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, 40000]), 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, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), 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', 100, 400]), 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, 1000]), 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, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), 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, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]), 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', 200, 2000]), 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', 400, 2000]), 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, 200000]), 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', 400, 4000]), 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', 100, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), 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, 400000]), 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, 400000])]
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 45.5
Index size:  396464.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0836003960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7600000000, query time of that 0.7494961270, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.6400000000, query time of that 7.5786433000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0794537090, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1288.11 < 1298.01
  -> Decision False in time 0.7600000000, query time of that 0.7549190130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1789.35 < 1871.98
  -> Decision False in time 4.7100000000, query time of that 4.6792401470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0811290400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1000000000, query time of that 0.8778057890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1254.11 < 1265.72
  -> Decision False in time 1.2600000000, query time of that 1.1590641630, 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 33.65999999999997
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 0.0374633370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3586179330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1227.6 < 1272.97
  -> Decision False in time 1.6700000000, query time of that 1.6533074330, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0384168660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
764.421 < 776.14
  -> Decision False in time 0.2000000000, query time of that 0.1992238710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1378.64 < 1388.18
  -> Decision False in time 0.6800000000, query time of that 0.6694230740, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0435880100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1070.13 < 1080.26
  -> Decision False in time 0.2200000000, query time of that 0.1336895930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1527.06 < 1541.24
  -> Decision False in time 0.4300000000, query time of that 0.2511659930, 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 18.069999999999936
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 0.0230582250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2216162540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.1900000000, query time of that 2.1524938920, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1504.8 < 1577.93
  -> Decision False in time 0.0300000000, query time of that 0.0224862320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1079.74 < 1086.02
  -> Decision False in time 0.0600000000, query time of that 0.0623554330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
880.622 < 896.625
  -> Decision False in time 0.3300000000, query time of that 0.3166663970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0256275570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
881.806 < 987.647
  -> Decision False in time 0.2600000000, query time of that 0.0989257840, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1220.65 < 1377.07
  -> Decision False in time 0.0400000000, query time of that 0.0267374530, 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 18.049999999999955
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 0.0104238390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1044.46 < 1126.59
  -> Decision False in time 0.0400000000, query time of that 0.0421067530, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
941.455 < 1038.73
  -> Decision False in time 0.1400000000, query time of that 0.1384528780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1390.71 < 1398.94
  -> Decision False in time 0.0200000000, query time of that 0.0107617860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1459.06 < 1497.47
  -> Decision False in time 0.0100000000, query time of that 0.0108543810, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
845.196 < 1199.36
  -> Decision False in time 0.0100000000, query time of that 0.0117281800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1038.79 < 1056.48
  -> Decision False in time 0.0100000000, query time of that 0.0122182710, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1030.13 < 1123.15
  -> Decision False in time 0.0200000000, query time of that 0.0114650510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1295.4 < 1374.77
  -> Decision False in time 0.0100000000, query time of that 0.0125759450, 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 18.210000000000036
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0121639470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
824.833 < 834.47
  -> Decision False in time 0.0900000000, query time of that 0.0890243740, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1353.82 < 1513.88
  -> Decision False in time 0.1800000000, query time of that 0.1725827810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1441.82 < 1454.61
  -> Decision False in time 0.0100000000, query time of that 0.0111867070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
820.944 < 828.13
  -> Decision False in time 0.0300000000, query time of that 0.0270850290, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1982.16 < 1989.48
  -> Decision False in time 0.0200000000, query time of that 0.0191845260, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1137.95 < 1179.23
  -> Decision False in time 0.0200000000, query time of that 0.0126139270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
978.554 < 991.686
  -> Decision False in time 0.0100000000, query time of that 0.0122953940, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1188.7 < 1206.43
  -> Decision False in time 0.0100000000, query time of that 0.0116725640, 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 18.07000000000005
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 0.0816099660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7697332480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8800000000, query time of that 7.8194235410, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0812481790, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8300000000, query time of that 0.8042119510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1326.73 < 1333.42
  -> Decision False in time 6.4800000000, query time of that 6.4275898060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0911674840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1600000000, query time of that 0.9990764940, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1386.68 < 1450.33
  -> Decision False in time 0.6500000000, query time of that 0.6400605280, 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 18.11999999999989
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0824850000
  Testing...
|S| = 20
|T| = 283
Reject!
