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, 100000]), 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, 400000]), 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, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), 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', 200, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 40000]), 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, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 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, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]), 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, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 100000])
Got a train set of size (60000 * 784)
Built index in 18.34
Index size:  304616.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2651100320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.4200000000, query time of that 2.4027654570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 23.2900000000, query time of that 23.1907894310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2407583600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.3400000000, query time of that 2.3165115540, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1994.27 < 2012.7
  -> Decision False in time 2.7700000000, query time of that 2.7649654150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.2504266210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.5200000000, query time of that 2.3994004570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.9100000000, query time of that 24.4175421570, 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 65.78999999999996
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2029999700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0500000000, query time of that 2.0444620360, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.8400000000, query time of that 19.7478420400, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2028165390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0100000000, query time of that 1.9898587820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.0600000000, query time of that 19.9409774510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.1974894900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2500000000, query time of that 2.1208642450, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.6600000000, query time of that 21.2539827550, 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 34.1400000000001
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7600000000, query time of that 0.7491000270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.8600000000, query time of that 6.8503359990, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 69.1100000000, query time of that 68.9886064230, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.7040856080, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.9500000000, query time of that 6.9295539510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 69.1400000000, query time of that 68.9952858460, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.6953284430, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.0500000000, query time of that 6.9638951180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 69.5900000000, query time of that 69.3333001210, 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 34.029999999999745
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0117494280, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1499.89 < 1529.3
  -> Decision False in time 0.0200000000, query time of that 0.0171511950, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1444.95 < 1555.08
  -> Decision False in time 0.0900000000, query time of that 0.0814767630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0137807030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1429.07 < 1488.96
  -> Decision False in time 0.0100000000, query time of that 0.0117042020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1552.09 < 1616.06
  -> Decision False in time 0.0100000000, query time of that 0.0120466640, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1680.55 < 1715.52
  -> Decision False in time 0.0300000000, query time of that 0.0133268090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1584.83 < 1584.92
  -> Decision False in time 0.0100000000, query time of that 0.0130162090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1755.68 < 1803.97
  -> Decision False in time 0.0200000000, query time of that 0.0133269700, 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 89.23999999999978
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Reject!
1597.12 < 1621.07
  -> Decision False in time 0.0200000000, query time of that 0.0228381110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2049.58 < 2070.1
  -> Decision False in time 0.1300000000, query time of that 0.1235254740, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2063.89 < 2078.54
  -> Decision False in time 0.0500000000, query time of that 0.0455509650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0207593570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1704.41 < 1799.78
  -> Decision False in time 0.0800000000, query time of that 0.0811968190, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1530.96 < 1610.45
  -> Decision False in time 0.0500000000, query time of that 0.0514159080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1538.63 < 1575.95
  -> Decision False in time 0.0300000000, query time of that 0.0230379830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1512.48 < 1544.11
  -> Decision False in time 0.0200000000, query time of that 0.0232680050, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1304.8 < 1309.22
  -> Decision False in time 0.0600000000, query time of that 0.0255724510, 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 18.140000000000327
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 0.0266666230, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2653175680, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1806.13 < 1881.17
  -> Decision False in time 1.7300000000, query time of that 1.6965158040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0284746550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1825.47 < 1891.61
  -> Decision False in time 0.1600000000, query time of that 0.1599010500, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1385.67 < 1414.28
  -> Decision False in time 0.0700000000, query time of that 0.0693698920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0306277480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1519.8 < 1559.79
  -> Decision False in time 0.0800000000, query time of that 0.0325094800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1426.03 < 1447.94
  -> Decision False in time 0.2000000000, query time of that 0.0884314740, 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 18.149999999999636
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Reject!
1487.4 < 1588.39
  -> Decision False in time 0.0100000000, query time of that 0.0102858640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1929.22 < 1932.33
  -> Decision False in time 0.0600000000, query time of that 0.0524605150, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1837.28 < 1864.06
  -> Decision False in time 0.0600000000, query time of that 0.0628484980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1457.96 < 1482.3
  -> Decision False in time 0.0100000000, query time of that 0.0094395930, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1011.46 < 1097.15
  -> Decision False in time 0.0100000000, query time of that 0.0091108400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1392.47 < 1408.98
  -> Decision False in time 0.0100000000, query time of that 0.0101339500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1437.47 < 1511.75
  -> Decision False in time 0.0200000000, query time of that 0.0098099490, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1795.62 < 1845.53
  -> Decision False in time 0.0100000000, query time of that 0.0111623750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1676.86 < 1713.62
  -> Decision False in time 0.0100000000, query time of that 0.0100514460, 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 18.169999999999163
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Reject!
