copying files to /scratch...
starting benchmark...
/scratch/knn/venv/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
running only annoy
order: [Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), 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, 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', 200, 1000]), 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, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), 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, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), 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, 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', 100, 4000]), 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, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), 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, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000])]
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 20.259999999999998
Index size:  304616.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2555245020, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3100000000, query time of that 2.2964116940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 22.9400000000, query time of that 22.8525211910, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2352885370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.3400000000, query time of that 2.3225017510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 23.0300000000, query time of that 22.9097317410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2220262320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.4500000000, query time of that 2.3609823160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.2400000000, query time of that 23.3182637490, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 10000])
Got a train set of size (60000 * 784)
Built index in 34.38999999999987
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0477284490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.4484929030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4700000000, query time of that 4.4225989980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0501576070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.4850150060, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1688.03 < 1689.37
  -> Decision False in time 1.9500000000, query time of that 1.9279761970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0497189480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1772.64 < 1785.61
  -> Decision False in time 0.2700000000, query time of that 0.1830028990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1553.18 < 1573.5
  -> Decision False in time 1.3600000000, query time of that 0.9077827700, 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 34.200000000000045
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0984436950, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0700000000, query time of that 1.0621644960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.4900000000, query time of that 10.4219170020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1020015660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.0500000000, query time of that 1.0364811450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1631.8 < 1643.31
  -> Decision False in time 6.2800000000, query time of that 6.2378583120, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1221406900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.3500000000, query time of that 1.2020029250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1771.06 < 1818.8
  -> Decision False in time 2.1600000000, query time of that 2.1465219240, 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 18.3900000000001
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0229533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0201430650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1554.32 < 1600.3
  -> Decision False in time 0.1500000000, query time of that 0.1390598070, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1105.68 < 1118.01
  -> Decision False in time 0.7100000000, query time of that 0.7004889330, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1519.93 < 1542.49
  -> Decision False in time 0.0200000000, query time of that 0.0205202320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1362.56 < 1434.53
  -> Decision False in time 0.0400000000, query time of that 0.0368380200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1891.62 < 1892.44
  -> Decision False in time 0.0900000000, query time of that 0.0820202120, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0209071800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1267.18 < 1339.19
  -> Decision False in time 0.1200000000, query time of that 0.0467362290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1795.79 < 1800.14
  -> Decision False in time 0.0200000000, query time of that 0.0202543330, 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 34.309999999999945
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0171800110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1515.8 < 1531.2
  -> Decision False in time 0.1000000000, query time of that 0.0962710460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1301.13 < 1344
  -> Decision False in time 0.1400000000, query time of that 0.1318123170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0179528320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1778.68 < 1783.7
  -> Decision False in time 0.0400000000, query time of that 0.0380161650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1322.31 < 1436.9
  -> Decision False in time 0.0200000000, query time of that 0.0230928410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1768.14 < 1829.97
  -> Decision False in time 0.0200000000, query time of that 0.0186714070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1920.32 < 2011.13
  -> Decision False in time 0.0200000000, query time of that 0.0192515710, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1429.78 < 1439
  -> Decision False in time 0.1000000000, query time of that 0.0272708330, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 400])
Got a train set of size (60000 * 784)
Built index in 34.18999999999983
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0132223370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1206.98 < 1235.15
  -> Decision False in time 0.0700000000, query time of that 0.0692543430, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1939.88 < 1951.8
  -> Decision False in time 0.1000000000, query time of that 0.0965383470, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1617.64 < 1889
  -> Decision False in time 0.0100000000, query time of that 0.0121907220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1455.1 < 1612.47
  -> Decision False in time 0.0300000000, query time of that 0.0202927220, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1745.14 < 1809.68
  -> Decision False in time 0.0100000000, query time of that 0.0155157050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1737.5 < 1834.44
  -> Decision False in time 0.0300000000, query time of that 0.0136556690, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1296.26 < 1315.09
  -> Decision False in time 0.0100000000, query time of that 0.0139930030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1361.28 < 1442.44
  -> Decision False in time 0.0200000000, query time of that 0.0137964290, 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 34.149999999999864
