copying files to /scratch...
starting benchmark...
/scratch/knn/venv/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
running only annoy
order: [Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), 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, 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', 400, 1000]), 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, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]), 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', 100, 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', 400, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]), 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, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), 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', 400, 400000]), 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, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), 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, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 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, 10000])]
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 23.78
Index size:  305104.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6500000000, query time of that 0.6405671940, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.0200000000, query time of that 6.0132955960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 60.0700000000, query time of that 59.9766977180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6266495320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.0700000000, query time of that 6.0493302380, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.5000000000, query time of that 59.3986469140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6184228120, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.1800000000, query time of that 6.0918088200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 60.2300000000, query time of that 59.9744668440, 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 33.899999999999636
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0542724300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4937569900, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.0800000000, query time of that 5.0286313020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0562296320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5800000000, query time of that 0.5451340650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1241.44 < 1264.06
  -> Decision False in time 2.1900000000, query time of that 2.1696436470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0623739650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0700000000, query time of that 0.6964513570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1049.92 < 1072.5
  -> Decision False in time 1.0800000000, query time of that 0.8015638010, 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 33.840000000000146
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2864143470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.8500000000, query time of that 2.8347257980, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.9200000000, query time of that 27.8540974840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2796379000, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.8000000000, query time of that 2.7808876590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 27.8900000000, query time of that 27.8089013340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2873866380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.0100000000, query time of that 2.8482967300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1627.29 < 1695.73
  -> Decision False in time 6.8600000000, query time of that 6.8368356390, 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 33.789999999999964
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0385416667
  Testing...
|S| = 20
|T| = 283
Reject!
1708.95 < 1741.39
  -> Decision False in time 0.0200000000, query time of that 0.0181422340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1912.91 < 1948.45
  -> Decision False in time 0.0900000000, query time of that 0.0850553870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1556.12 < 1690.71
  -> Decision False in time 0.3200000000, query time of that 0.3166088350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0195612730, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1575.77 < 1647.05
  -> Decision False in time 0.0200000000, query time of that 0.0257806530, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1147.89 < 1183.35
  -> Decision False in time 0.0700000000, query time of that 0.0669887750, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1121.58 < 1139.12
  -> Decision False in time 0.0300000000, query time of that 0.0201039610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1280.32 < 1308.5
  -> Decision False in time 0.0200000000, query time of that 0.0209983870, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1102.96 < 1118.33
  -> Decision False in time 0.0200000000, query time of that 0.0218998360, 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 65.22000000000025
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0244537190, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2322779400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1330.93 < 1336.18
  -> Decision False in time 0.0700000000, query time of that 0.0729804010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0266010820, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1274.14 < 1279.33
  -> Decision False in time 0.2100000000, query time of that 0.2074536970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1664.12 < 1728.38
  -> Decision False in time 0.0500000000, query time of that 0.0480989490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
748.9 < 769.912
  -> Decision False in time 0.0300000000, query time of that 0.0259646230, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1051.85 < 1054.88
  -> Decision False in time 0.0300000000, query time of that 0.0282405640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1418.35 < 1444.05
  -> Decision False in time 0.0500000000, query time of that 0.0295521610, 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 64.69000000000005
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0230024080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1794.96 < 1834.33
  -> Decision False in time 0.1000000000, query time of that 0.0957951500, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1121.43 < 1158.02
  -> Decision False in time 0.1800000000, query time of that 0.1783543380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0228387550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1141.83 < 1217.97
  -> Decision False in time 0.0200000000, query time of that 0.0213038490, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
816.524 < 843.358
  -> Decision False in time 0.0200000000, query time of that 0.0189467520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1317.15 < 1338.23
  -> Decision False in time 0.0200000000, query time of that 0.0217770800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1853.87 < 1947.08
  -> Decision False in time 0.0300000000, query time of that 0.0226912910, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
648.302 < 905.961
  -> Decision False in time 0.0200000000, query time of that 0.0225810320, 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 65.0