1275.73 < 1380.61
  -> Decision False in time 0.0100000000, query time of that 0.0107322270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0916378820, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1674.72 < 1730.48
  -> Decision False in time 0.0300000000, query time of that 0.0255085030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0111769540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1048.45 < 1099.85
  -> Decision False in time 0.0300000000, query time of that 0.0238899780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1527.55 < 1629.27
  -> Decision False in time 0.0100000000, query time of that 0.0105350020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1666.13 < 1733.89
  -> Decision False in time 0.0100000000, query time of that 0.0104704950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
824.208 < 889.85
  -> Decision False in time 0.0200000000, query time of that 0.0116009300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1740.02 < 1778.8
  -> Decision False in time 0.0100000000, query time of that 0.0113591010, 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 65.60000000000036
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 0.0277955250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2487732750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1710.84 < 1756.06
  -> Decision False in time 0.3900000000, query time of that 0.3804045970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0281442170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1557.92 < 1639.1
  -> Decision False in time 0.0900000000, query time of that 0.0810724460, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1729.36 < 1753.83
  -> Decision False in time 0.2300000000, query time of that 0.2333543490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0335625390, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1521.87 < 1588.52
  -> Decision False in time 0.0600000000, query time of that 0.0346349980, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1301.46 < 1558.32
  -> Decision False in time 0.2200000000, query time of that 0.1067962060, 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 33.970000000000255
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0311663930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2777909200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1810.5 < 1989.31
  -> Decision False in time 1.6300000000, query time of that 1.6036296770, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0319579230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3146300220, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1691.93 < 1721.77
  -> Decision False in time 0.3100000000, query time of that 0.2993841860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1535.99 < 1622.61
  -> Decision False in time 0.0800000000, query time of that 0.0377648200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1678.53 < 1802.77
  -> Decision False in time 0.3100000000, query time of that 0.1470236750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1945.41 < 1988.2
  -> Decision False in time 0.1200000000, query time of that 0.0664691970, 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 33.95000000000073
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0227288300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2072905140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1669.01 < 1683.18
  -> Decision False in time 0.3800000000, query time of that 0.3680597280, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0230266340, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2370697510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1914.48 < 1949.46
  -> Decision False in time 0.1900000000, query time of that 0.1818148860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2286.02 < 2332.34
  -> Decision False in time 0.0200000000, query time of that 0.0241207750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1486.27 < 1500.26
  -> Decision False in time 0.1200000000, query time of that 0.0505491240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1644.58 < 1652.51
  -> Decision False in time 0.0200000000, query time of that 0.0260956380, 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 65.89999999999964
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0515262550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4868018060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9500000000, query time of that 4.8856315370, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0549715920, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5336378530, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2004.22 < 2042.59
  -> Decision False in time 3.3700000000, query time of that 3.3293957340, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0629705360, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1476.02 < 1510.01
  -> Decision False in time 0.0600000000, query time of that 0.0594834040, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1831.07 < 1890.17
  -> Decision False in time 1.0800000000, query time of that 0.8119016640, 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 18.25
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 0.0681290360, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6943100210, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1532.05 < 1535.01
  -> Decision False in time 3.0300000000, query time of that 2.9960340000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0725934800, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7090176970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1449.96 < 1562.97
  -> Decision False in time 0.7000000000, query time of that 0.6837038100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0910720650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1900000000, query time of that 0.9143012930, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1944.03 < 1945.41
  -> Decision False in time 0.8100000000, query time of that 0.7366297890, 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 65.22999999999956
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Reject!
