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, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 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', 200, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 10000]), 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', 400, 4000]), 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, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]), 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', 400, 100]), 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', 100, 2000]), 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, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), 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, 100]), 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, 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', 400, 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', 100, 200]), 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, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 2000])
Got a train set of size (60000 * 784)
Built index in 33.339999999999996
Index size:  396460.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0237914960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2090706770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.0500000000, query time of that 2.0014222710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0233932150, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1011.12 < 1028.4
  -> Decision False in time 0.0500000000, query time of that 0.0548365820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
669.804 < 846.814
  -> Decision False in time 0.0400000000, query time of that 0.0365302030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
874.051 < 938.252
  -> Decision False in time 0.0400000000, query time of that 0.0244106780, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1342.8 < 1488.47
  -> Decision False in time 0.0500000000, query time of that 0.0254817270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1083.95 < 1276.76
  -> Decision False in time 0.0500000000, query time of that 0.0246623040, 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 18.019999999999982
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0006000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0809022490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7870387410, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8400000000, query time of that 7.7767410650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0840371290, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8200000000, query time of that 0.7933138390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2076.31 < 2076.6
  -> Decision False in time 1.5500000000, query time of that 1.5446609430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0879420390, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1357.35 < 1381.25
  -> Decision False in time 0.8900000000, query time of that 0.8743719140, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1020.12 < 1121.52
  -> Decision False in time 1.0000000000, query time of that 0.9824600310, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 20000])
Got a train set of size (60000 * 784)
Built index in 64.82999999999998
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0612035880, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5841286180, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1597.52 < 1644.18
  -> Decision False in time 3.9600000000, query time of that 3.9207872330, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0626368020, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6166559850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 6.3200000000, query time of that 6.2198480090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0709746280, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
906.013 < 1062.17
  -> Decision False in time 0.4100000000, query time of that 0.3342329320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1055.43 < 1071.7
  -> Decision False in time 1.1400000000, query time of that 0.9578757170, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100000])
Got a train set of size (60000 * 784)
Built index in 64.83000000000004
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1601113660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5402234700, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2000000000, query time of that 15.1265095490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1614678000, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5700000000, query time of that 1.5621807650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.4700000000, query time of that 15.3478264920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1671895060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7600000000, query time of that 1.6670902530, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1307.51 < 1322.88
  -> Decision False in time 12.7300000000, query time of that 12.6560999620, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 20000])
Got a train set of size (60000 * 784)
Built index in 33.75
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0525807080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5093971570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1616.44 < 1787.46
  -> Decision False in time 2.3600000000, query time of that 2.3322776150, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0496829950, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5437790660, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 5.6000000000, query time of that 5.4652705270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0602291790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1643.61 < 1649.03
  -> Decision False in time 0.7100000000, query time of that 0.5289863190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
864.969 < 939.509
  -> Decision False in time 0.4700000000, query time of that 0.3350232650, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 400])
Got a train set of size (60000 * 784)
Built index in 64.75
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0213920770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1937758520, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1120.98 < 1139.4
  -> Decision False in time 0.1900000000, query time of that 0.1935540560, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
842.47 < 874.746
  -> Decision False in time 0.0300000000, query time of that 0.0211949340, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
844.667 < 924.968
  -> Decision False in time 0.0500000000, query time of that 0.0504801890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1110.35 < 1167.64
  -> Decision False in time 0.0700000000, query time of that 0.0693459920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1971.96 < 2013.45
  -> Decision False in time 0.0200000000, query time of that 0.0226073240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1792.37 < 1852.3
  -> Decision False in time 0.0200000000, query time of that 0.0214844550, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1949.66 < 1961.25
  -> Decision False in time 0.0200000000, query time of that 0.0242775960, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 400])
Got a train set of size (60000 * 784)
Built index in 17.980000000000018
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0824850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0116678150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.1001355610, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1083.83 < 1145.47
  -> Decision False in time 0.0600000000, query time of that 0.0531579120, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0110416980, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
998.506 < 1025.71
  -> Decision False in time 0.0300000000, query time of that 0.0320527620, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1311.45 < 1330.96
  -> Decision False in time 0.0200000000, query time of that 0.0170682190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1782.48 < 1798.03
  -> Decision False in time 0.0100000000, query time of that 0.0116415610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1269.3 < 1282.55
  -> Decision False in time 0.0200000000, query time of that 0.0127890190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1140.13 < 1210.72
  -> Decision False in time 0.0200000000, query time of that 0.0120721870, 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 17.960000000000036