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2195196860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.1200000000, query time of that 2.1113563800, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.6500000000, query time of that 20.5587235970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2149035070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0900000000, query time of that 2.0743144260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.7800000000, query time of that 20.6567180960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.2403102780, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3000000000, query time of that 2.1597812600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 22.0700000000, query time of that 21.5256661030, 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 18.340000000000146
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0706324560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6889343630, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7000000000, query time of that 6.6302243740, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0684663280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.6956408170, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1633.84 < 1634.77
  -> Decision False in time 0.8100000000, query time of that 0.8056943030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0731691290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1679.52 < 1696.67
  -> Decision False in time 0.9500000000, query time of that 0.8608730680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1877.97 < 1885.12
  -> Decision False in time 0.4500000000, query time of that 0.3981849450, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 20000])
Got a train set of size (60000 * 784)
Built index in 34.289999999999964
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0739186650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.7018696490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7000000000, query time of that 6.6331998580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0716737500, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6912600770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1848.03 < 1883.97
  -> Decision False in time 0.7800000000, query time of that 0.7762927400, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0841990510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1328.35 < 1369.85
  -> Decision False in time 0.8300000000, query time of that 0.7373130810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1733.99 < 1806.16
  -> Decision False in time 0.8800000000, query time of that 0.7913975930, 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 66.4399999999996
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0151527930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1785.31 < 2029.88
  -> Decision False in time 0.0500000000, query time of that 0.0492194060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1432.95 < 1434.01
  -> Decision False in time 0.0400000000, query time of that 0.0395445240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1366.87 < 1484.09
  -> Decision False in time 0.0200000000, query time of that 0.0180362980, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
867.976 < 938.269
  -> Decision False in time 0.0300000000, query time of that 0.0275472460, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1552.52 < 1672.42
  -> Decision False in time 0.0100000000, query time of that 0.0154925530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1248.92 < 1270.24
  -> Decision False in time 0.0200000000, query time of that 0.0161836760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1998.6 < 2031.48
  -> Decision False in time 0.0200000000, query time of that 0.0171403330, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1551.69 < 1564.23
  -> Decision False in time 0.0200000000, query time of that 0.0165162060, 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 66.38000000000011
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Reject!
1743.85 < 1847.41
  -> Decision False in time 0.0200000000, query time of that 0.0162859180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1340.91 < 1371.86
  -> Decision False in time 0.0900000000, query time of that 0.0889081570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1831.35 < 1938.35
  -> Decision False in time 0.1200000000, query time of that 0.1194725630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0164035070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1736.77 < 1856.06
  -> Decision False in time 0.0300000000, query time of that 0.0296648760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1408.52 < 1434.07
  -> Decision False in time 0.0200000000, query time of that 0.0199591430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1217.97 < 1244.31
  -> Decision False in time 0.0200000000, query time of that 0.0171767170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1279.25 < 1473.92
  -> Decision False in time 0.0400000000, query time of that 0.0166194570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1397.44 < 1408.18
  -> Decision False in time 0.0100000000, query time of that 0.0160254320, 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 66.34999999999991
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6700000000, query time of that 0.6691670800, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.3000000000, query time of that 6.2826624880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.9700000000, query time of that 61.8649695750, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6320821560, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.2800000000, query time of that 6.2635842540, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 61.9100000000, query time of that 61.7806425260, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6368433950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.3400000000, query time of that 6.2545471860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 62.6900000000, query time of that 62.4925755850, 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 65.03999999999996
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0165134900, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1604.09 < 1634.07
  -> Decision False in time 0.1500000000, query time of that 0.1464048070, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2055.49 < 2101.08
  -> Decision False in time 0.0500000000, query time of that 0.0482852170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0178707180, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1851.89 < 1861.18
  -> Decision False in time 0.0200000000, query time of that 0.0201976870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1975.37 < 1979.12
  -> Decision False in time 0.0200000000, query time of that 0.0181819890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1559.44 < 1567.07
  -> Decision False in time 0.0200000000, query time of that 0.0176765820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1956.78 < 1994.38
  -> Decision False in time 0.0200000000, query time of that 0.0162677200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1371.26 < 1403.67
  -> Decision False in time 0.0100000000, query time of that 0.0148149630, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 400000])
Got a train set of size (60000 * 784)
Built index in 33.779999999999745
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.7063513600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.9600000000, query time of that 6.9543455560, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 69.0500000000, query time of that 68.9358851760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6864420500, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.9100000000, query time of that 6.8869829020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 69.0000000000, query time of that 68.8859907540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7059467300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.9500000000, query time of that 6.8559579630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 69.8400000000, query time of that 69.4818044890, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 100])
