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, 4000]), 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, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 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', 100, 100]), 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, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 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', 400, 40000]), 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, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), 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', 400, 400000])]
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 45.1
Index size:  395972.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0317038200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2675740450, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.7700000000, query time of that 2.7206004890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0311371050, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3051351990, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1725.05 < 1767.4
  -> Decision False in time 0.4500000000, query time of that 0.4365234000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0315295340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1331.24 < 1480.38
  -> Decision False in time 0.0400000000, query time of that 0.0329166750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1330.95 < 1386.12
  -> Decision False in time 0.1200000000, query time of that 0.0638774700, 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 65.06
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 0.0523407510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4974593860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.8700000000, query time of that 4.8159651500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0516879340, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5138435140, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1672.58 < 1724.16
  -> Decision False in time 1.0900000000, query time of that 1.0697697230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0620089010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2116.65 < 2155.28
  -> Decision False in time 0.1700000000, query time of that 0.1287249610, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1578.71 < 1678.18
  -> Decision False in time 1.8000000000, query time of that 1.3179016640, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 1000])
Got a train set of size (60000 * 784)
Built index in 17.95999999999998
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 0.0149553180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1328673490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1868.76 < 1988.27
  -> Decision False in time 0.3200000000, query time of that 0.3142313810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0147710740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1744.92 < 1888.43
  -> Decision False in time 0.0500000000, query time of that 0.0483436740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1491.04 < 1548.88
  -> Decision False in time 0.0400000000, query time of that 0.0325297240, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2113.83 < 2116.64
  -> Decision False in time 0.0100000000, query time of that 0.0141592010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1693.86 < 1892.53
  -> Decision False in time 0.0200000000, query time of that 0.0151980420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1430.54 < 1556.72
  -> Decision False in time 0.0100000000, query time of that 0.0153056060, 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 65.10000000000002
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 0.0156430340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1480.81 < 1501.27
  -> Decision False in time 0.0700000000, query time of that 0.0673243350, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1617.04 < 1734.28
  -> Decision False in time 0.1200000000, query time of that 0.1156308020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1513.52 < 1783.29
  -> Decision False in time 0.0200000000, query time of that 0.0161226070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1504.85 < 1514.66
  -> Decision False in time 0.0300000000, query time of that 0.0343735210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1601.33 < 1612.11
  -> Decision False in time 0.0300000000, query time of that 0.0234668430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1527.74 < 1589.79
  -> Decision False in time 0.0100000000, query time of that 0.0160052200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1297.31 < 1450.5
  -> Decision False in time 0.0200000000, query time of that 0.0162686480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1288.59 < 1307.6
  -> Decision False in time 0.0200000000, query time of that 0.0177129050, 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 33.67999999999995
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 0.0467913960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4463781730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3800000000, query time of that 4.3254557990, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0491916170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4713654050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1635.06 < 1644.41
  -> Decision False in time 0.3100000000, query time of that 0.3047348010, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0551972640, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2060.24 < 2136.06
  -> Decision False in time 0.3800000000, query time of that 0.2600176490, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1633.15 < 1757.13
  -> Decision False in time 1.2200000000, query time of that 0.8235365220, 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 18.050000000000068
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7841176690, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.6600000000, query time of that 7.6515730100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 75.4700000000, query time of that 75.3772339700, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7631207780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.5700000000, query time of that 7.5494289420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 76.5800000000, query time of that 76.4846616620, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8800000000, query time of that 0.7932373450, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.7400000000, query time of that 7.6609740490, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.3000000000, query time of that 76.9779842950, 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 65.23999999999978
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 0.0727475360, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1437.88 < 1455.3
  -> Decision False in time 0.2200000000, query time of that 0.2152440880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.9900000000, query time of that 6.9321886970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0752020800, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7500000000, query time of that 0.7323006700, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2058.01 < 2095.66
  -> Decision False in time 7.1800000000, query time of that 7.1214407890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0786815010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0700000000, query time of that 0.9066593580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1691.61 < 1700.87
  -> Decision False in time 1.2800000000, query time of that 1.2224680190, 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 65.4699999999998