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0427616667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0149835980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1162.23 < 1196.46
  -> Decision False in time 0.1000000000, query time of that 0.0954878060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1918.04 < 1941.68
  -> Decision False in time 0.2200000000, query time of that 0.2132178940, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0149917390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1208.91 < 1285.5
  -> Decision False in time 0.0400000000, query time of that 0.0375960450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1100.07 < 1101.76
  -> Decision False in time 0.1400000000, query time of that 0.1380210160, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1281.63 < 1437.14
  -> Decision False in time 0.0200000000, query time of that 0.0168031800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
864.054 < 919.028
  -> Decision False in time 0.0600000000, query time of that 0.0149712860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
988.158 < 994.624
  -> Decision False in time 0.0200000000, query time of that 0.0169487420, 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 33.63999999999987
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.5693258050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.3900000000, query time of that 5.3852713440, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.7900000000, query time of that 53.6992027950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5345528150, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3400000000, query time of that 5.3281363010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.6000000000, query time of that 53.5023829000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.5536508550, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.5100000000, query time of that 5.3849071580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 53.6000000000, query time of that 53.4314433360, 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 17.929999999999836
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0339825550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3412457870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1104.96 < 1140.58
  -> Decision False in time 0.3100000000, query time of that 0.3077450610, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0362410450, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3612262790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1461.87 < 1528.4
  -> Decision False in time 1.6900000000, query time of that 1.6691348340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0418195190, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1696.47 < 1725.56
  -> Decision False in time 0.5700000000, query time of that 0.3054721270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1232.01 < 1245.27
  -> Decision False in time 0.2300000000, query time of that 0.1365860690, 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 64.86999999999989
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0244498500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2323349860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1421.07 < 1439.99
  -> Decision False in time 0.8800000000, query time of that 0.8634280710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0251893670, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1949.3 < 2083.16
  -> Decision False in time 0.1000000000, query time of that 0.0956095770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
917.83 < 933.648
  -> Decision False in time 0.0700000000, query time of that 0.0681585880, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1435.63 < 1469.34
  -> Decision False in time 0.0300000000, query time of that 0.0286791300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1637.75 < 1638.08
  -> Decision False in time 0.0400000000, query time of that 0.0320773390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1211.23 < 1234.69
  -> Decision False in time 0.0500000000, query time of that 0.0291600500, 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 64.96000000000004
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0350950590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3172990270, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1742.81 < 1766.83
  -> Decision False in time 2.3700000000, query time of that 2.3394280840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0373378480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1451.09 < 1458.21
  -> Decision False in time 0.2200000000, query time of that 0.2111794790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1383.64 < 1590.24
  -> Decision False in time 0.1500000000, query time of that 0.1457920790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1664.37 < 1665.08
  -> Decision False in time 0.0400000000, query time of that 0.0385831900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1125.94 < 1219.95
  -> Decision False in time 0.1300000000, query time of that 0.0753635730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
805.946 < 816.044
  -> Decision False in time 0.0500000000, query time of that 0.0411201200, 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 33.68000000000029
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2871547000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.8300000000, query time of that 2.8215809730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.7200000000, query time of that 27.6434582710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2823134480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.8000000000, query time of that 2.7862742340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 27.8900000000, query time of that 27.8086023590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2819671800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.9500000000, query time of that 2.8681074840, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
833.055 < 833.058
  -> Decision False in time 6.5900000000, query time of that 6.5600761670, 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 18.039999999999964
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0119383333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0220969390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2189687670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1528.84 < 1608.99
  -> Decision False in time 1.5100000000, query time of that 1.4830207350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0251076540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2408564320, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1622.19 < 1730.2
  -> Decision False in time 0.1200000000, query time of that 0.1083607450, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0255410370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
876.28 < 979.898
  -> Decision False in time 0.0300000000, query time of that 0.0252284620, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2041.11 < 2046.61
  -> Decision False in time 0.0800000000, query time of that 0.0259409470, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 400])
Got a train set of size (60000 * 784)
Built index in 33.789999999999964
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0141894410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1072.57 < 1088.99
  -> Decision False in time 0.0600000000, query time of that 0.0588800220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
829.668 < 877.629
  -> Decision False in time 0.0300000000, query time of that 0.0331657080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1104.93 < 1105.4
  -> Decision False in time 0.0200000000, query time of that 0.0151459200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1345.04 < 1649.03
  -> Decision False in time 0.0300000000, query time of that 0.0346025800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1098.22 < 1105.94
  -> Decision False in time 0.0200000000, query time of that 0.0193354920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
996.071 < 1027.19
  -> Decision False in time 0.0200000000, query time of that 0.0149143800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
854.776 < 866.483
  -> Decision False in time 0.0100000000, query time of that 0.0150661200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1403.65 < 1439.53
  -> Decision False in time 0.0200000000, query time of that 0.0166759700, 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 33.720000000000255
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0385416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0175294270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1631773800, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1496.39 < 1551.72
