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, 10000]), 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', 100, 20000]), 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, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]), 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', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), 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, 400]), 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, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]), 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, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]), 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, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 40000]), 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', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 10000])
Got a train set of size (60000 * 784)
Built index in 34.38
Index size:  396464.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0405409670, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3845139220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.7400000000, query time of that 3.6883729890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0395915610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1461.52 < 1497.62
  -> Decision False in time 0.1400000000, query time of that 0.1375546130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1472.43 < 1485.9
  -> Decision False in time 0.4600000000, query time of that 0.4506872380, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1477.01 < 1488.1
  -> Decision False in time 0.0500000000, query time of that 0.0463475080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1063.54 < 1090.24
  -> Decision False in time 0.1000000000, query time of that 0.0616622240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
853.858 < 882.562
  -> Decision False in time 0.1700000000, query time of that 0.0962665620, 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 33.72
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0264819380, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2542913840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
966.504 < 1004.8
  -> Decision False in time 0.9800000000, query time of that 0.9643862650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1139.92 < 1142.29
  -> Decision False in time 0.0300000000, query time of that 0.0266049050, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1215.61 < 1227.74
  -> Decision False in time 0.2100000000, query time of that 0.2020278990, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1140.97 < 1193.96
  -> Decision False in time 0.0300000000, query time of that 0.0335490940, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1175.84 < 1220.52
  -> Decision False in time 0.0800000000, query time of that 0.0286450350, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1199.42 < 1200.31
  -> Decision False in time 0.0400000000, query time of that 0.0333581680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1418.52 < 1482.45
  -> Decision False in time 0.3300000000, query time of that 0.1427465800, 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 18.02000000000004
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Reject!
1914.97 < 1987.97
  -> Decision False in time 0.0500000000, query time of that 0.0533455250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4900096720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9800000000, query time of that 4.9236568660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0518597100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5240539340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1211.93 < 1263.61
  -> Decision False in time 3.4600000000, query time of that 3.4281356350, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0572761500, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1573.36 < 1664.27
  -> Decision False in time 0.1600000000, query time of that 0.1225457110, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1676.6 < 1848.18
  -> Decision False in time 0.2500000000, query time of that 0.1883784990, 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 65.10999999999996
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 0.2762092750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6600000000, query time of that 2.6441385720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.4000000000, query time of that 26.3361858770, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2662102960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6500000000, query time of that 2.6285730070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.5600000000, query time of that 26.4814178710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2778649270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8600000000, query time of that 2.6978025360, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1403.22 < 1433.31
  -> Decision False in time 20.3500000000, query time of that 20.2742104990, 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 18.049999999999955
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1729393310, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.7000000000, query time of that 1.6846223690, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.6400000000, query time of that 16.5753264050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1741904030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.7100000000, query time of that 1.6923548180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.7200000000, query time of that 16.6005813130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1793559560, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9300000000, query time of that 1.7559861250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1905.28 < 2049.33
  -> Decision False in time 16.1400000000, query time of that 16.0533695000, 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 18.029999999999745
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 0.0113650790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1217.04 < 1230.95
  -> Decision False in time 0.0700000000, query time of that 0.0677762750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
929.485 < 950.579
  -> Decision False in time 0.0500000000, query time of that 0.0451642160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0114561360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
841.696 < 852.25
  -> Decision False in time 0.0300000000, query time of that 0.0204958680, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1541.98 < 1559.3
  -> Decision False in time 0.0200000000, query time of that 0.0182533180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2340.53 < 2351.66
  -> Decision False in time 0.0100000000, query time of that 0.0115988160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1407 < 1412.02
  -> Decision False in time 0.0200000000, query time of that 0.0115881280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1066.27 < 1074.25
  -> Decision False in time 0.0200000000, query time of that 0.0130586950, 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 33.7800000000002
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5800000000, query time of that 0.5749129410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.4100000000, query time of that 5.3972362720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.6400000000, query time of that 53.5536227130, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5422473090, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3300000000, query time of that 5.3145808000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.5200000000, query time of that 53.4246232050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6000000000, query time of that 0.5263293720, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.5000000000, query time of that 5.3316673910, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 54.4700000000, query time of that 54.1053406790, 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 65.15999999999985