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1924178570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.9900000000, query time of that 1.9811698830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.7100000000, query time of that 19.6369987040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1959852730, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.9700000000, query time of that 1.9416121920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.7200000000, query time of that 19.6092699840, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2073268460, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2300000000, query time of that 2.1110978460, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.0600000000, query time of that 20.6608174130, 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 18.090000000000146
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 0.0204459960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1865969540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1869.12 < 1888.27
  -> Decision False in time 0.2700000000, query time of that 0.2595999010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1549.66 < 1576.22
  -> Decision False in time 0.0200000000, query time of that 0.0205200210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1449.67 < 1481.6
  -> Decision False in time 0.1000000000, query time of that 0.0965433320, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1237.35 < 1240.25
  -> Decision False in time 0.1600000000, query time of that 0.1510290370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0218788640, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2024.77 < 2053.49
  -> Decision False in time 0.0200000000, query time of that 0.0208131740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1787.83 < 1790.93
  -> Decision False in time 0.0200000000, query time of that 0.0209276450, 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 33.80999999999949
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 0.0120122610, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1083249400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1968.51 < 2020.97
  -> Decision False in time 0.1900000000, query time of that 0.1772110540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1648.69 < 1650.27
  -> Decision False in time 0.0100000000, query time of that 0.0116593010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1394.69 < 1424.6
  -> Decision False in time 0.0100000000, query time of that 0.0116014400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1481.63 < 1489.42
  -> Decision False in time 0.0200000000, query time of that 0.0232356520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1837.27 < 1860.29
  -> Decision False in time 0.0200000000, query time of that 0.0110189630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1394.44 < 1425.6
  -> Decision False in time 0.0100000000, query time of that 0.0111277300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1944.46 < 1998.36
  -> Decision False in time 0.0100000000, query time of that 0.0136763560, 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 65.07000000000062
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3351001480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4000000000, query time of that 3.3986047750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.7200000000, query time of that 33.6393750950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3443469210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.3000000000, query time of that 3.2749790250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 33.5100000000, query time of that 33.4222972110, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4200000000, query time of that 0.3465265610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.4600000000, query time of that 3.3818398300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.5000000000, query time of that 34.1909969160, 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 18.039999999999964
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0108317260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1669.01 < 1808.65
  -> Decision False in time 0.0400000000, query time of that 0.0342226030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1500.07 < 1656.68
  -> Decision False in time 0.0600000000, query time of that 0.0514726570, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1515.56 < 1517.63
  -> Decision False in time 0.0100000000, query time of that 0.0096564360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2029.21 < 2079.37
  -> Decision False in time 0.0100000000, query time of that 0.0145249750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1791.02 < 1866.38
  -> Decision False in time 0.0200000000, query time of that 0.0104382410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1553.51 < 1662.79
  -> Decision False in time 0.0100000000, query time of that 0.0108332960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1247.26 < 1429.07
  -> Decision False in time 0.0200000000, query time of that 0.0096074580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1508.73 < 1582.78
  -> Decision False in time 0.0100000000, query time of that 0.0096840830, 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 33.659999999999854
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1904596490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0600000000, query time of that 2.0504999150, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.3400000000, query time of that 20.2714663870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2075280960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0800000000, query time of that 2.0588069660, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.6100000000, query time of that 20.5176000540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2190763690, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2400000000, query time of that 2.1206427180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.6700000000, query time of that 21.2490297590, 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 65.03999999999996
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 0.0165366710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1992.1 < 2037.51
  -> Decision False in time 0.0400000000, query time of that 0.0433027160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1598.52 < 1632.58
  -> Decision False in time 0.2000000000, query time of that 0.1889125110, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1372.97 < 1379.34
  -> Decision False in time 0.0100000000, query time of that 0.0170995460, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1836.42 < 1904.16
  -> Decision False in time 0.0600000000, query time of that 0.0559044160, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1352.49 < 1394.21
  -> Decision False in time 0.0500000000, query time of that 0.0431935100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1644.67 < 1822.57
  -> Decision False in time 0.0100000000, query time of that 0.0164346040, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1318.05 < 1382.94
  -> Decision False in time 0.0200000000, query time of that 0.0168632690, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2072.43 < 2094.19
  -> Decision False in time 0.0300000000, query time of that 0.0182645870, 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 17.979999999999563