Got a train set of size (60000 * 784)
Built index in 33.710000000000946
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0126824150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1741.15 < 1899.79
  -> Decision False in time 0.0600000000, query time of that 0.0541947650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1601.36 < 1687.09
  -> Decision False in time 0.0600000000, query time of that 0.0607774680, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1319.26 < 1335.86
  -> Decision False in time 0.0200000000, query time of that 0.0125820400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1114.01 < 1231.97
  -> Decision False in time 0.0100000000, query time of that 0.0135946270, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1583.63 < 1593.69
  -> Decision False in time 0.0200000000, query time of that 0.0114216910, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1588.47 < 1610.73
  -> Decision False in time 0.0400000000, query time of that 0.0123966280, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1376.41 < 1443.02
  -> Decision False in time 0.0200000000, query time of that 0.0147632140, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1183.32 < 1187.88
  -> Decision False in time 0.0100000000, query time of that 0.0126141890, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 20000])
Got a train set of size (60000 * 784)
Built index in 65.05999999999949
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0781878190, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7155703810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.0900000000, query time of that 7.0224520940, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0814315200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7536137150, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.5000000000, query time of that 7.3993069820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0833029340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1500000000, query time of that 0.9315309810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2165.71 < 2204.44
  -> Decision False in time 0.0900000000, query time of that 0.0828198520, 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 34.04000000000087
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0286209080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2774500070, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1837.62 < 1840.74
  -> Decision False in time 0.4900000000, query time of that 0.4773110600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0302618550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3072309560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2113.05 < 2220.79
  -> Decision False in time 0.1500000000, query time of that 0.1471992990, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1466.05 < 1466.88
  -> Decision False in time 0.0400000000, query time of that 0.0307284320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1445.6 < 1461
  -> Decision False in time 0.1500000000, query time of that 0.0726904570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1716.42 < 1736.11
  -> Decision False in time 0.1700000000, query time of that 0.0736294880, 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 66.1200000000008
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0172116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0257126470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2503031230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1437.13 < 1457.18
  -> Decision False in time 0.4700000000, query time of that 0.4627656970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0274578740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1545.89 < 1559.97
  -> Decision False in time 0.1100000000, query time of that 0.1105545460, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1484 < 1494.49
  -> Decision False in time 0.1200000000, query time of that 0.1180183080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1220.95 < 1240.51
  -> Decision False in time 0.0700000000, query time of that 0.0313727950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1710.37 < 1724.78
  -> Decision False in time 0.1200000000, query time of that 0.0636749630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1782.64 < 1818.67
  -> Decision False in time 0.0400000000, query time of that 0.0317512550, 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 18.200000000000728
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Reject!
1772.78 < 1991.8
  -> Decision False in time 0.0100000000, query time of that 0.0103610580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1633.21 < 1676.65
  -> Decision False in time 0.0900000000, query time of that 0.0883924990, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1665.54 < 1912.02
  -> Decision False in time 0.0700000000, query time of that 0.0688714420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1719.67 < 1761.7
  -> Decision False in time 0.0200000000, query time of that 0.0097564410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1550.6 < 1669.97
  -> Decision False in time 0.0200000000, query time of that 0.0236580960, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1735.11 < 1749.31
  -> Decision False in time 0.0300000000, query time of that 0.0291597160, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1714.66 < 1716.76
  -> Decision False in time 0.0200000000, query time of that 0.0099294400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1077.38 < 1126.6
  -> Decision False in time 0.0200000000, query time of that 0.0109963530, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1468.82 < 1495.49
  -> Decision False in time 0.0100000000, query time of that 0.0115267830, 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 18.219999999999345
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0284970000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2605469670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.6300000000, query time of that 2.5796204150, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0299974280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1625.98 < 1648.44
  -> Decision False in time 0.2600000000, query time of that 0.2611192770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1683.75 < 1686.14
  -> Decision False in time 0.4800000000, query time of that 0.4692877690, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0296610940, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1579.66 < 1621.68
  -> Decision False in time 0.0400000000, query time of that 0.0303595570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
704.065 < 704.37
  -> Decision False in time 0.0500000000, query time of that 0.0319687250, 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 18.19000000000051
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0146437150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1338033640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1543.92 < 1589.53
  -> Decision False in time 0.6000000000, query time of that 0.5830248830, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1644.95 < 1695.45
  -> Decision False in time 0.0200000000, query time of that 0.0145413250, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1893.57 < 1964.34
  -> Decision False in time 0.0500000000, query time of that 0.0513336980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1348.01 < 1585.27
  -> Decision False in time 0.0400000000, query time of that 0.0342225760, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1470.86 < 1564.22