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 0.5108392080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9600000000, query time of that 4.9453298670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.3900000000, query time of that 49.3073895970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4942302770, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9500000000, query time of that 4.9317570830, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.6400000000, query time of that 49.5463099280, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5075677380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.0700000000, query time of that 4.9847431700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 50.4300000000, query time of that 50.0699512850, 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 65.48000000000047
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 0.0322731610, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3183461270, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.1800000000, query time of that 3.1378660890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1120.89 < 1158.23
  -> Decision False in time 0.0300000000, query time of that 0.0333721510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3537964740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
983.176 < 1014.9
  -> Decision False in time 0.6100000000, query time of that 0.5995936800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0398328210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1532.22 < 1534.9
  -> Decision False in time 0.1300000000, query time of that 0.0857595540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1045.37 < 1072.24
  -> Decision False in time 0.2200000000, query time of that 0.1204813720, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 200])
Got a train set of size (60000 * 784)
Built index in 66.21000000000004
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 0.0220650950, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1317.57 < 1361.25
  -> Decision False in time 0.0700000000, query time of that 0.0708397890, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1078.39 < 1143.73
  -> Decision False in time 0.0400000000, query time of that 0.0332813560, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0222362890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1598.64 < 1609.43
  -> Decision False in time 0.0700000000, query time of that 0.0752171970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1366.04 < 1451.51
  -> Decision False in time 0.0700000000, query time of that 0.0600881080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1170.1 < 1173.76
  -> Decision False in time 0.0300000000, query time of that 0.0254757510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
937.621 < 976.873
  -> Decision False in time 0.0200000000, query time of that 0.0244536380, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
803.075 < 864.197
  -> Decision False in time 0.0300000000, query time of that 0.0248376890, 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 18.099999999999454
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 0.3191837340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1600000000, query time of that 3.1499051500, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.6800000000, query time of that 31.6058819020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3200294210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1600000000, query time of that 3.1429508150, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.3100000000, query time of that 31.2185414270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3171755370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.3200000000, query time of that 3.1931733730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.1800000000, query time of that 31.9532493720, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200])
Got a train set of size (60000 * 784)
Built index in 34.14000000000033
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 0.0149148850, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1329618290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1302.22 < 1319.88
  -> Decision False in time 0.0200000000, query time of that 0.0229367060, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1947.08 < 1964.68
  -> Decision False in time 0.0200000000, query time of that 0.0151116030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1239.31 < 1389.85
  -> Decision False in time 0.0300000000, query time of that 0.0307740170, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
917.396 < 923.886
  -> Decision False in time 0.0300000000, query time of that 0.0245738400, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
827.551 < 838.573
  -> Decision False in time 0.0100000000, query time of that 0.0153938720, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1621.22 < 1738.68
  -> Decision False in time 0.0200000000, query time of that 0.0163192690, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1105.97 < 1134.18
  -> Decision False in time 0.0400000000, query time of that 0.0158974130, 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 66.11000000000058
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1629396780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5332711800, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.1500000000, query time of that 15.0803013290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1660999660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5600000000, query time of that 1.5476993090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.6600000000, query time of that 15.5301510040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1627770320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7900000000, query time of that 1.6640749170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1260.23 < 1329.2
  -> Decision False in time 4.0300000000, query time of that 4.0067873390, 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 65.09999999999854
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0253825070, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2287298240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2039.15 < 2082.87
  -> Decision False in time 0.2100000000, query time of that 0.1970312380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0260963560, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
961.924 < 1379
  -> Decision False in time 0.1400000000, query time of that 0.1375047940, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1389.85 < 1448.48
  -> Decision False in time 0.1200000000, query time of that 0.1116351910, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0286565110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1041.86 < 1240.53
  -> Decision False in time 0.0500000000, query time of that 0.0318326550, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1671.32 < 1695.06
  -> Decision False in time 0.0300000000, query time of that 0.0249719830, 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 65.1299999999992
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0202438500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1939995570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1775.16 < 1893.86