  -> Decision False in time 0.0600000000, query time of that 0.0571191270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0187157890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1468.45 < 1488.13
  -> Decision False in time 0.0800000000, query time of that 0.0771209660, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1749.22 < 1955.78
  -> Decision False in time 0.0500000000, query time of that 0.0483351200, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1203.97 < 1247.43
  -> Decision False in time 0.0400000000, query time of that 0.0195112910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1374.23 < 1381.8
  -> Decision False in time 0.0300000000, query time of that 0.0225392180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1676.43 < 1685.59
  -> Decision False in time 0.0200000000, query time of that 0.0191930820, 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: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1716028700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6700000000, query time of that 1.6678649490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.5700000000, query time of that 16.4963165810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1707537050, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6800000000, query time of that 1.6658048090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.6100000000, query time of that 16.5372890420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1718264020, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9000000000, query time of that 1.7599105460, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 18.1000000000, query time of that 17.5719511210, 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 64.8100000000004
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Reject!
2001.33 < 2019.49
  -> Decision False in time 0.0200000000, query time of that 0.0201524740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1436.98 < 1469.59
  -> Decision False in time 0.0900000000, query time of that 0.0947780380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1450.23 < 1460.94
  -> Decision False in time 0.1800000000, query time of that 0.1675574410, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1037.52 < 1047.63
  -> Decision False in time 0.0200000000, query time of that 0.0228342420, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1971.95 < 2032.27
  -> Decision False in time 0.0200000000, query time of that 0.0194794580, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1253.61 < 1288.03
  -> Decision False in time 0.0200000000, query time of that 0.0196031600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1372.94 < 1403.94
  -> Decision False in time 0.0300000000, query time of that 0.0230958000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1392.41 < 1421.12
  -> Decision False in time 0.0300000000, query time of that 0.0245750340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1376.63 < 1392.97
  -> Decision False in time 0.0400000000, query time of that 0.0260003940, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 40000])
Got a train set of size (60000 * 784)
Built index in 64.67000000000007
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0874199230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8300000000, query time of that 0.8230270970, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.3300000000, query time of that 8.2686132790, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0920450750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8700000000, query time of that 0.8594456750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.8200000000, query time of that 8.6471606480, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0926473110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1900000000, query time of that 1.0443977270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1775.64 < 1802.3
  -> Decision False in time 4.8400000000, query time of that 4.7834278610, 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 65.05999999999949
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0436391270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4316865140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3000000000, query time of that 4.2556368320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0471559600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4800000000, query time of that 0.4658807410, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1488.72 < 1502.06
  -> Decision False in time 0.9300000000, query time of that 0.9198739060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1713.25 < 1721.6
  -> Decision False in time 0.0500000000, query time of that 0.0500815000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1108.78 < 1200.62
  -> Decision False in time 0.6300000000, query time of that 0.4213185770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1361.72 < 1449.96
  -> Decision False in time 0.2300000000, query time of that 0.1607291950, 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 18.06999999999971
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0185792710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1706372930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1376.12 < 1450.26
  -> Decision False in time 0.5700000000, query time of that 0.5539948050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0175418400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1919798080, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1652.17 < 1763.06
  -> Decision False in time 0.0600000000, query time of that 0.0642110420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1159.87 < 1217.2
  -> Decision False in time 0.0400000000, query time of that 0.0198131420, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
738.762 < 747.959
  -> Decision False in time 0.0700000000, query time of that 0.0217712420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1673.06 < 1711.93
  -> Decision False in time 0.0900000000, query time of that 0.0290588000, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 2000])
Got a train set of size (60000 * 784)
Built index in 64.99000000000069
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0193766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0282297750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1769.77 < 1838.86
  -> Decision False in time 0.1700000000, query time of that 0.1670080440, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.6400000000, query time of that 2.5869366390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1223.63 < 1238.44
  -> Decision False in time 0.0400000000, query time of that 0.0288705500, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2053.12 < 2093.99
  -> Decision False in time 0.0600000000, query time of that 0.0595453340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1240.26 < 1257.5
  -> Decision False in time 0.1000000000, query time of that 0.0926769660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
874.998 < 951.691
  -> Decision False in time 0.0700000000, query time of that 0.0309376480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1285.74 < 1299.17
  -> Decision False in time 0.1000000000, query time of that 0.0542492470, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
992.014 < 1049.65
  -> Decision False in time 0.0300000000, query time of that 0.0295207660, 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 18.029999999999745
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0525309730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4903716300, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
756.292 < 1005.39
  -> Decision False in time 2.3300000000, query time of that 2.3039981300, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0520263250, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5188420090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1165.38 < 1239.63
  -> Decision False in time 2.2800000000, query time of that 2.2653908020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0568123470, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1349.35 < 1446.99
  -> Decision False in time 0.1900000000, query time of that 0.1332071310, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1257.95 < 1263.88
  -> Decision False in time 0.5800000000, query time of that 0.4179184780, 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 33.789999999999964
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Reject!
