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, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 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', 200, 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', 100, 400000]), 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, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]), 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, 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, 400]), 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, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]), 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, 4000]), 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, 1000]), 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, 2000]), 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, 20000]), 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, 100]), 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, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), 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, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 200000])
Got a train set of size (60000 * 784)
Built index in 17.96
Index size:  305104.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3294259800, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1900000000, query time of that 3.1772847220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.5600000000, query time of that 31.4754869140, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.3148974190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1900000000, query time of that 3.1692775240, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.4900000000, query time of that 31.3917615660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3209081950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.3400000000, query time of that 3.1954533440, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.7300000000, query time of that 32.1518290710, 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 18.0
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1780115930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6700000000, query time of that 1.6687515460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.5300000000, query time of that 16.4717635870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1618703340, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.7100000000, query time of that 1.6826745020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1267.57 < 1493.41
  -> Decision False in time 8.2900000000, query time of that 8.2646969650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1791261500, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.9100000000, query time of that 1.7836308630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1618.77 < 1619.5
  -> Decision False in time 1.2900000000, query time of that 1.2840892880, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 4000])
Got a train set of size (60000 * 784)
Built index in 17.940000000000055
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0119383333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0231023540, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2199997450, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1545.11 < 1556.77
  -> Decision False in time 1.0200000000, query time of that 0.9977519040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0256482280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1363.14 < 1405.85
  -> Decision False in time 0.2400000000, query time of that 0.2349407900, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1570.19 < 1594.81
  -> Decision False in time 0.5900000000, query time of that 0.5759782500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0265502060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1467.81 < 1482.62
  -> Decision False in time 0.0500000000, query time of that 0.0248407100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1512.68 < 1572.82
  -> Decision False in time 0.0300000000, query time of that 0.0249449880, 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 64.90000000000009
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0193766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0285779270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2653016380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1749.98 < 1820.57
  -> Decision False in time 1.1800000000, query time of that 1.1614214420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0309664400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3106385290, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1330.15 < 1330.81
  -> Decision False in time 0.0300000000, query time of that 0.0340860420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0350221450, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1170.88 < 1261.08
  -> Decision False in time 0.1500000000, query time of that 0.0774037830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1241.54 < 1268.07
  -> Decision False in time 0.0500000000, query time of that 0.0359877770, 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 33.56000000000017
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1549864080, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5191170260, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2100000000, query time of that 15.1479403540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1503257460, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5319530060, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1512.05 < 1599.3
  -> Decision False in time 12.3300000000, query time of that 12.2761419770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.1714516060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8100000000, query time of that 1.6450652080, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 16.7400000000, query time of that 16.3139644220, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 20000])
Got a train set of size (60000 * 784)
Built index in 17.920000000000073
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0524116880, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5001745650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9200000000, query time of that 4.8712243780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0526659420, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5139548070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1125.52 < 1146.9
  -> Decision False in time 2.4900000000, query time of that 2.4614814730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0585544190, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1907.73 < 1925.81
  -> Decision False in time 0.5600000000, query time of that 0.3895539670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1383.81 < 1407.66
  -> Decision False in time 0.1900000000, query time of that 0.1298289560, 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 17.920000000000073
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6286047550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.0200000000, query time of that 6.0068126410, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 60.1000000000, query time of that 60.0038516390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6200000000, query time of that 0.6068609390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.9600000000, query time of that 5.9405549790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.9200000000, query time of that 59.8106089860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6066129100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.1300000000, query time of that 6.0139114500, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 59.9300000000, query time of that 59.7405133630, 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 17.949999999999818
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0107626740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1283.72 < 1345.06
  -> Decision False in time 0.0400000000, query time of that 0.0432318380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1498.99 < 1517.52
  -> Decision False in time 0.0700000000, query time of that 0.0662342820, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2316.71 < 2439.51
  -> Decision False in time 0.0200000000, query time of that 0.0107888200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1500.43 < 1554.77
  -> Decision False in time 0.0200000000, query time of that 0.0180101150, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1251.2 < 1280.12
  -> Decision False in time 0.0200000000, query time of that 0.0209915820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1251.47 < 1264.57
  -> Decision False in time 0.0200000000, query time of that 0.0116423260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1510.65 < 1537.66
  -> Decision False in time 0.0200000000, query time of that 0.0130380890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
939.002 < 955.573
  -> Decision False in time 0.0200000000, query time of that 0.0123796370, 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 64.48000000000047
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0217202260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1891888220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1653.92 < 1733.31
  -> Decision False in time 0.0800000000, query time of that 0.0824544050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
920.824 < 921.21
  -> Decision False in time 0.0200000000, query time of that 0.0178752720, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1101.08 < 1114.19