  -> Decision False in time 0.3200000000, query time of that 0.3146917490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1090.49 < 1090.93
  -> Decision False in time 0.0200000000, query time of that 0.0209542950, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
951.318 < 966.148
  -> Decision False in time 0.0400000000, query time of that 0.0402945250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
882.278 < 940.96
  -> Decision False in time 0.0300000000, query time of that 0.0257962820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
959.272 < 999.885
  -> Decision False in time 0.0200000000, query time of that 0.0211094750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
833.919 < 851.87
  -> Decision False in time 0.0200000000, query time of that 0.0236257800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1250.41 < 1263.93
  -> Decision False in time 0.0200000000, query time of that 0.0240715150, 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 18.05999999999949
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 0.0113329460, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
617.162 < 689.238
  -> Decision False in time 0.0500000000, query time of that 0.0478548280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
714.878 < 775.663
  -> Decision False in time 0.0200000000, query time of that 0.0189343510, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0113214350, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
989.197 < 1002.66
  -> Decision False in time 0.0100000000, query time of that 0.0119502180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1255.52 < 1262.92
  -> Decision False in time 0.0300000000, query time of that 0.0279038640, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1153.26 < 1240.95
  -> Decision False in time 0.0200000000, query time of that 0.0116169220, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1467.89 < 1583.53
  -> Decision False in time 0.0100000000, query time of that 0.0119424200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
979.419 < 1144.67
  -> Decision False in time 0.0100000000, query time of that 0.0118739990, 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:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0369354180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3335453640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.3800000000, query time of that 3.3165267810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0358283600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3561909210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
813.462 < 849.192
  -> Decision False in time 0.3700000000, query time of that 0.3634257870, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0400808570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1659.44 < 1724.99
  -> Decision False in time 0.1400000000, query time of that 0.0846341690, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1781.33 < 1836.31
  -> Decision False in time 0.2200000000, query time of that 0.1273303960, 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 65.29999999999927
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 0.0622539940, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5836592280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.8800000000, query time of that 5.8255602550, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0642001520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6217533810, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1693.38 < 1781.27
  -> Decision False in time 0.3800000000, query time of that 0.3752676000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0658751590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1742.81 < 1766.83
  -> Decision False in time 0.3800000000, query time of that 0.3235824380, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1582.13 < 1873.74
  -> Decision False in time 0.7100000000, query time of that 0.5920818190, 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 33.82999999999993
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 0.2839342160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.8000000000, query time of that 2.7883589280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.9900000000, query time of that 27.9195226060, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2902351030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.8000000000, query time of that 2.7761284650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 27.9400000000, query time of that 27.8583281440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.2967586450, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.0300000000, query time of that 2.8856031870, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 29.0300000000, query time of that 28.6223237050, 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 0.1600000000, query time of that 0.1584326550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5231159860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2400000000, query time of that 15.1790607420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1577352640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5229737600, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.4000000000, query time of that 15.3050248270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.1511525540, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8000000000, query time of that 1.6020518890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
933.215 < 1193.7
  -> Decision False in time 4.2000000000, query time of that 4.1776928440, 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 18.020000000000437
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 0.0117070630, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2016.3 < 2016.95
  -> Decision False in time 0.0300000000, query time of that 0.0302320590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1781.71 < 1790.17
  -> Decision False in time 0.1300000000, query time of that 0.1175861460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0114917900, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1398 < 1432.26
  -> Decision False in time 0.0100000000, query time of that 0.0118652900, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1626.72 < 1706.59
  -> Decision False in time 0.0300000000, query time of that 0.0289626150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
771.715 < 788.54
  -> Decision False in time 0.0300000000, query time of that 0.0121267890, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1115.44 < 1145.2
  -> Decision False in time 0.0100000000, query time of that 0.0122565010, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1625.22 < 1713.74
  -> Decision False in time 0.0100000000, query time of that 0.0126183840, 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 33.899999999999636
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0218261840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.2004653330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2026.58 < 2039.07
  -> Decision False in time 0.4700000000, query time of that 0.4559577450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0220773750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2321070650, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1301.71 < 1330.27
  -> Decision False in time 0.0600000000, query time of that 0.0614869770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0231783520, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1100.61 < 1132.68
  -> Decision False in time 0.0300000000, query time of that 0.0273088870, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1351.68 < 1488.29