1420.85 < 1575.17
  -> Decision False in time 0.0200000000, query time of that 0.0174552020, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1394.78 < 1442.25
  -> Decision False in time 0.0400000000, query time of that 0.0452936190, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1591.88 < 1650.03
  -> Decision False in time 0.0400000000, query time of that 0.0356702170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1246.19 < 1318.67
  -> Decision False in time 0.0200000000, query time of that 0.0163193700, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1576.3 < 1662.06
  -> Decision False in time 0.0300000000, query time of that 0.0287107180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1119.47 < 1154.88
  -> Decision False in time 0.0100000000, query time of that 0.0146775950, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1688.1 < 1708.91
  -> Decision False in time 0.0200000000, query time of that 0.0155842880, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1342.44 < 1450.61
  -> Decision False in time 0.0200000000, query time of that 0.0170396900, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1396.9 < 1425.35
  -> Decision False in time 0.0200000000, query time of that 0.0176385820, 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 65.25
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0748778780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7173438240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.1300000000, query time of that 7.0625683230, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0811690500, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7600000000, query time of that 0.7436955780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.6700000000, query time of that 7.5191968820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.0876473960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1800000000, query time of that 0.9706491200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1333.49 < 1442.33
  -> Decision False in time 5.7500000000, query time of that 5.4562112390, 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 18.11999999999989
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 0.0198592570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1817.97 < 1847.45
  -> Decision False in time 0.1400000000, query time of that 0.1289237140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1364.25 < 1394.7
  -> Decision False in time 0.3200000000, query time of that 0.3166438140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1888.08 < 1896.32
  -> Decision False in time 0.0200000000, query time of that 0.0212944220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1867.02 < 1870.64
  -> Decision False in time 0.1400000000, query time of that 0.1359943830, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1728.42 < 1739.35
  -> Decision False in time 0.1300000000, query time of that 0.1239900190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2064.01 < 2086.49
  -> Decision False in time 0.0300000000, query time of that 0.0240596230, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1360.73 < 1486.72
  -> Decision False in time 0.1500000000, query time of that 0.0510813420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1733.55 < 1750.66
  -> Decision False in time 0.1700000000, query time of that 0.0558011980, 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 33.92999999999938
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 0.1057702860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0800000000, query time of that 1.0699047810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.5400000000, query time of that 10.4638281250, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1125824090, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.0964637970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1980.66 < 1983.44
  -> Decision False in time 8.9400000000, query time of that 8.8744723840, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1208400260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1758.7 < 1782.01
  -> Decision False in time 0.1500000000, query time of that 0.1515680630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1379.68 < 1384.45
  -> Decision False in time 9.2400000000, query time of that 9.1623270000, 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 18.140000000000327
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1104744660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1300000000, query time of that 1.1176144580, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 11.0500000000, query time of that 10.9702899510, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.1003459250, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.0923213350, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.1800000000, query time of that 11.0581896650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1228768820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4300000000, query time of that 1.2969787620, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1604.08 < 1612.81
  -> Decision False in time 2.5400000000, query time of that 2.5206810240, 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 18.150000000000546
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 0.0095532040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1517.33 < 1517.38
  -> Decision False in time 0.0600000000, query time of that 0.0562000780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1695.12 < 1714.82
  -> Decision False in time 0.0100000000, query time of that 0.0125585720, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1612.17 < 1654.65
  -> Decision False in time 0.0100000000, query time of that 0.0092077040, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1591.58 < 1705.36
  -> Decision False in time 0.0100000000, query time of that 0.0097479400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1091.77 < 1279.79
  -> Decision False in time 0.0200000000, query time of that 0.0147908060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1482.74 < 1521.97
  -> Decision False in time 0.0100000000, query time of that 0.0104096040, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1659.43 < 1728.69
  -> Decision False in time 0.0200000000, query time of that 0.0104990100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1252 < 1298.06
  -> Decision False in time 0.0100000000, query time of that 0.0101150020, 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 65.38000000000011
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0325346940, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3176480480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1472.99 < 1491.53
  -> Decision False in time 2.7100000000, query time of that 2.6806855820, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0327640990, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1945.28 < 1981.96
  -> Decision False in time 0.2400000000, query time of that 0.2375782870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1842.49 < 1851.86
  -> Decision False in time 0.4600000000, query time of that 0.4502734380, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0431368260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1597.86 < 1636.37
  -> Decision False in time 0.0700000000, query time of that 0.0435048920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1633.62 < 1666.91
  -> Decision False in time 0.0900000000, query time of that 0.0417914330, 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 18.199999999999818
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 0.4365363070, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.2500000000, query time of that 4.2407753540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.7300000000, query time of that 42.6226322560, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4349657110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.3200000000, query time of that 4.3114736570, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.2700000000, query time of that 42.1530229350, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.4427417200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.4600000000, query time of that 4.3618875850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.8500000000, query time of that 43.5321273330, 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 34.22999999999956
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4100000000, query time of that 0.4105223510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.6700000000, query time of that 3.6614749590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 37.0500000000, query time of that 36.9539038210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3776889750, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.7200000000, query time of that 3.6980409000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.8700000000, query time of that 36.7606271370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.3819464510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.9900000000, query time of that 3.7584776560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 38.0400000000, query time of that 37.8042940170, 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 65.60000000000036
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Reject!
