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, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 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', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]), 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, 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', 200, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), 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, 2000]), 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, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), 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, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 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', 200, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]), 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, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 1000])
Got a train set of size (60000 * 784)
Built index in 18.03
Index size:  304616.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0165367530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1662.24 < 1683.17
  -> Decision False in time 0.0400000000, query time of that 0.0387757650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1868.38 < 2061.73
  -> Decision False in time 0.1000000000, query time of that 0.0957007720, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1305.83 < 1316.61
  -> Decision False in time 0.0200000000, query time of that 0.0103301400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1849.19 < 1929.58
  -> Decision False in time 0.0700000000, query time of that 0.0675804770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1539.78 < 1670.33
  -> Decision False in time 0.0200000000, query time of that 0.0205593530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1436.41 < 1461.05
  -> Decision False in time 0.0200000000, query time of that 0.0163928820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1188.33 < 1219.38
  -> Decision False in time 0.0200000000, query time of that 0.0154314600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1196.4 < 1315.86
  -> Decision False in time 0.0500000000, query time of that 0.0163082820, 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 33.519999999999996
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Reject!
1472.88 < 1584.92
  -> Decision False in time 0.0100000000, query time of that 0.0123335440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1103.19 < 1133.34
  -> Decision False in time 0.0600000000, query time of that 0.0583208520, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1177.16 < 1228.05
  -> Decision False in time 0.0200000000, query time of that 0.0186171720, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1533.32 < 1550.2
  -> Decision False in time 0.0100000000, query time of that 0.0115085280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1448.44 < 1477.8
  -> Decision False in time 0.0200000000, query time of that 0.0175258800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1909.61 < 1954.9
  -> Decision False in time 0.0100000000, query time of that 0.0120424790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1191.7 < 1372.72
  -> Decision False in time 0.0200000000, query time of that 0.0125376660, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1360.29 < 1405.46
  -> Decision False in time 0.0200000000, query time of that 0.0129648820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1066.96 < 1101.98
  -> Decision False in time 0.0200000000, query time of that 0.0143363540, 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 64.78
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6500000000, query time of that 0.6470401370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.2300000000, query time of that 6.2155132340, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.9500000000, query time of that 61.8685274530, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6235780710, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.2400000000, query time of that 6.2211190680, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 61.1300000000, query time of that 61.0300696660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6023648580, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.2700000000, query time of that 6.1771462540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 61.5100000000, query time of that 61.3086274630, 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 65.0300000000002
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0164420300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1473907510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1533.43 < 1635.12
  -> Decision False in time 0.1000000000, query time of that 0.1025448140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1277.62 < 1301.92
  -> Decision False in time 0.0200000000, query time of that 0.0162957670, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1388.78 < 1408.3
  -> Decision False in time 0.0700000000, query time of that 0.0659633180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1650.2 < 1718.64
  -> Decision False in time 0.0600000000, query time of that 0.0565788450, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1190.41 < 1270.39
  -> Decision False in time 0.0200000000, query time of that 0.0192457910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1569.66 < 1574.97
  -> Decision False in time 0.0100000000, query time of that 0.0158637190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1702.25 < 1717.67
  -> Decision False in time 0.0200000000, query time of that 0.0177195990, 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 33.69999999999982
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0121644790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1818.44 < 1927.38
  -> Decision False in time 0.1100000000, query time of that 0.1040553010, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1812.47 < 1952.32
  -> Decision False in time 0.0300000000, query time of that 0.0306029690, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0120021750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1149.86 < 1266.66
  -> Decision False in time 0.0200000000, query time of that 0.0133903750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1215.36 < 1254.93
  -> Decision False in time 0.0200000000, query time of that 0.0209118990, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1543.01 < 1719.5
  -> Decision False in time 0.0100000000, query time of that 0.0140366290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
909.037 < 945.429
  -> Decision False in time 0.0200000000, query time of that 0.0131885610, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1135.07 < 1141.37
  -> Decision False in time 0.0100000000, query time of that 0.0117759920, 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 64.82999999999993
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3608839530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4000000000, query time of that 3.3865079460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.6300000000, query time of that 33.5491485000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3118746590, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.3800000000, query time of that 3.3605799720, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 33.6100000000, query time of that 33.5242987180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4200000000, query time of that 0.3450706200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.5300000000, query time of that 3.4120138440, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.6600000000, query time of that 34.1910793970, 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 33.75