  -> Decision False in time 0.0100000000, query time of that 0.0153091610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1641.35 < 1777.25
  -> Decision False in time 0.0200000000, query time of that 0.0150443520, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1326.22 < 1352.49
  -> Decision False in time 0.0600000000, query time of that 0.0164669840, 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 65.80000000000109
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2090811660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0200000000, query time of that 2.0124703200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.8600000000, query time of that 19.7694113660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2043651780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0100000000, query time of that 1.9990872450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.0700000000, query time of that 19.9438618960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2290563060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2200000000, query time of that 2.1076400850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.5700000000, query time of that 20.8438037960, 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 18.160000000001673
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4484927460, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.3200000000, query time of that 4.3062073190, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.7400000000, query time of that 42.6390777780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4403118040, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.2800000000, query time of that 4.2674744210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.6100000000, query time of that 42.4919467580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4320821520, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.5000000000, query time of that 4.3555971980, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.6500000000, query time of that 43.4065936740, 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 18.280000000000655
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1238089190, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1000000000, query time of that 1.0949233420, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 11.0700000000, query time of that 10.9977235360, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1122685150, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1200000000, query time of that 1.0974576750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1602.91 < 1633.96
  -> Decision False in time 1.9400000000, query time of that 1.9293809520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.1378256070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1767.79 < 1840.57
  -> Decision False in time 0.8700000000, query time of that 0.8611111560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1763.35 < 1804.82
  -> Decision False in time 1.3400000000, query time of that 1.3275151530, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200])
Got a train set of size (60000 * 784)
Built index in 34.23999999999978
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0114874680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1100840720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1353.78 < 1411.41
  -> Decision False in time 0.0800000000, query time of that 0.0727075290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1593.46 < 1636.82
  -> Decision False in time 0.0100000000, query time of that 0.0120081040, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1741.49 < 1808.41
  -> Decision False in time 0.0300000000, query time of that 0.0249861970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1714.76 < 1794.93
  -> Decision False in time 0.0200000000, query time of that 0.0220058550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1408.49 < 1415.39
  -> Decision False in time 0.0100000000, query time of that 0.0103155270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1412.91 < 1531.95
  -> Decision False in time 0.0100000000, query time of that 0.0124246340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1328.43 < 1378.43
  -> Decision False in time 0.0200000000, query time of that 0.0126534470, 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 34.100000000000364
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3760096110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.6900000000, query time of that 3.6821352700, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.7900000000, query time of that 36.6923634020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3638464570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.6900000000, query time of that 3.6685608630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.9600000000, query time of that 36.8549921200, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4700000000, query time of that 0.3925566380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.9100000000, query time of that 3.7759709170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 38.2500000000, query time of that 37.5041665790, 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 18.01000000000022
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0103561480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1477.19 < 1560.61
  -> Decision False in time 0.0400000000, query time of that 0.0445514220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1503.74 < 1555.35
  -> Decision False in time 0.0400000000, query time of that 0.0292272630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2011.63 < 2094.59
  -> Decision False in time 0.0100000000, query time of that 0.0089110840, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1443.09 < 1454.23
  -> Decision False in time 0.0100000000, query time of that 0.0100424200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1791.35 < 1792.97
  -> Decision False in time 0.0100000000, query time of that 0.0102759090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1840.24 < 1873.93
  -> Decision False in time 0.0100000000, query time of that 0.0100364200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1574.78 < 1581.91
  -> Decision False in time 0.0100000000, query time of that 0.0099285640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1366.36 < 1476.62
  -> Decision False in time 0.0100000000, query time of that 0.0094163290, 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 64.90999999999985
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0345381820, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3262126810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1790.79 < 1808.29
  -> Decision False in time 0.3700000000, query time of that 0.3677715170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0346506000, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3637834550, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1572.84 < 1601.68
  -> Decision False in time 0.2600000000, query time of that 0.2494032750, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0433738120, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1888.5 < 2003.67
  -> Decision False in time 0.2200000000, query time of that 0.1359999370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1428.34 < 1442.28
  -> Decision False in time 0.1400000000, query time of that 0.0821912020, 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 64.8799999999992