  -> Decision False in time 0.0200000000, query time of that 0.0241411110, 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 18.01000000000022
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0119383333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0241103860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1138.01 < 1176.05
  -> Decision False in time 0.1300000000, query time of that 0.1313752350, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1400.14 < 1432.77
  -> Decision False in time 0.1600000000, query time of that 0.1529130120, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0245964850, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1124.59 < 1147.96
  -> Decision False in time 0.1300000000, query time of that 0.1230938960, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
805.145 < 845.789
  -> Decision False in time 0.0500000000, query time of that 0.0532727790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0255310220, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
857.921 < 896.625
  -> Decision False in time 0.2600000000, query time of that 0.0927263350, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1254.41 < 1324.16
  -> Decision False in time 0.1300000000, query time of that 0.0554920880, 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 65.11999999999898
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 0.0190965690, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
840.176 < 1162.06
  -> Decision False in time 0.1200000000, query time of that 0.1142925230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1750.31 < 1799.48
  -> Decision False in time 0.1400000000, query time of that 0.1451599550, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1327.01 < 1366.56
  -> Decision False in time 0.0300000000, query time of that 0.0204447440, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
854.434 < 866.668
  -> Decision False in time 0.1100000000, query time of that 0.1097054370, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1713.4 < 2188.94
  -> Decision False in time 0.0200000000, query time of that 0.0203581430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1279.38 < 1287.24
  -> Decision False in time 0.0200000000, query time of that 0.0218770480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1847.43 < 1903.91
  -> Decision False in time 0.0300000000, query time of that 0.0233031520, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1441.82 < 1583.51
  -> Decision False in time 0.0200000000, query time of that 0.0224506700, 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 65.17000000000007
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 0.0456883840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4405708690, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3300000000, query time of that 4.2847519060, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0483468180, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.4735580110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1630.87 < 1646.19
  -> Decision False in time 3.4200000000, query time of that 3.3858807630, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0510758130, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1211.09 < 1229.16
  -> Decision False in time 0.1600000000, query time of that 0.1127804760, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1694.91 < 2093.35
  -> Decision False in time 0.3000000000, query time of that 0.2060850440, 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 33.75
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 0.0140063650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1543.58 < 1599.11
  -> Decision False in time 0.0900000000, query time of that 0.0892070090, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1190.44 < 1200.91
  -> Decision False in time 0.0800000000, query time of that 0.0791443610, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0147230980, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1395.95 < 1412.98
  -> Decision False in time 0.0900000000, query time of that 0.0846259310, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1006.02 < 1011.57
  -> Decision False in time 0.0200000000, query time of that 0.0210691490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1049.03 < 1074.12
  -> Decision False in time 0.0300000000, query time of that 0.0153781020, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1015.45 < 1026.69
  -> Decision False in time 0.1100000000, query time of that 0.0306387320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1804.91 < 1815.83
  -> Decision False in time 0.0100000000, query time of that 0.0150865770, 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 33.75
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 0.0824017520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8100000000, query time of that 0.7968445150, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8100000000, query time of that 7.7488484440, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0791909750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8300000000, query time of that 0.8065098940, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1613.11 < 1628.49
  -> Decision False in time 3.8200000000, query time of that 3.7999929190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0905423140, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1268.76 < 1279.23
  -> Decision False in time 0.5100000000, query time of that 0.5075880150, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1715.27 < 1722.24
  -> Decision False in time 0.1200000000, query time of that 0.1155442910, 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 33.80999999999949
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 0.0537870610, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5300000000, query time of that 0.5179052130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1500000000, query time of that 5.1016651260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0555198370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5800000000, query time of that 0.5497031100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2005.7 < 2171.67
  -> Decision False in time 3.1700000000, query time of that 3.1440169690, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0586014290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1034.28 < 1223.94
  -> Decision False in time 0.2500000000, query time of that 0.1963419990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1190.54 < 1192.11
  -> Decision False in time 4.3100000000, query time of that 3.2602206100, 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 18.0
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0006000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0741188340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7881113670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.9000000000, query time of that 7.8440481940, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0786700230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8181203840, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.2100000000, query time of that 8.1083412780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0934733820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1346.63 < 1366.75
  -> Decision False in time 1.0600000000, query time of that 0.9534327920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1387.45 < 1496.03
  -> Decision False in time 1.6000000000, query time of that 1.5589438930, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 2000])
Got a train set of size (60000 * 784)
Built index in 18.090000000000146
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Reject!