1435.82 < 1525.13
  -> Decision False in time 0.0200000000, query time of that 0.0171375800, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1478.22 < 1484.7
  -> Decision False in time 0.0600000000, query time of that 0.0589570730, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1276.26 < 1336.88
  -> Decision False in time 0.1800000000, query time of that 0.1745186970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
606.791 < 610.308
  -> Decision False in time 0.0200000000, query time of that 0.0178083130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1401.84 < 1442.59
  -> Decision False in time 0.0300000000, query time of that 0.0307447500, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1116.05 < 1372.91
  -> Decision False in time 0.0600000000, query time of that 0.0566018290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1385.68 < 1399.93
  -> Decision False in time 0.0200000000, query time of that 0.0173324240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1874.25 < 1927.43
  -> Decision False in time 0.0200000000, query time of that 0.0179418410, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1594.6 < 1695.4
  -> Decision False in time 0.0200000000, query time of that 0.0184877580, 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 34.10999999999876
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0137257260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1106111720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1548.8 < 1582.73
  -> Decision False in time 0.0300000000, query time of that 0.0278697170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1208.27 < 1234.62
  -> Decision False in time 0.0200000000, query time of that 0.0118897410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1824.15 < 1894.95
  -> Decision False in time 0.0100000000, query time of that 0.0119345480, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1301.41 < 1310.35
  -> Decision False in time 0.0200000000, query time of that 0.0179888250, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1797.42 < 1807
  -> Decision False in time 0.0100000000, query time of that 0.0122490470, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
976.632 < 993.49
  -> Decision False in time 0.0100000000, query time of that 0.0122451420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1587.44 < 1638.46
  -> Decision False in time 0.0200000000, query time of that 0.0117150810, 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 66.29000000000087
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0166340840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1473495100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1507.4 < 1659.98
  -> Decision False in time 0.0600000000, query time of that 0.0549046090, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1231.03 < 1231.51
  -> Decision False in time 0.0200000000, query time of that 0.0147984240, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1226 < 1330.75
  -> Decision False in time 0.0200000000, query time of that 0.0256133780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1375.08 < 1432.03
  -> Decision False in time 0.0300000000, query time of that 0.0292688800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1448.87 < 1630.89
  -> Decision False in time 0.0200000000, query time of that 0.0179382730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1441.81 < 1555.38
  -> Decision False in time 0.0300000000, query time of that 0.0214421480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1986.86 < 2006.84
  -> Decision False in time 0.0300000000, query time of that 0.0232040660, 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 35.210000000000946
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0753038040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6805684220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.6900000000, query time of that 6.6102492200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0720825820, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6847538890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1668.73 < 1682.47
  -> Decision False in time 3.5700000000, query time of that 3.5439225560, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0771833690, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1200000000, query time of that 0.7380634130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1432.17 < 1511.47
  -> Decision False in time 0.2100000000, query time of that 0.1663489310, 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 65.40999999999985
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 0.3534536770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4300000000, query time of that 3.4232514980, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.9500000000, query time of that 33.8450017210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3493071160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.4300000000, query time of that 3.4111228440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 34.1500000000, query time of that 34.0443656970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.3693579320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.5300000000, query time of that 3.4510712620, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.9300000000, query time of that 34.6118920050, 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 18.159999999999854
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0139961050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1692.71 < 1711.5
  -> Decision False in time 0.1000000000, query time of that 0.0971090950, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1877.66 < 1887.37
  -> Decision False in time 0.1300000000, query time of that 0.1251188790, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0154747430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1742.51 < 1866.4
  -> Decision False in time 0.0500000000, query time of that 0.0478529420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1435.63 < 1520.49
  -> Decision False in time 0.0700000000, query time of that 0.0699066380, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1569.35 < 1608.84
  -> Decision False in time 0.0200000000, query time of that 0.0146884170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1228.04 < 1252.28
  -> Decision False in time 0.0200000000, query time of that 0.0172176380, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1519.29 < 1522.64
  -> Decision False in time 0.0100000000, query time of that 0.0165867520, 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 65.61999999999898
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1058905920, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0870127330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.7900000000, query time of that 10.7127896310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1122962120, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.0947412400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.0500000000, query time of that 10.9491970270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1317325600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4400000000, query time of that 1.2932944180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1805.98 < 1885.74