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.2023781290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0700000000, query time of that 2.0614244630, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.4800000000, query time of that 20.4013258470, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2132594960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0500000000, query time of that 2.0274087060, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.6900000000, query time of that 20.5780593720, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2088326580, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3500000000, query time of that 2.2079585260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 22.0600000000, query time of that 21.4521480870, 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 18.110000000000582
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7631295770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.5600000000, query time of that 7.5457658010, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 75.8500000000, query time of that 75.7625714270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7881907650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.7000000000, query time of that 7.6863914140, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 76.4800000000, query time of that 76.3722044250, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8700000000, query time of that 0.7895965460, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.8900000000, query time of that 7.7684201260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.3700000000, query time of that 77.1260597480, 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 18.109999999999673
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4373641880, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.2800000000, query time of that 4.2687300790, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.3600000000, query time of that 42.2717169860, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4373669360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.2000000000, query time of that 4.1807784870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.7700000000, query time of that 42.6703484270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4215900950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.4300000000, query time of that 4.3049646560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.5500000000, query time of that 43.3540200830, 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 33.590000000000146
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1067158500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0400000000, query time of that 1.0399514550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.5200000000, query time of that 10.4497689640, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0980906810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1000000000, query time of that 1.0809199770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1623.38 < 1643.31
  -> Decision False in time 5.1500000000, query time of that 5.1228593410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1200643960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4000000000, query time of that 1.2396798380, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1678.75 < 1695.78
  -> Decision False in time 11.9100000000, query time of that 11.8112131990, 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 33.86000000000058
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0162177760, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1557.14 < 1573.45
  -> Decision False in time 0.0900000000, query time of that 0.0954175460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1454.42 < 1494.76
  -> Decision False in time 0.0800000000, query time of that 0.0693493960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0168904520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1518.4 < 1545.52
  -> Decision False in time 0.0900000000, query time of that 0.0858801240, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1752.01 < 1784.7
  -> Decision False in time 0.0400000000, query time of that 0.0406841590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0177152120, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1279.15 < 1393.95
  -> Decision False in time 0.0200000000, query time of that 0.0178694470, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1942.05 < 1953.2
  -> Decision False in time 0.0200000000, query time of that 0.0188123260, 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 65.03999999999905
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0201160000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1971233640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2154.21 < 2340.5
  -> Decision False in time 0.2700000000, query time of that 0.2560710140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0215597790, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1805.68 < 1830.93
  -> Decision False in time 0.0600000000, query time of that 0.0510956930, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1634.49 < 1676.66
  -> Decision False in time 0.0200000000, query time of that 0.0206783110, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1212.6 < 1347.1
  -> Decision False in time 0.0200000000, query time of that 0.0230442400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1297.72 < 1325.03
  -> Decision False in time 0.0300000000, query time of that 0.0232643320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1519.31 < 1585.56
  -> Decision False in time 0.0400000000, query time of that 0.0247548870, 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 33.73999999999978
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3793736140, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.7800000000, query time of that 3.7679651420, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.7800000000, query time of that 36.7000324100, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3675026050, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.6700000000, query time of that 3.6535237830, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.4800000000, query time of that 36.3931221980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4700000000, query time of that 0.3875743080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.8400000000, query time of that 3.7508953520, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 37.8600000000, query time of that 37.4142192730, 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 18.18999999999869
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0273977790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2571732020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1045.13 < 1048.35
  -> Decision False in time 1.7200000000, query time of that 1.6922535690, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0275631350, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1225.12 < 1258.27
  -> Decision False in time 0.1800000000, query time of that 0.1775785130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1750.43 < 1766.8
  -> Decision False in time 0.2500000000, query time of that 0.2459505500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1387.56 < 1454.99
  -> Decision False in time 0.0300000000, query time of that 0.0266760930, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1539.83 < 1583.92
  -> Decision False in time 0.2000000000, query time of that 0.0928226730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1136.91 < 1153.5