1540.72 < 1544.78
  -> Decision False in time 0.0200000000, query time of that 0.0184452520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1701356600, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
879.107 < 959.309
  -> Decision False in time 0.3500000000, query time of that 0.3381460910, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0191370170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1425.63 < 1437.97
  -> Decision False in time 0.0800000000, query time of that 0.0859769660, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1222.49 < 1236
  -> Decision False in time 0.0500000000, query time of that 0.0491529100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1276.55 < 1337.51
  -> Decision False in time 0.0400000000, query time of that 0.0200334200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
932.366 < 996.175
  -> Decision False in time 0.0500000000, query time of that 0.0211519250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1168.61 < 1234.55
  -> Decision False in time 0.2800000000, query time of that 0.0830547420, 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 18.030000000000655
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.6131859290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.9600000000, query time of that 5.9514267060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 59.9100000000, query time of that 59.8174271730, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.6182150600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.9500000000, query time of that 5.9320474840, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.6200000000, query time of that 59.5134418200, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.5968498280, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.1500000000, query time of that 6.0621176130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 60.7000000000, query time of that 60.5217154050, 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 18.209999999999127
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 0.0143378730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1346262640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
735.027 < 950.537
  -> Decision False in time 0.2400000000, query time of that 0.2307345080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0154647030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1635.45 < 1648.93
  -> Decision False in time 0.0800000000, query time of that 0.0717356660, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1496.69 < 1548.93
  -> Decision False in time 0.0400000000, query time of that 0.0367979510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1164.26 < 1164.41
  -> Decision False in time 0.0100000000, query time of that 0.0152273490, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1495.72 < 1511.8
  -> Decision False in time 0.0400000000, query time of that 0.0162301480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
820.514 < 869.946
  -> Decision False in time 0.1100000000, query time of that 0.0330379250, 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 65.47999999999956
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 0.0271438990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2661895760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1789.64 < 2018.99
  -> Decision False in time 0.0800000000, query time of that 0.0771512330, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0299556750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
986.824 < 1019.79
  -> Decision False in time 0.2000000000, query time of that 0.2035169400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1522.6 < 1738.04
  -> Decision False in time 0.0800000000, query time of that 0.0783001270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1257.38 < 1265.91
  -> Decision False in time 0.0300000000, query time of that 0.0307936960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2026.32 < 2087.12
  -> Decision False in time 0.0900000000, query time of that 0.0421419360, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1465.75 < 1523.65
  -> Decision False in time 0.1700000000, query time of that 0.0785544340, 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 65.32999999999993
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 0.0811987710, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8390080060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.3600000000, query time of that 8.2995653390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0849369630, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.9100000000, query time of that 0.8812066120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.7400000000, query time of that 8.6580202450, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0966996950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 1.0131325500, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1474.74 < 1515.23
  -> Decision False in time 4.0400000000, query time of that 4.0020679800, 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 33.970000000001164
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 0.0144827070, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1063.45 < 1078.12
  -> Decision False in time 0.0200000000, query time of that 0.0205356630, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1347.93 < 1360.06
  -> Decision False in time 0.1400000000, query time of that 0.1407382020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
946.128 < 947.168
  -> Decision False in time 0.0200000000, query time of that 0.0138973430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1845.1 < 1893.96
  -> Decision False in time 0.0600000000, query time of that 0.0564965560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1353.52 < 1379.33
  -> Decision False in time 0.0300000000, query time of that 0.0369100980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
956.988 < 962.36
  -> Decision False in time 0.0700000000, query time of that 0.0160883790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2246.67 < 2318.27
  -> Decision False in time 0.1000000000, query time of that 0.0313943760, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1023.53 < 1043.29
  -> Decision False in time 0.0200000000, query time of that 0.0164027230, 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 33.89000000000124
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0385416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0176381290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1641575670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1842.77 < 1885.54
  -> Decision False in time 0.1700000000, query time of that 0.1709406240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0187277440, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1230.75 < 1256.08
  -> Decision False in time 0.0800000000, query time of that 0.0756941100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1270.27 < 1282.28
  -> Decision False in time 0.1000000000, query time of that 0.1038133140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1482.89 < 1523.68
  -> Decision False in time 0.0300000000, query time of that 0.0212184160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1337.42 < 1501.91
  -> Decision False in time 0.0300000000, query time of that 0.0218812670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
963.726 < 1047.75
  -> Decision False in time 0.0900000000, query time of that 0.0292550840, with c1=5.0000000000, c2=0.1000000000