1506.27 < 1542.13
  -> Decision False in time 0.0200000000, query time of that 0.0143532610, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1297.61 < 1335.77
  -> Decision False in time 0.1000000000, query time of that 0.0975467440, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1030.83 < 1104.3
  -> Decision False in time 0.0900000000, query time of that 0.0907806270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0152185560, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1389.67 < 1433.75
  -> Decision False in time 0.0300000000, query time of that 0.0343319450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
943.864 < 1036.59
  -> Decision False in time 0.0300000000, query time of that 0.0271652590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1640.15 < 1798.36
  -> Decision False in time 0.0200000000, query time of that 0.0146464480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1150.59 < 1159.87
  -> Decision False in time 0.0100000000, query time of that 0.0153037250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
943.11 < 987.618
  -> Decision False in time 0.0200000000, query time of that 0.0148256270, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 400000])
Got a train set of size (60000 * 784)
Built index in 18.020000000000437
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5847672130, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.0000000000, query time of that 5.9931431940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 59.4200000000, query time of that 59.3229402060, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6211771290, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.0100000000, query time of that 5.9927684270, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.7100000000, query time of that 59.6023981270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.6421010820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.1200000000, query time of that 6.0305478410, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 60.4300000000, query time of that 60.2391963570, 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 33.67000000000007
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0368549980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3636358570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.6800000000, query time of that 3.6283997030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0406568010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.4007053740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1174.74 < 1215.42
  -> Decision False in time 1.1700000000, query time of that 1.1587067740, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1067.69 < 1072.95
  -> Decision False in time 0.0500000000, query time of that 0.0388246000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1605.84 < 1832.3
  -> Decision False in time 0.1400000000, query time of that 0.0923792130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1153.66 < 1174.69
  -> Decision False in time 0.2400000000, query time of that 0.1467555650, 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 17.959999999999127
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Reject!
2263.71 < 2358.04
  -> Decision False in time 0.0100000000, query time of that 0.0115127520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2229.57 < 2249.68
  -> Decision False in time 0.0200000000, query time of that 0.0188000460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1444.56 < 1458.27
  -> Decision False in time 0.0200000000, query time of that 0.0171248040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0117263430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1390.11 < 1405.63
  -> Decision False in time 0.0200000000, query time of that 0.0113518120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1443.33 < 1473.36
  -> Decision False in time 0.0100000000, query time of that 0.0168376560, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1107.3 < 1134.14
  -> Decision False in time 0.0200000000, query time of that 0.0119010180, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1110.84 < 1116.12
  -> Decision False in time 0.0200000000, query time of that 0.0122124960, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
901.074 < 928.217
  -> Decision False in time 0.0100000000, query time of that 0.0117089350, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 200])
Got a train set of size (60000 * 784)
Built index in 64.6299999999992
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Reject!