  -> Decision False in time 0.0300000000, query time of that 0.0261668640, 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 65.46999999999935
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0172116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0265308410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2439689670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1342.02 < 1392.81
  -> Decision False in time 1.1900000000, query time of that 1.1695435380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1834.22 < 1866.79
  -> Decision False in time 0.0200000000, query time of that 0.0259165490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1936.27 < 1938.21
  -> Decision False in time 0.2000000000, query time of that 0.1895919630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1544.81 < 1602.77
  -> Decision False in time 0.1200000000, query time of that 0.1247735390, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0310448970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1566.88 < 1578.92
  -> Decision False in time 0.0700000000, query time of that 0.0300498020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1917.49 < 2110.74
  -> Decision False in time 0.0400000000, query time of that 0.0327109710, 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 18.090000000000146
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0101242600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1729.23 < 2002.87
  -> Decision False in time 0.0300000000, query time of that 0.0235325430, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1259.93 < 1516.28
  -> Decision False in time 0.0300000000, query time of that 0.0279434110, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1494.94 < 1737.87
  -> Decision False in time 0.0100000000, query time of that 0.0101020150, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1686.71 < 1747.52
  -> Decision False in time 0.0100000000, query time of that 0.0103790020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1709.83 < 1734.88
  -> Decision False in time 0.0100000000, query time of that 0.0097955120, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1620.68 < 1728.96
  -> Decision False in time 0.0100000000, query time of that 0.0092958110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1373.24 < 1392.06
  -> Decision False in time 0.0100000000, query time of that 0.0096754470, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1504.36 < 1518.33
  -> Decision False in time 0.0200000000, query time of that 0.0104713950, 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 65.81999999999971
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1947932980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0400000000, query time of that 2.0356767880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.7400000000, query time of that 19.6634240870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2063770270, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.9900000000, query time of that 1.9829225470, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.7500000000, query time of that 19.6671288440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2034517570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2000000000, query time of that 2.0935499530, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.0600000000, query time of that 20.6409954150, 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 33.73999999999978
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0679153280, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6825950620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.6900000000, query time of that 6.6315316910, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0728910170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6882409070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1540.46 < 1555.46
  -> Decision False in time 5.2300000000, query time of that 5.1784274580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0780545250, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1300000000, query time of that 0.8883918300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1607.77 < 1633.59
  -> Decision False in time 2.3700000000, query time of that 2.1154011040, 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 33.56999999999971
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.7054236130, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.8900000000, query time of that 6.8762985840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 68.9600000000, query time of that 68.8664302470, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6864379020, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.8300000000, query time of that 6.8126378000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 68.1600000000, query time of that 68.0631453600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.6988723580, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.9300000000, query time of that 6.8349532510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 69.4500000000, query time of that 69.0316275630, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 100])
Got a train set of size (60000 * 784)
Built index in 17.93000000000029
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0105934720, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1775.9 < 1789.77
  -> Decision False in time 0.0200000000, query time of that 0.0175427050, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1576.4 < 1646.71
  -> Decision False in time 0.0400000000, query time of that 0.0397768180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0102812490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2085.82 < 2146.77
  -> Decision False in time 0.0200000000, query time of that 0.0224874850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1624.64 < 1673.04
  -> Decision False in time 0.0300000000, query time of that 0.0302104110, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1166.54 < 1298.68
  -> Decision False in time 0.0200000000, query time of that 0.0111145340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1681.12 < 1699.74
  -> Decision False in time 0.0100000000, query time of that 0.0105370780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
860.505 < 916.035
  -> Decision False in time 0.0200000000, query time of that 0.0105721420, 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 18.01000000000022
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0229533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0198269560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1829941900, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1418.57 < 1579.79
  -> Decision False in time 0.4400000000, query time of that 0.4299438980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0207135890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1339.13 < 1344.67
  -> Decision False in time 0.1300000000, query time of that 0.1204488100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1735.29 < 1740.09
  -> Decision False in time 0.0500000000, query time of that 0.0505025640, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2307.35 < 2401.88
  -> Decision False in time 0.0400000000, query time of that 0.0213511820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1442.77 < 1490.14
  -> Decision False in time 0.0400000000, query time of that 0.0228329850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1646.34 < 1654.11
  -> Decision False in time 0.0300000000, query time of that 0.0232639030, 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 18.020000000000437