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2144060030, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3200000000, query time of that 2.3127342800, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 22.9100000000, query time of that 22.8316028260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2383601760, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.2800000000, query time of that 2.2633661170, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 22.9000000000, query time of that 22.8207514050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3100000000, query time of that 0.2358619960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.5500000000, query time of that 2.3653120920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.0700000000, query time of that 23.7591653600, 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 34.0
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0687492590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6869869080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7600000000, query time of that 6.6979925470, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0689912030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6918205130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1639.01 < 1701.05
  -> Decision False in time 0.5400000000, query time of that 0.5331268250, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0750046210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1994.27 < 2012.7
  -> Decision False in time 0.0900000000, query time of that 0.0851597740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1790.79 < 1802.2
  -> Decision False in time 1.5300000000, query time of that 1.3819730090, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 1000])
Got a train set of size (60000 * 784)
Built index in 33.960000000000946
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0175835230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1647.11 < 1656.96
  -> Decision False in time 0.1100000000, query time of that 0.1067443060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1518.49 < 1519.83
  -> Decision False in time 0.5300000000, query time of that 0.5134274540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1418.96 < 1458.94
  -> Decision False in time 0.0200000000, query time of that 0.0167714860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1932.11 < 2163.26
  -> Decision False in time 0.0600000000, query time of that 0.0600190430, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1707.32 < 1708.84
  -> Decision False in time 0.1600000000, query time of that 0.1595223850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1679.31 < 1747.12
  -> Decision False in time 0.0200000000, query time of that 0.0174832870, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1733.98 < 1830.68
  -> Decision False in time 0.0200000000, query time of that 0.0162379770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1566.21 < 1576.03
  -> Decision False in time 0.0300000000, query time of that 0.0198591920, 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 18.1299999999992
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 0.0468123310, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4366080730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.2900000000, query time of that 4.2356279090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0492075750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1279.26 < 1294
  -> Decision False in time 0.2200000000, query time of that 0.2148253740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1581.84 < 1583.7
  -> Decision False in time 3.1600000000, query time of that 3.1245462960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1877.52 < 1995.59
  -> Decision False in time 0.1200000000, query time of that 0.0527665890, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1756.8 < 1770.92
  -> Decision False in time 0.1400000000, query time of that 0.1063594600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1509.53 < 1725.48
  -> Decision False in time 0.4400000000, query time of that 0.2882522870, 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 18.159999999999854
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 0.0099885270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1496.49 < 1553.05
  -> Decision False in time 0.0600000000, query time of that 0.0584949830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1728.83 < 1752.15
  -> Decision False in time 0.1300000000, query time of that 0.1234924710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1144.78 < 1332.43
  -> Decision False in time 0.0100000000, query time of that 0.0099099620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1148.34 < 1156.81
  -> Decision False in time 0.0100000000, query time of that 0.0152627190, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1481.2 < 1500.04
  -> Decision False in time 0.0100000000, query time of that 0.0097529040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1726.07 < 1729.61
  -> Decision False in time 0.0200000000, query time of that 0.0096125160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1797.12 < 1825.76
  -> Decision False in time 0.0100000000, query time of that 0.0107742800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1633.46 < 1710.3
  -> Decision False in time 0.0100000000, query time of that 0.0102575560, 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 18.219999999999345
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 0.4283314260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.2600000000, query time of that 4.2534128100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 41.8700000000, query time of that 41.7733415320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4411149210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.1900000000, query time of that 4.1794518250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.0400000000, query time of that 41.9318149040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4271744550, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.3900000000, query time of that 4.3096456670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.4500000000, query time of that 43.1956589790, 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 18.019999999998618
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0264867390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2587831000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1805.96 < 1807.41
  -> Decision False in time 1.6900000000, query time of that 1.6641063440, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0283408330, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1557.71 < 1576.25
  -> Decision False in time 0.1300000000, query time of that 0.1317203620, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1701.31 < 1727.22
  -> Decision False in time 0.2200000000, query time of that 0.2094642300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1503.72 < 1525.77
  -> Decision False in time 0.0300000000, query time of that 0.0269485760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1139.86 < 1289.38
  -> Decision False in time 0.1000000000, query time of that 0.0532791900, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1530.54 < 1570.32
  -> Decision False in time 0.5300000000, query time of that 0.2239935200, 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 33.659999999999854
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0202147250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2048346930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1712.75 < 1815.85
  -> Decision False in time 1.0500000000, query time of that 1.0290531920, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0219313260, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1759.82 < 1797.73