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2632597550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6400000000, query time of that 2.6296492760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.3500000000, query time of that 26.2775846430, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2710457750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6500000000, query time of that 2.6410328960, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.4900000000, query time of that 26.3995810040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2741605500, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8500000000, query time of that 2.7201834720, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 27.5500000000, query time of that 27.1385999200, 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 17.889999999999418
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0006000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0850533180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7864736780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.9300000000, query time of that 7.8785301520, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0810176870, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8200000000, query time of that 0.8009507210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1800000000, query time of that 8.0640957590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0925775080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
991.782 < 1007.84
  -> Decision False in time 0.7600000000, query time of that 0.7485330780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1504.08 < 1578.64
  -> Decision False in time 0.1600000000, query time of that 0.1423834860, 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 64.60000000000036
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0623508830, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6000000000, query time of that 0.5931221790, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.8600000000, query time of that 5.7995091380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0655815140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6214111390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 6.3100000000, query time of that 6.2312130170, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0695095750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2213.72 < 2250.58
  -> Decision False in time 0.1300000000, query time of that 0.1098027490, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1926.57 < 1934.06
  -> Decision False in time 0.7500000000, query time of that 0.6270673130, 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 17.970000000000255
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0427616667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0150615790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2074.31 < 2173.37
  -> Decision False in time 0.0200000000, query time of that 0.0182282450, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1383.64 < 1666.69
  -> Decision False in time 0.0600000000, query time of that 0.0621441350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0159224360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1231.7 < 1245.27
  -> Decision False in time 0.0300000000, query time of that 0.0249529800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1336.38 < 1539.14
  -> Decision False in time 0.0400000000, query time of that 0.0345617290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1128.8 < 1198.47
  -> Decision False in time 0.0400000000, query time of that 0.0157990120, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1003.68 < 1018.12
  -> Decision False in time 0.0200000000, query time of that 0.0173472300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1202.44 < 1266.33
  -> Decision False in time 0.0200000000, query time of that 0.0170109130, 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 18.11999999999989
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0112472680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1462.45 < 1487.46
  -> Decision False in time 0.0100000000, query time of that 0.0144064880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
909.481 < 975.676
  -> Decision False in time 0.1300000000, query time of that 0.1210373870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1198.16 < 1292.24
  -> Decision False in time 0.0200000000, query time of that 0.0107785890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2012.89 < 2018.35
  -> Decision False in time 0.0100000000, query time of that 0.0120859990, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1527.24 < 1689.07
  -> Decision False in time 0.0400000000, query time of that 0.0397101250, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1283.48 < 1297.15
  -> Decision False in time 0.0100000000, query time of that 0.0111900180, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1262.16 < 1266.66
  -> Decision False in time 0.0200000000, query time of that 0.0131882820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
985.386 < 999.571
  -> Decision False in time 0.0100000000, query time of that 0.0132718520, 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 64.93000000000029
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0219521240, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1219.72 < 1278.59
  -> Decision False in time 0.1700000000, query time of that 0.1694004880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1189.14 < 1193.7
  -> Decision False in time 0.5800000000, query time of that 0.5708922690, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1568.15 < 1583.44
  -> Decision False in time 0.0300000000, query time of that 0.0226265680, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1282.43 < 1318.19
  -> Decision False in time 0.0300000000, query time of that 0.0350796200, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1202.35 < 1210.34
  -> Decision False in time 0.0500000000, query time of that 0.0409831480, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1111.17 < 1153.75
  -> Decision False in time 0.0400000000, query time of that 0.0258554010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
778.599 < 779.431
  -> Decision False in time 0.0500000000, query time of that 0.0270820170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1995.45 < 2013.45
  -> Decision False in time 0.0200000000, query time of that 0.0224869550, 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 64.92000000000007
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0322086680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
938.221 < 995.302
  -> Decision False in time 0.2500000000, query time of that 0.2492783260, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2126.98 < 2179.76
  -> Decision False in time 1.1800000000, query time of that 1.1657530890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0367083250, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3597422440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
973.472 < 1003.25
  -> Decision False in time 0.4800000000, query time of that 0.4755279920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1098.69 < 1171.83
  -> Decision False in time 0.0400000000, query time of that 0.0375761750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1549.69 < 1606.34
  -> Decision False in time 0.0400000000, query time of that 0.0378233500, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1192.67 < 1223.19
  -> Decision False in time 0.0800000000, query time of that 0.0403584400, 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 18.109999999999673
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0824850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0118196840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1666.48 < 1718.66
  -> Decision False in time 0.0500000000, query time of that 0.0423620170, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1231.53 < 1266.66
  -> Decision False in time 0.0300000000, query time of that 0.0358903490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1071.25 < 1092.16