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0028783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0446128700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4358312370, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3200000000, query time of that 4.2626888260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0462402450, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4648987510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1854.11 < 1894.77
  -> Decision False in time 2.4800000000, query time of that 2.4471100090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0526226330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1724.18 < 1732.9
  -> Decision False in time 0.4500000000, query time of that 0.3008791300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1745.32 < 1747.81
  -> Decision False in time 2.4700000000, query time of that 1.5635058700, 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 18.030000000000655
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2326712500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.2700000000, query time of that 2.2700499400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 22.8800000000, query time of that 22.7993469950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2325677200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.3100000000, query time of that 2.2920235130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 22.8400000000, query time of that 22.7410809600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.2393663110, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.6000000000, query time of that 2.4585603790, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.0400000000, query time of that 23.7763999300, 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 18.06000000000131
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0671703950, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6700000000, query time of that 0.6586171550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.6900000000, query time of that 6.6260098810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0733099850, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6891435640, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.0200000000, query time of that 6.8992029440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0827233210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1813.65 < 1913.72
  -> Decision False in time 0.6400000000, query time of that 0.5608121120, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1431.15 < 1440.82
  -> Decision False in time 4.2700000000, query time of that 3.8260738400, 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 65.16999999999825
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0167363360, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1602.95 < 1670.28
  -> Decision False in time 0.0800000000, query time of that 0.0725214940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1282.51 < 1328.08
  -> Decision False in time 0.1000000000, query time of that 0.0994293520, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1480.33 < 1482.43
  -> Decision False in time 0.0200000000, query time of that 0.0149790970, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1628.02 < 1645.03
  -> Decision False in time 0.0300000000, query time of that 0.0304262050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1564.17 < 1602.86
  -> Decision False in time 0.0300000000, query time of that 0.0316146000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1490.1 < 1515.62
  -> Decision False in time 0.0200000000, query time of that 0.0184001070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1458.49 < 1503.54
  -> Decision False in time 0.0500000000, query time of that 0.0183767890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1410.94 < 1452.49
  -> Decision False in time 0.0200000000, query time of that 0.0168910690, 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 33.54999999999927
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0125515580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1068410340, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1980.61 < 2071.91
  -> Decision False in time 0.0100000000, query time of that 0.0138290170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1712.43 < 1724.55
  -> Decision False in time 0.0100000000, query time of that 0.0119966570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1307.49 < 1407.47
  -> Decision False in time 0.0400000000, query time of that 0.0323381600, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2215.4 < 2231.74
  -> Decision False in time 0.0200000000, query time of that 0.0162710560, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2069.9 < 2111.86
  -> Decision False in time 0.0100000000, query time of that 0.0126058060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1562.11 < 1584.8
  -> Decision False in time 0.0100000000, query time of that 0.0131871540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1624.52 < 1692.33
  -> Decision False in time 0.0200000000, query time of that 0.0113321600, 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 65.36000000000058
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0343218880, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3226655120, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1914.48 < 1949.46
  -> Decision False in time 2.2500000000, query time of that 2.2242119680, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0365573550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1630.42 < 1709.81
  -> Decision False in time 0.2700000000, query time of that 0.2617866480, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1705.84 < 1756.14
  -> Decision False in time 0.4700000000, query time of that 0.4679569400, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0405121610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1588.94 < 1641.79
  -> Decision False in time 0.0600000000, query time of that 0.0431094590, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1837.91 < 1884.15
  -> Decision False in time 0.2400000000, query time of that 0.1357572650, 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 33.599999999998545
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0504003360, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.4535357130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4400000000, query time of that 4.3997768140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0482591780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4800000000, query time of that 0.4708415710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1646.22 < 1657.36
  -> Decision False in time 1.9400000000, query time of that 1.9177345060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0531144780, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1447.2 < 1530.73
  -> Decision False in time 0.1500000000, query time of that 0.1060776890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1419.54 < 1442.13
  -> Decision False in time 1.5500000000, query time of that 1.0174068710, 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 18.040000000000873
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0104164520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1642.46 < 1689.5
  -> Decision False in time 0.0800000000, query time of that 0.0774875510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1446.6 < 1507.64
  -> Decision False in time 0.0100000000, query time of that 0.0127437240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0100608160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1299.74 < 1339.95