  -> Decision False in time 0.0500000000, query time of that 0.0462195040, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1602.91 < 1633.96
  -> Decision False in time 0.0500000000, query time of that 0.0481165950, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0234775580, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1710.17 < 1850.77
  -> Decision False in time 0.0600000000, query time of that 0.0256590840, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1359.63 < 1375.27
  -> Decision False in time 0.0700000000, query time of that 0.0252169080, 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 18.1200000000008
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 0.0104297130, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1327.18 < 1404.67
  -> Decision False in time 0.0300000000, query time of that 0.0219077710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1652.24 < 1655.95
  -> Decision False in time 0.0400000000, query time of that 0.0422374870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0102532480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1764.72 < 1819.47
  -> Decision False in time 0.0100000000, query time of that 0.0135577330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1567.43 < 1642.26
  -> Decision False in time 0.0100000000, query time of that 0.0098467640, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1418.5 < 1637.12
  -> Decision False in time 0.0100000000, query time of that 0.0106541170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1617.3 < 1675.65
  -> Decision False in time 0.0200000000, query time of that 0.0103961930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1452.83 < 1475.46
  -> Decision False in time 0.0100000000, query time of that 0.0097379960, 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 65.52000000000044
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 0.0215473020, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1532.47 < 1541.15
  -> Decision False in time 0.1500000000, query time of that 0.1392778050, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1595.43 < 1668.98
  -> Decision False in time 0.3600000000, query time of that 0.3586468370, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1548.54 < 1550.15
  -> Decision False in time 0.0200000000, query time of that 0.0205983210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1381.14 < 1593.9
  -> Decision False in time 0.0800000000, query time of that 0.0771652250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1525.37 < 1532.9
  -> Decision False in time 0.0200000000, query time of that 0.0203081040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1172.84 < 1198.64
  -> Decision False in time 0.0500000000, query time of that 0.0245364430, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
950.895 < 996.173
  -> Decision False in time 0.0300000000, query time of that 0.0265856350, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1284.23 < 1456.91
  -> Decision False in time 0.0300000000, query time of that 0.0217473050, 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 33.8799999999992
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Reject!
1529.9 < 1544.4
  -> Decision False in time 0.0100000000, query time of that 0.0122425010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1275.6 < 1309.1
  -> Decision False in time 0.0800000000, query time of that 0.0701428710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2140.29 < 2140.88
  -> Decision False in time 0.2500000000, query time of that 0.2423948500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1509.35 < 1547.2
  -> Decision False in time 0.0100000000, query time of that 0.0106609640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1679.35 < 1702.56
  -> Decision False in time 0.0200000000, query time of that 0.0199349790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1272.87 < 1314.3
  -> Decision False in time 0.0100000000, query time of that 0.0124307030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1127.98 < 1175.01
  -> Decision False in time 0.0300000000, query time of that 0.0136952410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1699.3 < 1713.82
  -> Decision False in time 0.0100000000, query time of that 0.0128891310, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1548.14 < 1559.75
  -> Decision False in time 0.0200000000, query time of that 0.0123566080, 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 18.13000000000102
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0696549090, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6700000000, query time of that 0.6618554480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7400000000, query time of that 6.6845361160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0623292490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.6899226440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.0400000000, query time of that 6.9310697200, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0751754030, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1833.41 < 1881.82
  -> Decision False in time 0.1600000000, query time of that 0.1526068680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1968.51 < 2029.97
  -> Decision False in time 2.1400000000, query time of that 1.9702604300, 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 34.030000000000655
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0121894910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1389.9 < 1401.54
  -> Decision False in time 0.0500000000, query time of that 0.0530904010, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1593.81 < 1699.9
  -> Decision False in time 0.0500000000, query time of that 0.0464499950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1877.69 < 1968.66
  -> Decision False in time 0.0100000000, query time of that 0.0131902360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1207.5 < 1352.6
  -> Decision False in time 0.0300000000, query time of that 0.0232054950, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1968.43 < 2026.15
  -> Decision False in time 0.0100000000, query time of that 0.0126093850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2178.5 < 2202.9
  -> Decision False in time 0.0200000000, query time of that 0.0134380630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1462.76 < 1481.29
  -> Decision False in time 0.0200000000, query time of that 0.0135028500, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1767.48 < 1809.2
  -> Decision False in time 0.0200000000, query time of that 0.0133889100, 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 65.92000000000007
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0333716320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3274861460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.2400000000, query time of that 3.1906320320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0374737170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3614386890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1755.11 < 1780.94
  -> Decision False in time 0.6600000000, query time of that 0.6478324380, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0406181670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1666.36 < 1755.24
  -> Decision False in time 0.1400000000, query time of that 0.0850391370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1940.39 < 1969.82
  -> Decision False in time 0.3700000000, query time of that 0.1971230230, 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 65.20999999999913