1390.3 < 1404.52
  -> Decision False in time 0.0200000000, query time of that 0.0210751380, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1896922000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1214.74 < 1240.54
  -> Decision False in time 0.1400000000, query time of that 0.1276456570, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1786.75 < 1786.88
  -> Decision False in time 0.0200000000, query time of that 0.0226573940, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1466.8 < 1475.29
  -> Decision False in time 0.0300000000, query time of that 0.0318138710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1164.97 < 1189.67
  -> Decision False in time 0.1300000000, query time of that 0.1270619160, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
976.474 < 1018.07
  -> Decision False in time 0.0300000000, query time of that 0.0216741010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1196.61 < 1202.92
  -> Decision False in time 0.0600000000, query time of that 0.0262517030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1212.38 < 1225.71
  -> Decision False in time 0.0200000000, query time of that 0.0257159810, 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: 0.0002100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1608262010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5180047480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.1100000000, query time of that 15.0523831390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1545589350, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5200000000, query time of that 1.5051873240, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.3400000000, query time of that 15.2569242880, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1631743200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1305.8 < 1338.27
  -> Decision False in time 1.1500000000, query time of that 1.1427460110, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1132.15 < 1142.81
  -> Decision False in time 2.8800000000, query time of that 2.8584439270, 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 17.8799999999992
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3148550850, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1700000000, query time of that 3.1565604830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.4400000000, query time of that 31.3668707670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3216873910, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1500000000, query time of that 3.1292016980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.3700000000, query time of that 31.2892977390, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3224630690, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.3200000000, query time of that 3.1935075790, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.5300000000, query time of that 32.0984275030, 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 65.29999999999927
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.5057597900, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9800000000, query time of that 4.9668320450, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.4800000000, query time of that 49.4004014300, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5300000000, query time of that 0.5221746800, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9500000000, query time of that 4.9339204050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.5900000000, query time of that 49.4990583090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5080868330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.0400000000, query time of that 4.9478083610, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 49.8500000000, query time of that 49.3216625820, 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 33.73999999999978
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0153037620, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2000.49 < 2013.81
  -> Decision False in time 0.0700000000, query time of that 0.0662010360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1913.31 < 1934.95
  -> Decision False in time 0.7700000000, query time of that 0.7511619990, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1756.81 < 1886.75
  -> Decision False in time 0.0200000000, query time of that 0.0152422730, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1451.79 < 1486.99
  -> Decision False in time 0.0100000000, query time of that 0.0134427170, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1254.88 < 1264.23
  -> Decision False in time 0.0400000000, query time of that 0.0336759320, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1146.94 < 1169.12
  -> Decision False in time 0.0200000000, query time of that 0.0152484760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1336.11 < 1391.69
  -> Decision False in time 0.0300000000, query time of that 0.0150228060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1489.38 < 1527.15
  -> Decision False in time 0.0200000000, query time of that 0.0178718700, 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 18.06999999999971
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0115634930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1269.29 < 1317
  -> Decision False in time 0.0500000000, query time of that 0.0534531200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1602.95 < 1620.21
  -> Decision False in time 0.0200000000, query time of that 0.0214864800, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1230.18 < 1254.28
  -> Decision False in time 0.0200000000, query time of that 0.0113255680, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
940.215 < 951.831
  -> Decision False in time 0.0100000000, query time of that 0.0156564890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
964.552 < 998.741
  -> Decision False in time 0.0200000000, query time of that 0.0204123310, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1782.56 < 1854.78
  -> Decision False in time 0.0200000000, query time of that 0.0118493380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1395.77 < 1422.94
  -> Decision False in time 0.0100000000, query time of that 0.0119843320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1557.13 < 1562.24
  -> Decision False in time 0.0100000000, query time of that 0.0127574010, 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 33.67000000000007
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0807664430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7809265030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8100000000, query time of that 7.7547249660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0744196430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8500000000, query time of that 0.8002978330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1900000000, query time of that 8.0901712930, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0909217070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1900000000, query time of that 0.9689887580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1028.7 < 1031.09
  -> Decision False in time 0.4300000000, query time of that 0.4022517600, 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 65.10000000000036
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2712865540, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6600000000, query time of that 2.6601362660, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.3800000000, query time of that 26.3038838960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2746815690, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6800000000, query time of that 2.6591454670, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.2800000000, query time of that 26.1915691920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.2700873700, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8200000000, query time of that 2.7256094510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1001.75 < 1117.56
  -> Decision False in time 2.7200000000, query time of that 2.7115086190, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 4000])
Got a train set of size (60000 * 784)
Built index in 33.649999999999636
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0266658740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2496205750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.5000000000, query time of that 2.4493749700, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0254541680, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2016.24 < 2130.71
  -> Decision False in time 0.1300000000, query time of that 0.1242554870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1660.58 < 1660.97
  -> Decision False in time 0.0700000000, query time of that 0.0680516730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1419.21 < 1440.06
  -> Decision False in time 0.0300000000, query time of that 0.0279284180, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
927.468 < 994.644
  -> Decision False in time 0.0500000000, query time of that 0.0302556880, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1906.36 < 1943.69
  -> Decision False in time 0.1000000000, query time of that 0.0442318940, with c1=5.0000000000, c2=0.1000000000