  -> Decision False in time 0.0100000000, query time of that 0.0099225330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1318.71 < 1370.67
  -> Decision False in time 0.0200000000, query time of that 0.0143064990, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1401.88 < 1460.6
  -> Decision False in time 0.0100000000, query time of that 0.0110537930, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1112.29 < 1148.39
  -> Decision False in time 0.0100000000, query time of that 0.0103427280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1445.49 < 1501.02
  -> Decision False in time 0.0100000000, query time of that 0.0096528810, 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 65.18999999999869
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1174831050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1000000000, query time of that 1.0911782330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.5300000000, query time of that 10.4613163260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1112203480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.0973523080, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1666.39 < 1744.21
  -> Decision False in time 2.3200000000, query time of that 2.3040665770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1194924120, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4700000000, query time of that 1.2712466080, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 13.5500000000, query time of that 12.5211620090, 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 65.09000000000015
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0719459930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7400000000, query time of that 0.7283187940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.0100000000, query time of that 6.9467659650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0701117580, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.7062778980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1587.97 < 1636.23
  -> Decision False in time 4.4300000000, query time of that 4.3960588250, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0834036140, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.2000000000, query time of that 0.9576778230, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1590.73 < 1691.51
  -> Decision False in time 3.7700000000, query time of that 3.5730982730, 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 18.049999999999272
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1157447610, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0800000000, query time of that 1.0742372990, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.9500000000, query time of that 10.8852330030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1200568110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1700000000, query time of that 1.1511505820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1711.04 < 1902.52
  -> Decision False in time 7.0300000000, query time of that 6.9965553440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1290029140, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4600000000, query time of that 1.2792148130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2209.79 < 2210.79
  -> Decision False in time 13.2500000000, query time of that 12.6132844250, 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 33.780000000002474
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0284381020, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1768.27 < 1796.09
  -> Decision False in time 0.0900000000, query time of that 0.0871511090, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1668.42 < 1668.65
  -> Decision False in time 1.5300000000, query time of that 1.5091297210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0290885770, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3000816110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1769.74 < 1823.3
  -> Decision False in time 0.4400000000, query time of that 0.4332891130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0332264130, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1490.93 < 1641.86
  -> Decision False in time 0.2000000000, query time of that 0.0972649560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1315.05 < 1666.56
  -> Decision False in time 0.2900000000, query time of that 0.1256112150, 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 64.98999999999796
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0514211690, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4941938280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.8800000000, query time of that 4.8294050030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0516408820, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1550.6 < 1551.48
  -> Decision False in time 0.4600000000, query time of that 0.4539553240, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1414.53 < 1474.01
  -> Decision False in time 1.9200000000, query time of that 1.9035320060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0590661240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1200000000, query time of that 0.6903836730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1533.7 < 1611.23
  -> Decision False in time 0.4700000000, query time of that 0.3319350050, 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 33.79000000000087
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0225391370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2052353940, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1735.73 < 1897.59
  -> Decision False in time 1.0200000000, query time of that 1.0031563660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0231416280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1766.18 < 1786.67
  -> Decision False in time 0.1100000000, query time of that 0.1077186500, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1519.01 < 1542.38
  -> Decision False in time 0.0400000000, query time of that 0.0361193370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1594.36 < 1600.06
  -> Decision False in time 0.0200000000, query time of that 0.0233929150, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1624.5 < 1628.34
  -> Decision False in time 0.2000000000, query time of that 0.0771018740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1298.17 < 1321.17
  -> Decision False in time 0.0300000000, query time of that 0.0233394160, 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 65.11000000000058
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0156777520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1495.82 < 1630.31
  -> Decision False in time 0.0600000000, query time of that 0.0589609880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1790.54 < 1798.55
  -> Decision False in time 0.0400000000, query time of that 0.0366009870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0170414480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1507.78 < 1640.13
  -> Decision False in time 0.0200000000, query time of that 0.0229814180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1138.57 < 1147.64
  -> Decision False in time 0.0400000000, query time of that 0.0384427290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1549.77 < 1587.18
  -> Decision False in time 0.0200000000, query time of that 0.0176050290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1555.25 < 1569.22
  -> Decision False in time 0.0200000000, query time of that 0.0166429930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1455.69 < 1464.31
  -> Decision False in time 0.0200000000, query time of that 0.0158366960, with c1=5.0000000000, c2=0.1000000000