1156.91 < 1177.12
  -> Decision False in time 0.0100000000, query time of that 0.0106760060, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.1020822130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1152.59 < 1162.83
  -> Decision False in time 0.0500000000, query time of that 0.0473433310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0118797850, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1340.35 < 1602.97
  -> Decision False in time 0.0100000000, query time of that 0.0115687140, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1420.88 < 1422.81
  -> Decision False in time 0.0200000000, query time of that 0.0102371350, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1249.44 < 1254.1
  -> Decision False in time 0.0100000000, query time of that 0.0109217250, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
615.54 < 740.575
  -> Decision False in time 0.0300000000, query time of that 0.0106127130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
859.973 < 889.295
  -> Decision False in time 0.0100000000, query time of that 0.0114263190, 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 33.75999999999999
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 0.0149165940, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1295306100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
935.044 < 1016.58
  -> Decision False in time 0.0300000000, query time of that 0.0372022220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1199.33 < 1208.73
  -> Decision False in time 0.0200000000, query time of that 0.0137530310, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1103.45 < 1138.89
  -> Decision False in time 0.0200000000, query time of that 0.0223255510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1083.77 < 1085.62
  -> Decision False in time 0.0600000000, query time of that 0.0554936030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1731.43 < 1806.29
  -> Decision False in time 0.0200000000, query time of that 0.0156776310, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1823.77 < 1831.5
  -> Decision False in time 0.0100000000, query time of that 0.0153116220, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
763.132 < 793.437
  -> Decision False in time 0.0200000000, query time of that 0.0149756110, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 1000])
Got a train set of size (60000 * 784)
Built index in 18.039999999999964
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 0.0145068480, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1355795940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1019.44 < 1113.43
  -> Decision False in time 0.0400000000, query time of that 0.0468928510, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0155856180, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
897.995 < 911.798
  -> Decision False in time 0.0500000000, query time of that 0.0466702230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1717.85 < 1718.11
  -> Decision False in time 0.0400000000, query time of that 0.0381788930, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1214.24 < 1230.85
  -> Decision False in time 0.0100000000, query time of that 0.0175641480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1883.62 < 1885.54
  -> Decision False in time 0.0200000000, query time of that 0.0169082130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1091.27 < 1115.81
  -> Decision False in time 0.0500000000, query time of that 0.0176066420, 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 33.76999999999998
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 0.0267013430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1014.22 < 1111.27
  -> Decision False in time 0.1300000000, query time of that 0.1260229100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1010.51 < 1050.11
  -> Decision False in time 1.3700000000, query time of that 1.3485995310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0284328310, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1296.11 < 1311.83
  -> Decision False in time 0.0600000000, query time of that 0.0564704280, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1838.24 < 1868.52
  -> Decision False in time 0.7200000000, query time of that 0.7080910900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0306787590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1802.96 < 1911.85
  -> Decision False in time 0.1500000000, query time of that 0.0651021160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1274.26 < 1575.39
  -> Decision False in time 0.0700000000, query time of that 0.0309692790, 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 65.80999999999995
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1577781420, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5500000000, query time of that 1.5432283890, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2300000000, query time of that 15.1631151720, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1611746820, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5209553470, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.4100000000, query time of that 15.3292311570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1604937530, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1155.58 < 1258.12
  -> Decision False in time 1.0600000000, query time of that 1.0525905850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1910.14 < 2002.84
  -> Decision False in time 2.3600000000, query time of that 2.3487157340, 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 17.950000000000045
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0511169090, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4980311050, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9600000000, query time of that 4.9044363550, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0512573190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5162425290, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1123.12 < 1148.76
  -> Decision False in time 0.3500000000, query time of that 0.3483069960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0594955610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1100000000, query time of that 0.6338941740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1409.91 < 1418.02
  -> Decision False in time 2.0700000000, query time of that 1.4409945650, 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 0.5611961170, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.4500000000, query time of that 5.4414031190, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.4800000000, query time of that 53.3938930940, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5417613850, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3200000000, query time of that 5.3052589000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.6100000000, query time of that 53.5172561150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6100000000, query time of that 0.5299330900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.5100000000, query time of that 5.4217678320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 54.2400000000, query time of that 54.0685472280, 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 65.01000000000022