  -> Decision False in time 0.0200000000, query time of that 0.0114845660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1290.52 < 1325.4
  -> Decision False in time 0.0300000000, query time of that 0.0277931390, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1368.28 < 1391.4
  -> Decision False in time 0.0100000000, query time of that 0.0109376360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1559.77 < 1593.8
  -> Decision False in time 0.0100000000, query time of that 0.0120838600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
946.545 < 974.168
  -> Decision False in time 0.0200000000, query time of that 0.0127348020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1005.55 < 1009.14
  -> Decision False in time 0.0100000000, query time of that 0.0116950540, 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 33.76000000000022
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1526654570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5500000000, query time of that 1.5350664730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2000000000, query time of that 15.1355909270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1482546880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5500000000, query time of that 1.5387087930, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.5200000000, query time of that 15.4466459130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.1667497400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7200000000, query time of that 1.6123252170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
888.746 < 927.074
  -> Decision False in time 7.6100000000, query time of that 7.5610579020, 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 33.60999999999967
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0136101710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
974.868 < 991.338
  -> Decision False in time 0.0300000000, query time of that 0.0359130330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1347.3 < 1350.94
  -> Decision False in time 0.1100000000, query time of that 0.1111946010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
663.948 < 667.385
  -> Decision False in time 0.0200000000, query time of that 0.0159761650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1142.43 < 1189.44
  -> Decision False in time 0.0200000000, query time of that 0.0219605490, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1500.27 < 1566.02
  -> Decision False in time 0.0500000000, query time of that 0.0486550960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1306.54 < 1343.05
  -> Decision False in time 0.0200000000, query time of that 0.0155714050, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
872.488 < 941.975
  -> Decision False in time 0.0200000000, query time of that 0.0168178710, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1227.04 < 1227.98
  -> Decision False in time 0.0200000000, query time of that 0.0168933090, 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 17.94000000000051
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1724018060, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6800000000, query time of that 1.6736973360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.5400000000, query time of that 16.4771568240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1674483140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6800000000, query time of that 1.6593755880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1457.05 < 1528.68
  -> Decision False in time 15.9700000000, query time of that 15.9149689490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1758939020, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8900000000, query time of that 1.7562929640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 17.9400000000, query time of that 17.5147662390, 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 33.350000000000364
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0268924550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2530063250, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1638.45 < 1650.72
  -> Decision False in time 1.2700000000, query time of that 1.2558752620, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0288832530, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1611.52 < 1662.96
  -> Decision False in time 0.2400000000, query time of that 0.2348119530, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1226.25 < 1237.06
  -> Decision False in time 0.5700000000, query time of that 0.5626936440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0315136370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1707.5 < 1722.86
  -> Decision False in time 0.2800000000, query time of that 0.1277571630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
811.841 < 811.962
  -> Decision False in time 0.0300000000, query time of that 0.0286177940, 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 65.23000000000047
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0838630080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8401841400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.3900000000, query time of that 8.3293504530, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0859904050, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.9000000000, query time of that 0.8771659010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1910.2 < 2032.26
  -> Decision False in time 2.0000000000, query time of that 1.9894740240, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.0998951820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 1.0210370260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1671.89 < 1716.85
  -> Decision False in time 0.0800000000, query time of that 0.0837810000, 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 33.64000000000033
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5442011760, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.4200000000, query time of that 5.4033802230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 54.1000000000, query time of that 54.0095431760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5543842430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.4400000000, query time of that 5.4177629510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.6300000000, query time of that 53.5334860550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.5499044220, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.4200000000, query time of that 5.3355657830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 54.0800000000, query time of that 53.6741858410, 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 18.170000000000073
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3158477720, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1900000000, query time of that 3.1769656710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.5000000000, query time of that 31.4171158180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3192933660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1800000000, query time of that 3.1577410230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.4000000000, query time of that 31.3121521620, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3198170300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.2900000000, query time of that 3.1698050540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.5000000000, query time of that 32.1924598210, 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 18.01000000000022
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0114561570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0988178620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1275.84 < 1278.7
  -> Decision False in time 0.1300000000, query time of that 0.1214031180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1180.86 < 1196.4