  -> Decision False in time 0.7500000000, query time of that 0.7485734590, 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 34.11000000000058
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0490411520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4475269220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4800000000, query time of that 4.4188924540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0499451410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1394.1 < 1452.07
  -> Decision False in time 0.3800000000, query time of that 0.3703445790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1918.92 < 1927.5
  -> Decision False in time 0.9300000000, query time of that 0.9181473870, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1209.82 < 1313.31
  -> Decision False in time 0.0700000000, query time of that 0.0546509510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1200000000, query time of that 0.6498365590, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1713.7 < 1728.99
  -> Decision False in time 0.0600000000, query time of that 0.0579501420, 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 34.13000000000102
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 0.0182625910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1423.32 < 1559.57
  -> Decision False in time 0.1600000000, query time of that 0.1539998740, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1350.05 < 1469.95
  -> Decision False in time 0.4900000000, query time of that 0.4704833880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1651.2 < 1933.65
  -> Decision False in time 0.0200000000, query time of that 0.0188385530, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2198.08 < 2203.27
  -> Decision False in time 0.0300000000, query time of that 0.0283252560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1719.97 < 1800.37
  -> Decision False in time 0.0200000000, query time of that 0.0162260970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1472.35 < 1574.15
  -> Decision False in time 0.0200000000, query time of that 0.0190833940, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1114.91 < 1128.27
  -> Decision False in time 0.0200000000, query time of that 0.0192148160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
899.901 < 1017.33
  -> Decision False in time 0.0600000000, query time of that 0.0195009030, 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 18.270000000000437
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 0.0469454980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4364469480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4100000000, query time of that 4.3439430560, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0437487060, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4800000000, query time of that 0.4652673780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1379.88 < 1388.23
  -> Decision False in time 0.2800000000, query time of that 0.2738467900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0514074630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0200000000, query time of that 0.5905711740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1747.69 < 1802.08
  -> Decision False in time 0.5500000000, query time of that 0.3631597700, 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 40.8700000000008
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2050860080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0500000000, query time of that 2.0466793480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.6200000000, query time of that 20.5252814700, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2059971860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0700000000, query time of that 2.0541810250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.9400000000, query time of that 20.8188783400, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2214809380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2700000000, query time of that 2.0985745480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.3900000000, query time of that 20.9011963100, 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 65.73999999999978
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6100000000, query time of that 0.6148738060, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.2500000000, query time of that 6.2373572880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 62.2000000000, query time of that 62.0755047240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6233873700, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.2000000000, query time of that 6.1823267940, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 61.9500000000, query time of that 61.8229011100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6265398400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.3800000000, query time of that 6.2823834650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 62.4600000000, query time of that 62.2150471550, 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 41.31000000000131
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0139442960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1415.93 < 1473.63
  -> Decision False in time 0.0300000000, query time of that 0.0328719460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1708.96 < 2081.76
  -> Decision False in time 0.0500000000, query time of that 0.0393517420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1649.27 < 1797.4
  -> Decision False in time 0.0100000000, query time of that 0.0114802590, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1486.81 < 1489.57
  -> Decision False in time 0.0300000000, query time of that 0.0319840740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1837.63 < 1882.8
  -> Decision False in time 0.0400000000, query time of that 0.0385728490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1013.9 < 1079.04
  -> Decision False in time 0.0200000000, query time of that 0.0121038090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1193.48 < 1280.76
  -> Decision False in time 0.0100000000, query time of that 0.0127972090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1242.11 < 1291.4
  -> Decision False in time 0.0300000000, query time of that 0.0121764970, 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 18.31000000000131
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7815177960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.7400000000, query time of that 7.7209667030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 77.3300000000, query time of that 77.2078513470, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.7808728090, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.7000000000, query time of that 7.6825542920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 75.8100000000, query time of that 75.6697029100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8700000000, query time of that 0.7939762760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.9300000000, query time of that 7.7895170550, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 78.1000000000, query time of that 77.5611938410, with c1=5.0000000000, c2=0.1000000000