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0829648950, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8297241760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.3900000000, query time of that 8.3264039340, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0842182370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.9000000000, query time of that 0.8789553180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1313.05 < 1458.59
  -> Decision False in time 6.0700000000, query time of that 6.0339783890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.0957691630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 1.0305486800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
714.855 < 1086.56
  -> Decision False in time 1.6000000000, query time of that 1.5834279680, 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 33.57999999999993
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 0.0151504440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1314989510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1773.26 < 1782.17
  -> Decision False in time 0.0100000000, query time of that 0.0156842240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0143032130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1237.15 < 1331.2
  -> Decision False in time 0.0300000000, query time of that 0.0253829880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1391.73 < 1469.66
  -> Decision False in time 0.0400000000, query time of that 0.0429633840, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1200.44 < 1372.94
  -> Decision False in time 0.0200000000, query time of that 0.0151989470, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
878.216 < 901.039
  -> Decision False in time 0.0300000000, query time of that 0.0148970930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1239.47 < 1258.35
  -> Decision False in time 0.0100000000, query time of that 0.0167744640, 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 65.17000000000007
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 0.0255494590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1373.19 < 1473.63
  -> Decision False in time 0.1500000000, query time of that 0.1489543560, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1369.78 < 1515.52
  -> Decision False in time 0.1700000000, query time of that 0.1634285620, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0256488710, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1524.82 < 1535.88
  -> Decision False in time 0.1000000000, query time of that 0.0946973740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1184.73 < 1188.61
  -> Decision False in time 0.0900000000, query time of that 0.0895441540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1124.1 < 1150.79
  -> Decision False in time 0.0300000000, query time of that 0.0322715290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1207.94 < 1228.37
  -> Decision False in time 0.0400000000, query time of that 0.0316665930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1092.6 < 1106.33
  -> Decision False in time 0.0400000000, query time of that 0.0282017680, 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 18.01000000000022
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3334869450, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1800000000, query time of that 3.1732570260, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.4700000000, query time of that 31.3913693410, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3068426030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1500000000, query time of that 3.1404989070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.2400000000, query time of that 31.1489946080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3230181670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.3000000000, query time of that 3.1655764810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.3000000000, query time of that 31.9982490770, 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 33.909999999999854
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 0.0151028520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1310736340, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1218.92 < 1223.42
  -> Decision False in time 0.2000000000, query time of that 0.1970216370, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0157280320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
919.548 < 926.752
  -> Decision False in time 0.0500000000, query time of that 0.0548855920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1140.7 < 1170.43
  -> Decision False in time 0.0400000000, query time of that 0.0372514500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1003.29 < 1040.57
  -> Decision False in time 0.0200000000, query time of that 0.0134343670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1325.66 < 1353.34
  -> Decision False in time 0.0300000000, query time of that 0.0170695100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1007.36 < 1026.13
  -> Decision False in time 0.0200000000, query time of that 0.0163093250, 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 65.26999999999953
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0192663140, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1585.53 < 1688.46
  -> Decision False in time 0.1000000000, query time of that 0.0993260530, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1230.61 < 1251.12
  -> Decision False in time 0.5800000000, query time of that 0.5699878670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1669.58 < 1706.92
  -> Decision False in time 0.0200000000, query time of that 0.0215522770, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1050.01 < 1053.76
  -> Decision False in time 0.0600000000, query time of that 0.0547632820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1558.06 < 1573.08
  -> Decision False in time 0.0400000000, query time of that 0.0376344800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1140.38 < 1156.94
  -> Decision False in time 0.0200000000, query time of that 0.0212529230, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1683.72 < 1715.16
  -> Decision False in time 0.0200000000, query time of that 0.0202779850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1232.89 < 1315.18
  -> Decision False in time 0.0700000000, query time of that 0.0250970890, 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 33.850000000000364
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0209449870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.2018484940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1728.8 < 1791.81
  -> Decision False in time 1.0100000000, query time of that 0.9835591020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1367.18 < 1377.09
  -> Decision False in time 0.0200000000, query time of that 0.0197072620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
903.106 < 914.91
  -> Decision False in time 0.0900000000, query time of that 0.0902710040, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
788.424 < 918.158
  -> Decision False in time 0.2400000000, query time of that 0.2361246220, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
881.263 < 920.239
  -> Decision False in time 0.0400000000, query time of that 0.0252773890, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1617.72 < 1655.08