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3451240200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4700000000, query time of that 3.4580549310, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.9400000000, query time of that 33.8529177670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3142120620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.3600000000, query time of that 3.3454104880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 33.9800000000, query time of that 33.8831135680, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.3423379030, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.5900000000, query time of that 3.4550075740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.9100000000, query time of that 34.2948967860, 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 18.049999999999272
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7743538870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.6500000000, query time of that 7.6344594150, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 76.6700000000, query time of that 76.5690458600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7811230510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.6800000000, query time of that 7.6631644740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 76.0000000000, query time of that 75.8818929860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8600000000, query time of that 0.7792884090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.7900000000, query time of that 7.7117702720, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.3800000000, query time of that 77.0557222970, 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 18.18000000000029
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0099445270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1395.98 < 1541.84
  -> Decision False in time 0.0800000000, query time of that 0.0688106330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1177.86 < 1328.27
  -> Decision False in time 0.0500000000, query time of that 0.0503759240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0107927130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1498.29 < 1514.41
  -> Decision False in time 0.0100000000, query time of that 0.0101923590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1610.49 < 1616.91
  -> Decision False in time 0.0300000000, query time of that 0.0219407500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1524.38 < 1606.48
  -> Decision False in time 0.0100000000, query time of that 0.0091098480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1467.23 < 1477.97
  -> Decision False in time 0.0200000000, query time of that 0.0106316240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1411.07 < 1431.76
  -> Decision False in time 0.0100000000, query time of that 0.0102950600, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 1000])
Got a train set of size (60000 * 784)
Built index in 64.97999999999956
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0200411750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1931458010, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1113.79 < 1315.33
  -> Decision False in time 0.3400000000, query time of that 0.3285808860, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0226338930, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1581.77 < 1599.73
  -> Decision False in time 0.1900000000, query time of that 0.1870492730, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1209.43 < 1210.3
  -> Decision False in time 0.1800000000, query time of that 0.1710436610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1341.51 < 1377.06
  -> Decision False in time 0.0400000000, query time of that 0.0238198140, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1517.14 < 1523.38
  -> Decision False in time 0.0500000000, query time of that 0.0266286390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1633.48 < 1718.82
  -> Decision False in time 0.0300000000, query time of that 0.0246206840, 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 18.090000000000146
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0028783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0463777410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4404214340, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3700000000, query time of that 4.3028856430, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0430803610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4800000000, query time of that 0.4615422050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1611.32 < 1650.52
  -> Decision False in time 1.0800000000, query time of that 1.0657837030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1720.82 < 1755.99
  -> Decision False in time 0.0600000000, query time of that 0.0480885410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1871.12 < 1912.12
  -> Decision False in time 0.1800000000, query time of that 0.1216300630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1473.5 < 1501.17
  -> Decision False in time 0.1200000000, query time of that 0.0803249200, 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 65.03000000000247
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1105177840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0800000000, query time of that 1.0730991720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1380.84 < 1384.45
  -> Decision False in time 4.6000000000, query time of that 4.5641184700, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1039950370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1300000000, query time of that 1.1140545420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.0000000000, query time of that 10.9095576500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1244454160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4200000000, query time of that 1.2492712260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1630.3 < 1638.06
  -> Decision False in time 12.4800000000, query time of that 12.2706325640, 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 65.04999999999927
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0481105280, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4877531600, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1735.88 < 1754.18
  -> Decision False in time 4.6100000000, query time of that 4.5548169420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1502.05 < 1523.99
  -> Decision False in time 0.0600000000, query time of that 0.0558042160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5211161740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1618.31 < 1633.92
  -> Decision False in time 2.7800000000, query time of that 2.7491300530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0590344650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1404.58 < 1501.28
  -> Decision False in time 0.0700000000, query time of that 0.0600791510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1710.73 < 1779.03
  -> Decision False in time 0.1900000000, query time of that 0.1466428120, 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 33.640000000003056
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0215755950, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2041080870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1467.94 < 1487.51
  -> Decision False in time 0.1200000000, query time of that 0.1190699590, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0226367110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1796.48 < 1850.15
  -> Decision False in time 0.0900000000, query time of that 0.0849436490, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1670.38 < 1708.31
  -> Decision False in time 0.0200000000, query time of that 0.0234577040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0252309910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1475.38 < 1550.43
  -> Decision False in time 0.0200000000, query time of that 0.0243534440, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1519.7 < 1586.86
  -> Decision False in time 0.3000000000, query time of that 0.1111023320, with c1=5.0000000000, c2=0.1000000000
