -> Decision False in time 0.9700000000, query time of that 0.6088959280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1448.84 < 1449.12
  -> Decision False in time 1.5200000000, query time of that 1.0191013980, 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 33.909999999999854
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 0.0227408380, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2027206480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1735.92 < 1740.09
  -> Decision False in time 1.4700000000, query time of that 1.4409207990, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1765.74 < 1781.64
  -> Decision False in time 0.0200000000, query time of that 0.0218057200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1145.24 < 1234.91
  -> Decision False in time 0.0700000000, query time of that 0.0630532090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1447.75 < 1456.19
  -> Decision False in time 0.0500000000, query time of that 0.0545336890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1524.07 < 1541.97
  -> Decision False in time 0.0300000000, query time of that 0.0217038080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1838.62 < 1891.91
  -> Decision False in time 0.1100000000, query time of that 0.0487597400, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1818.92 < 1842.56
  -> Decision False in time 0.0200000000, query time of that 0.0252228930, 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 65.19000000000051
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 0.0166419770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1566.38 < 1569.34
  -> Decision False in time 0.0900000000, query time of that 0.0876497860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1664.69 < 1667.56
  -> Decision False in time 0.1700000000, query time of that 0.1590628150, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2078.54 < 2112.26
  -> Decision False in time 0.0100000000, query time of that 0.0156329070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1594.23 < 1598.7
  -> Decision False in time 0.0400000000, query time of that 0.0387607480, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1159.49 < 1196.57
  -> Decision False in time 0.0400000000, query time of that 0.0370177620, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2055.64 < 2176.41
  -> Decision False in time 0.0200000000, query time of that 0.0157808240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1327.57 < 1358.5
  -> Decision False in time 0.0200000000, query time of that 0.0167766860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1619.91 < 1678
  -> Decision False in time 0.0100000000, query time of that 0.0160987730, 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 65.21000000000095
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 0.0507187470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2116.65 < 2155.28
  -> Decision False in time 0.4800000000, query time of that 0.4698858760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.8500000000, query time of that 4.8035545760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0510317730, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2066.41 < 2068.33
  -> Decision False in time 0.1600000000, query time of that 0.1606070750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1805.42 < 1808.93
  -> Decision False in time 0.5800000000, query time of that 0.5669187010, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0580915080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1287.25 < 1302.64
  -> Decision False in time 0.2400000000, query time of that 0.1881016290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1904.69 < 1939.76
  -> Decision False in time 0.5100000000, query time of that 0.3659551260, 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 18.039999999999054
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1124701640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0804322640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.8600000000, query time of that 10.7972054080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1199285740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1300000000, query time of that 1.1208484870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.2000000000, query time of that 11.1219398140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1214825990, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4900000000, query time of that 1.2826160770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 13.6400000000, query time of that 12.6036124390, 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 65.28999999999905
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2072905000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.9800000000, query time of that 1.9737735770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.5300000000, query time of that 19.4548369290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1905196340, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.9800000000, query time of that 1.9675501070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.7400000000, query time of that 19.6402998030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2187635860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2100000000, query time of that 2.0841636720, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1796.41 < 1807.22
  -> Decision False in time 6.8900000000, query time of that 6.8562011890, 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 18.090000000000146
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2346569910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3200000000, query time of that 2.3063911850, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 22.6600000000, query time of that 22.5869347390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2368028700, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.3000000000, query time of that 2.2790314230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 22.8200000000, query time of that 22.7338929660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.2536054870, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.5300000000, query time of that 2.3657259060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.3900000000, query time of that 23.7708446820, 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 33.840000000000146
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2013923180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0200000000, query time of that 2.0128749750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.4800000000, query time of that 20.4099943280, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2111360900, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0600000000, query time of that 2.0443586250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.6800000000, query time of that 20.5541928460, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3100000000, query time of that 0.2280590190, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3700000000, query time of that 2.1494275530, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 22.0800000000, query time of that 21.5122721840, with c1=5.0000000000, c2=0.1000000000