  -> Decision False in time 0.0100000000, query time of that 0.0110116550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
903.303 < 951.829
  -> Decision False in time 0.0300000000, query time of that 0.0240882490, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1190.39 < 1275.98
  -> Decision False in time 0.0300000000, query time of that 0.0295661890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
976.185 < 1014.42
  -> Decision False in time 0.0100000000, query time of that 0.0121896950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1598.49 < 1599.03
  -> Decision False in time 0.0200000000, query time of that 0.0119765650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1694.9 < 1743.86
  -> Decision False in time 0.0300000000, query time of that 0.0121392710, 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 33.8700000000008
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0794743040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7840103380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8400000000, query time of that 7.7832751200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0792441110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8216299970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1900000000, query time of that 8.0954029500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1417.13 < 1433.16
  -> Decision False in time 0.0900000000, query time of that 0.0867523920, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1600000000, query time of that 0.9712968880, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1503.35 < 1505.35
  -> Decision False in time 0.8500000000, query time of that 0.8307782860, 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 33.88999999999942
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0383792710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3616028970, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
877.881 < 951.063
  -> Decision False in time 3.3800000000, query time of that 3.3402981050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0405874570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4200000000, query time of that 0.3978894510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1322.67 < 1330.88
  -> Decision False in time 0.2300000000, query time of that 0.2235076790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0440393030, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0200000000, query time of that 0.5031714570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1381.72 < 1395.71
  -> Decision False in time 0.7900000000, query time of that 0.4467858500, 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 64.89999999999964
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5103018580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9800000000, query time of that 4.9723917210, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.1400000000, query time of that 49.0569984800, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4891481170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.0000000000, query time of that 4.9810593450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.2700000000, query time of that 49.1726506360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.4951738340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.1300000000, query time of that 4.9878227630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 50.2400000000, query time of that 49.9364990890, 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 33.659999999999854
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0142972880, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1435.19 < 1457.22
  -> Decision False in time 0.0900000000, query time of that 0.0853419320, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1186.26 < 1192.6
  -> Decision False in time 0.0700000000, query time of that 0.0744183970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1291.93 < 1308
  -> Decision False in time 0.0200000000, query time of that 0.0140708310, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1548.02 < 1680.85
  -> Decision False in time 0.0200000000, query time of that 0.0228660440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
973.24 < 1040.92
  -> Decision False in time 0.0500000000, query time of that 0.0487530310, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1308.55 < 1335.64
  -> Decision False in time 0.0200000000, query time of that 0.0152519170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1194.74 < 1196.66
  -> Decision False in time 0.0200000000, query time of that 0.0163752650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1102.76 < 1213.17
  -> Decision False in time 0.0100000000, query time of that 0.0157658270, 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 17.960000000000946
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0119383333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0234291450, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2225993590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1561.55 < 1575.54
  -> Decision False in time 1.0200000000, query time of that 1.0033525830, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0249761110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1072.5 < 1123.13
  -> Decision False in time 0.0900000000, query time of that 0.0897907340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
953.095 < 980.722
  -> Decision False in time 0.1500000000, query time of that 0.1524612820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1500.89 < 1506.15
  -> Decision False in time 0.0300000000, query time of that 0.0235336240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1125.44 < 1137.8
  -> Decision False in time 0.1600000000, query time of that 0.0587380030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1143.99 < 1147.7
  -> Decision False in time 0.1600000000, query time of that 0.0541316590, 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 65.06000000000131
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0193766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0288821900, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2718663560, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1544.76 < 1554.43
  -> Decision False in time 0.8400000000, query time of that 0.8292507570, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0313037610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1061.94 < 1118.67
  -> Decision False in time 0.0400000000, query time of that 0.0316400640, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2008.28 < 2018.24
  -> Decision False in time 0.1300000000, query time of that 0.1347188820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0353218270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1050.3 < 1084.28
  -> Decision False in time 0.0800000000, query time of that 0.0349586700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1264.69 < 1269.56
  -> Decision False in time 0.1200000000, query time of that 0.0669169990, 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 65.01999999999862
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1553634980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5315155000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.3100000000, query time of that 15.2379068040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1532299940, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5700000000, query time of that 1.5332126700, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.5800000000, query time of that 15.5055619170, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1627824210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7800000000, query time of that 1.6353214380, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1332.89 < 1338.14