  -> Decision False in time 0.1200000000, query time of that 0.0511726950, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1174.64 < 1197.53
  -> Decision False in time 0.0300000000, query time of that 0.0253381480, 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 65.11999999999989
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 0.0471756460, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4452217110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3500000000, query time of that 4.3013887900, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0480597270, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4564982860, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 4.8800000000, query time of that 4.7386456480, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0515444090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1369.94 < 1374.04
  -> Decision False in time 0.5100000000, query time of that 0.3467333980, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1482.81 < 1546.91
  -> Decision False in time 0.3300000000, query time of that 0.2271686790, 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 65.25
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 0.0292564150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
893.674 < 938.252
  -> Decision False in time 0.0800000000, query time of that 0.0792353900, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1330.21 < 1432.25
  -> Decision False in time 0.8900000000, query time of that 0.8727926780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0315553960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1101.77 < 1109.26
  -> Decision False in time 0.0300000000, query time of that 0.0311274570, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1598.62 < 1631.43
  -> Decision False in time 0.0800000000, query time of that 0.0763442490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1133.12 < 1134.23
  -> Decision False in time 0.0500000000, query time of that 0.0335136340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1180.38 < 1181.27
  -> Decision False in time 0.0900000000, query time of that 0.0453765610, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1151.06 < 1188.05
  -> Decision False in time 0.1100000000, query time of that 0.0559625160, 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 65.15000000000055
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2684873990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6200000000, query time of that 2.6219393990, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.3400000000, query time of that 26.2681862010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2760258690, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6600000000, query time of that 2.6453244670, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.4800000000, query time of that 26.4011191520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.2679067020, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8200000000, query time of that 2.7335607790, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 27.3400000000, query time of that 26.9292516750, 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 33.69000000000051
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2843668970, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.8200000000, query time of that 2.8144163780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 28.0800000000, query time of that 28.0081509830, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2784232460, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.7900000000, query time of that 2.7741975010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 27.8800000000, query time of that 27.7944865420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.2965397410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.9500000000, query time of that 2.8468514090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1910.14 < 2002.84
  -> Decision False in time 20.7200000000, query time of that 20.6540810600, 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 33.94000000000051
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 0.0175804430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1674146770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
596.42 < 613.44
  -> Decision False in time 1.3700000000, query time of that 1.3331685670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
943.832 < 970.185
  -> Decision False in time 0.0200000000, query time of that 0.0174535520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1053.96 < 1199.31
  -> Decision False in time 0.0500000000, query time of that 0.0463425880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1390.3 < 1396.08
  -> Decision False in time 0.1000000000, query time of that 0.0990762190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
908.336 < 940.408
  -> Decision False in time 0.0200000000, query time of that 0.0177430410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1506.87 < 1590.68
  -> Decision False in time 0.0300000000, query time of that 0.0199904900, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1352.57 < 1361.04
  -> Decision False in time 0.0700000000, query time of that 0.0213359050, 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 18.040000000000873
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0361302230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3355584840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.3300000000, query time of that 3.2912405980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0361293420, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3583970570, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1560.37 < 1566.58
  -> Decision False in time 0.4000000000, query time of that 0.4001940800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0372713830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1753.31 < 1831.49
  -> Decision False in time 0.0500000000, query time of that 0.0426968370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
905.643 < 955.967
  -> Decision False in time 0.0400000000, query time of that 0.0400763430, 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 65.14000000000124
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0345048980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3228997340, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.2300000000, query time of that 3.1767899100, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0382216580, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1082.48 < 1086.78
  -> Decision False in time 0.2100000000, query time of that 0.2020097870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1187.43 < 1213.67
  -> Decision False in time 0.6700000000, query time of that 0.6582556030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1390.39 < 1409.09
  -> Decision False in time 0.0500000000, query time of that 0.0389968170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1469.44 < 1537.08
  -> Decision False in time 0.0400000000, query time of that 0.0397923910, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1007.1 < 1150.84
  -> Decision False in time 0.0600000000, query time of that 0.0409728500, 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 65.5
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Reject!