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 0.0256947960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2438206780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1428.31 < 1430.6
  -> Decision False in time 0.7800000000, query time of that 0.7655986270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1997.49 < 2004.96
  -> Decision False in time 0.0400000000, query time of that 0.0268723010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1624.53 < 1772.19
  -> Decision False in time 0.1700000000, query time of that 0.1739700050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1700 < 1839.97
  -> Decision False in time 0.0600000000, query time of that 0.0517977670, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0311123980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1323.97 < 1370.7
  -> Decision False in time 0.1300000000, query time of that 0.0650558100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1196.71 < 1233.53
  -> Decision False in time 0.0700000000, query time of that 0.0309189550, 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 65.19000000000051
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1134583480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0700000000, query time of that 1.0667568860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.6200000000, query time of that 10.5552032120, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1149301870, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.0946092890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1691.61 < 1700.87
  -> Decision False in time 9.3900000000, query time of that 9.3335038430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1280989290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4900000000, query time of that 1.2455075810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1676.36 < 1677.71
  -> Decision False in time 0.7300000000, query time of that 0.7286910950, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200000])
Got a train set of size (60000 * 784)
Built index in 33.73000000000138
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3845234500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.6900000000, query time of that 3.6841356880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.5400000000, query time of that 36.4555639480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3702711140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.7200000000, query time of that 3.7014499630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.8500000000, query time of that 36.7551627340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.3837393860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.8500000000, query time of that 3.7404054830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 37.4400000000, query time of that 37.1609867960, 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 18.05999999999949
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1006101270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.1065718830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.8700000000, query time of that 10.8013441350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1036379020, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1000000000, query time of that 1.0778276080, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.1200000000, query time of that 11.0459620790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1298946970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1982.05 < 2069.95
  -> Decision False in time 0.7900000000, query time of that 0.7838783900, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1741.04 < 1879.01
  -> Decision False in time 4.1100000000, query time of that 4.0842875440, 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 33.719999999999345
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6858465120, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.8700000000, query time of that 6.8589845160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 68.0800000000, query time of that 67.9883716600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6840741530, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.8500000000, query time of that 6.8340778200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 68.6200000000, query time of that 68.5176111800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7600000000, query time of that 0.6770415360, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.0300000000, query time of that 6.9061619180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 69.9800000000, query time of that 69.5753058540, 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 65.21999999999935
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 0.0164179480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1404.95 < 1406.19
  -> Decision False in time 0.0400000000, query time of that 0.0445435140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1325.99 < 1490.74
  -> Decision False in time 0.3100000000, query time of that 0.2982901450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1687.71 < 1705.35
  -> Decision False in time 0.0200000000, query time of that 0.0160452660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1182.22 < 1189.1
  -> Decision False in time 0.0400000000, query time of that 0.0319881620, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1240.48 < 1244.73
  -> Decision False in time 0.0400000000, query time of that 0.0416718480, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1555.26 < 1600.72
  -> Decision False in time 0.0200000000, query time of that 0.0171393630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1144.26 < 1264.96
  -> Decision False in time 0.0200000000, query time of that 0.0189659200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1779 < 1824.24
  -> Decision False in time 0.0300000000, query time of that 0.0170860380, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 40000])
Got a train set of size (60000 * 784)
Built index in 33.79000000000087
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 0.1079803590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0600000000, query time of that 1.0460589280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.3800000000, query time of that 10.3207346800, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1166791410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0835279420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 10.6500000000, query time of that 10.5456185430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1125764180, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4500000000, query time of that 1.1920725180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1940.55 < 1977.16
  -> Decision False in time 5.1800000000, query time of that 5.1400188210, 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 65.70000000000073
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6100000000, query time of that 0.6135421450, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.2600000000, query time of that 6.2478711170, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.6600000000, query time of that 61.5664468190, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6178352860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.1300000000, query time of that 6.1211822300, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 61.3800000000, query time of that 61.2700099810, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.6496626730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.3600000000, query time of that 6.2288565820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 62.2500000000, query time of that 62.0699628440, with c1=5.0000000000, c2=0.1000000000