  -> Decision False in time 2.5000000000, query time of that 2.4901053100, 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 33.42000000000007
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0217203680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1389.83 < 1393.98
  -> Decision False in time 0.1700000000, query time of that 0.1646060020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
892.515 < 908.113
  -> Decision False in time 1.3200000000, query time of that 1.2993021070, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0222198280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
846.522 < 894.053
  -> Decision False in time 0.1800000000, query time of that 0.1787777920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1863.41 < 1919.23
  -> Decision False in time 0.1300000000, query time of that 0.1248738360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1403.89 < 1484.16
  -> Decision False in time 0.0200000000, query time of that 0.0208944840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1899.3 < 2062.23
  -> Decision False in time 0.0600000000, query time of that 0.0243789680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
752.865 < 770.833
  -> Decision False in time 0.0300000000, query time of that 0.0262592560, 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 65.63999999999942
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0206415050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
857.206 < 867.123
  -> Decision False in time 0.1800000000, query time of that 0.1802054290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1261.42 < 1285.91
  -> Decision False in time 0.6600000000, query time of that 0.6470628290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1063.49 < 1068.64
  -> Decision False in time 0.0300000000, query time of that 0.0188287800, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1264.26 < 1283.59
  -> Decision False in time 0.0400000000, query time of that 0.0443891850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1321.41 < 1330.08
  -> Decision False in time 0.1800000000, query time of that 0.1747677580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1022.85 < 1048.2
  -> Decision False in time 0.0300000000, query time of that 0.0243845810, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1589.52 < 1603.05
  -> Decision False in time 0.0200000000, query time of that 0.0237769710, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1207.83 < 1239.48
  -> Decision False in time 0.0300000000, query time of that 0.0217216920, 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 33.80999999999949
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0150041300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1292652660, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1329.49 < 1346.56
  -> Decision False in time 0.0300000000, query time of that 0.0241159350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1298.26 < 1325.52
  -> Decision False in time 0.0100000000, query time of that 0.0137989320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1088.25 < 1205.73
  -> Decision False in time 0.0300000000, query time of that 0.0243940080, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
895.979 < 921.396
  -> Decision False in time 0.0100000000, query time of that 0.0134227320, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1749.49 < 1811.16
  -> Decision False in time 0.0200000000, query time of that 0.0138321370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
958.089 < 1045.95
  -> Decision False in time 0.0200000000, query time of that 0.0159407630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
928.574 < 959.536
  -> Decision False in time 0.0200000000, query time of that 0.0159412700, 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 18.139999999999418
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0490246590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4995770370, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1883.2 < 1894.67
  -> Decision False in time 1.5700000000, query time of that 1.5601868860, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0515627220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5221627750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 5.4000000000, query time of that 5.2816516720, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0613149640, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1509.48 < 1510.12
  -> Decision False in time 0.2800000000, query time of that 0.2139311280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
731.489 < 774.176
  -> Decision False in time 0.6500000000, query time of that 0.4608216610, 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 18.18000000000029
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Reject!
1227.74 < 1252.13
  -> Decision False in time 0.0400000000, query time of that 0.0363251370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3417041050, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.3600000000, query time of that 3.3229793570, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0369299960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1564.67 < 1576.22
  -> Decision False in time 0.2600000000, query time of that 0.2599644990, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1208.76 < 1234
  -> Decision False in time 1.2400000000, query time of that 1.2139896300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0381614160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1611.45 < 1621.11
  -> Decision False in time 0.2000000000, query time of that 0.1059830060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1136.14 < 1188.27
  -> Decision False in time 0.7400000000, query time of that 0.3878767700, 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 18.18000000000029
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0174167630, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1685875190, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1448.85 < 1477.82
  -> Decision False in time 0.8200000000, query time of that 0.7983930030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0183738430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1025.38 < 1031.94
  -> Decision False in time 0.1000000000, query time of that 0.0936293650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1491.7 < 1511.28
  -> Decision False in time 0.0400000000, query time of that 0.0400085700, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1326.75 < 1393.81
  -> Decision False in time 0.0200000000, query time of that 0.0199251860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
992.3 < 1070.01
  -> Decision False in time 0.0200000000, query time of that 0.0201749230, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1189.77 < 1450.01
  -> Decision False in time 0.0400000000, query time of that 0.0193875470, 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 65.20000000000073
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0440055300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4335166740, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3400000000, query time of that 4.2895337760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0461139230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4728520340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1945.82 < 1965.78
  -> Decision False in time 0.6000000000, query time of that 0.5919412300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0530667980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
836.779 < 871.103
  -> Decision False in time 0.0700000000, query time of that 0.0544284650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1714.89 < 1778.08
  -> Decision False in time 0.3800000000, query time of that 0.2778283870, with c1=5.0000000000, c2=0.1000000000