1013.1 < 1089.3
  -> Decision False in time 0.0700000000, query time of that 0.0622371860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5888188960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.8600000000, query time of that 5.8001563650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0623393750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6185437850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1413.68 < 1430.2
  -> Decision False in time 3.8000000000, query time of that 3.7667319940, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0696460230, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
981.454 < 1000.94
  -> Decision False in time 0.0600000000, query time of that 0.0626717020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1946.19 < 1983.24
  -> Decision False in time 0.1000000000, query time of that 0.0840136110, 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 18.05999999999949
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 0.0192525620, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1702523420, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1522.58 < 1525.9
  -> Decision False in time 1.6800000000, query time of that 1.6368473600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0181535100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.1863847420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1479.19 < 1573.35
  -> Decision False in time 0.0500000000, query time of that 0.0450141840, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0204433780, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1157.49 < 1157.53
  -> Decision False in time 0.0300000000, query time of that 0.0205998130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2069.21 < 2099.07
  -> Decision False in time 0.0400000000, query time of that 0.0204971870, 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 65.28000000000065
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0210082100, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1616.61 < 1789.16
  -> Decision False in time 0.0300000000, query time of that 0.0343680020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1742.67 < 1757.23
  -> Decision False in time 0.1900000000, query time of that 0.1854372680, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1625.6 < 1719.96
  -> Decision False in time 0.0200000000, query time of that 0.0203808220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
941.956 < 945.409
  -> Decision False in time 0.1200000000, query time of that 0.1106403020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1080.49 < 1089.35
  -> Decision False in time 0.0500000000, query time of that 0.0577419870, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
951.76 < 976.572
  -> Decision False in time 0.0300000000, query time of that 0.0229297050, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
992.972 < 1119.4
  -> Decision False in time 0.0300000000, query time of that 0.0254122630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1206.36 < 1279.14
  -> Decision False in time 0.0200000000, query time of that 0.0229721870, 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 65.14000000000124
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Reject!
1473 < 1549.5
  -> Decision False in time 0.0200000000, query time of that 0.0211331780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1175.21 < 1230.45
  -> Decision False in time 0.0500000000, query time of that 0.0470201500, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1306.97 < 1338.2
  -> Decision False in time 0.1800000000, query time of that 0.1756651600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1821.85 < 1829.05
  -> Decision False in time 0.0200000000, query time of that 0.0222861800, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1444.1 < 1444.78
  -> Decision False in time 0.0600000000, query time of that 0.0575835520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1948.18 < 1951.77
  -> Decision False in time 0.1800000000, query time of that 0.1726458540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1420.67 < 1440.44
  -> Decision False in time 0.0200000000, query time of that 0.0208554220, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1359.47 < 1360.96
  -> Decision False in time 0.0300000000, query time of that 0.0239104900, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1280.04 < 1310.91
  -> Decision False in time 0.0200000000, query time of that 0.0244797490, 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 0.0522033460, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5300000000, query time of that 0.5170717250, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1700000000, query time of that 5.1108961310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0552284510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5332710720, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1996.05 < 2086.13
  -> Decision False in time 0.6400000000, query time of that 0.6348342180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0641498040, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
976.495 < 981.587
  -> Decision False in time 0.0600000000, query time of that 0.0588591980, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1213.59 < 1216.58
  -> Decision False in time 0.2100000000, query time of that 0.1464219080, 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 33.649999999999636
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 0.1566557500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5209779220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.1800000000, query time of that 15.1235113360, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1664960250, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5600000000, query time of that 1.5423948910, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.5000000000, query time of that 15.3442288120, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.1622249790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7700000000, query time of that 1.6260495040, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2091.81 < 2118.4
  -> Decision False in time 6.1400000000, query time of that 6.1033327000, 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 18.039999999999054
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6100000000, query time of that 0.6079275360, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.0000000000, query time of that 5.9871630330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 59.7900000000, query time of that 59.7038137770, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6227385350, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.0000000000, query time of that 5.9751824920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.9300000000, query time of that 59.8352018160, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6122949790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.0600000000, query time of that 5.9784867680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 60.3800000000, query time of that 60.2094177820, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 100000])
Got a train set of size (60000 * 784)
Built index in 18.05000000000109
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1791697300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6700000000, query time of that 1.6647621250, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.4900000000, query time of that 16.4156473480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1668287320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6800000000, query time of that 1.6672354390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.7300000000, query time of that 16.6284678450, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1795597260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9300000000, query time of that 1.7985881190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2886.46 < 2906.82
  -> Decision False in time 11.7300000000, query time of that 11.6760320750, 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 65.1200000000008
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 0.4970314230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9500000000, query time of that 4.9403750330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.2300000000, query time of that 49.1444300110, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5048128310, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9300000000, query time of that 4.9112120340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.3300000000, query time of that 49.2365523000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5143135400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.1200000000, query time of that 5.0057012680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 50.2500000000, query time of that 49.7892112110, with c1=5.0000000000, c2=0.1000000000