  -> Decision False in time 0.0300000000, query time of that 0.0286203800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1609.77 < 1619.11
  -> Decision False in time 0.0700000000, query time of that 0.0650003290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
889.39 < 1031.25
  -> Decision False in time 0.0200000000, query time of that 0.0232071530, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1515.76 < 1516.06
  -> Decision False in time 0.0300000000, query time of that 0.0199045970, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1675.69 < 1691.42
  -> Decision False in time 0.0200000000, query time of that 0.0241700400, 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 64.48999999999978
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0462985640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4376236550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3400000000, query time of that 4.2904004220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0470278880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1367.98 < 1462.89
  -> Decision False in time 0.0800000000, query time of that 0.0792369270, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1223.64 < 1225.53
  -> Decision False in time 2.7600000000, query time of that 2.7335194170, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1710.64 < 1744.95
  -> Decision False in time 0.0600000000, query time of that 0.0538526460, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1181.52 < 1220.53
  -> Decision False in time 0.5200000000, query time of that 0.3562277630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1190.69 < 1215.74
  -> Decision False in time 0.0500000000, query time of that 0.0503714190, 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 64.46000000000004
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2628272960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6400000000, query time of that 2.6291401670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.3800000000, query time of that 26.3141341480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2641540550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6400000000, query time of that 2.6299807450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.4800000000, query time of that 26.3964537960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.2763319530, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8100000000, query time of that 2.7254730860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 27.3400000000, query time of that 27.0253934700, 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 18.0
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0360398510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3307109710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.3400000000, query time of that 3.3009468050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0338365280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3525582760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1351.79 < 1369.77
  -> Decision False in time 0.4900000000, query time of that 0.4853014620, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0379698230, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1098.69 < 1149.45
  -> Decision False in time 0.1300000000, query time of that 0.0794436700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1853.7 < 1908.31
  -> Decision False in time 0.8500000000, query time of that 0.4405279870, 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 33.72999999999956
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0148269840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1340829240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1636.95 < 1642.16
  -> Decision False in time 0.2000000000, query time of that 0.1927530560, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1070.08 < 1093.91
  -> Decision False in time 0.0100000000, query time of that 0.0154252500, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1106.76 < 1138.87
  -> Decision False in time 0.0200000000, query time of that 0.0142633720, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1236.44 < 1242.09
  -> Decision False in time 0.0300000000, query time of that 0.0300773220, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1312.65 < 1330.1
  -> Decision False in time 0.0400000000, query time of that 0.0158182270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1376.24 < 1411.22
  -> Decision False in time 0.0300000000, query time of that 0.0166265390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1284.02 < 1325.91
  -> Decision False in time 0.0200000000, query time of that 0.0166999110, 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 65.07999999999993
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0235774900, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2321591140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1807.22 < 1823.59
  -> Decision False in time 0.6100000000, query time of that 0.5970524050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0257574820, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
941.09 < 967.028
  -> Decision False in time 0.2100000000, query time of that 0.2027097770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1027.94 < 1136.83
  -> Decision False in time 0.0600000000, query time of that 0.0608562490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
940.4 < 960.746
  -> Decision False in time 0.0400000000, query time of that 0.0280754840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
959.125 < 960.146
  -> Decision False in time 0.0900000000, query time of that 0.0400792110, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1004.46 < 1033.31
  -> Decision False in time 0.0600000000, query time of that 0.0280994370, 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 17.960000000000036
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0824850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0115495780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1025560590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1002.37 < 1046.36
  -> Decision False in time 0.1100000000, query time of that 0.1023725040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1167.05 < 1191.09
  -> Decision False in time 0.0100000000, query time of that 0.0111739570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1793.39 < 1803.06
  -> Decision False in time 0.0100000000, query time of that 0.0146610870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
977.875 < 1015.91
  -> Decision False in time 0.0400000000, query time of that 0.0301139190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1577.24 < 1621.32
  -> Decision False in time 0.0200000000, query time of that 0.0123421410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
992.3 < 1077.71
  -> Decision False in time 0.0500000000, query time of that 0.0130079330, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1207.4 < 1318.61
  -> Decision False in time 0.0200000000, query time of that 0.0123786580, 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 64.75
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1495244520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5300000000, query time of that 1.5235809500, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.2500000000, query time of that 15.1886789340, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1586457850, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.6100000000, query time of that 1.5669289630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.5600000000, query time of that 15.4831102690, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.1634923060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8100000000, query time of that 1.6431399610, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1083.95 < 1236.63
  -> Decision False in time 1.4000000000, query time of that 1.3848203000, 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 33.529999999999745
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0385416667
  Testing...
|S| = 20
|T| = 283
Reject!
1572.7 < 1595.97
  -> Decision False in time 0.0200000000, query time of that 0.0180215570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1678985660, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1140.02 < 1149.97
  -> Decision False in time 0.1200000000, query time of that 0.1151029180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0192919300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1100.09 < 1132.1
  -> Decision False in time 0.1600000000, query time of that 0.1577854750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1234.34 < 1265.73
  -> Decision False in time 0.0300000000, query time of that 0.0343162800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
920.333 < 1048.72
  -> Decision False in time 0.0200000000, query time of that 0.0183710250, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1208.87 < 1288.65
  -> Decision False in time 0.0200000000, query time of that 0.0200149920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1297.16 < 1322.65
  -> Decision False in time 0.0300000000, query time of that 0.0219670630, 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 18.07000000000062
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0112307270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1263.84 < 1323.87
  -> Decision False in time 0.0300000000, query time of that 0.0258091490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1675.32 < 1683.44
  -> Decision False in time 0.0200000000, query time of that 0.0239318290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1318.34 < 1339.42
  -> Decision False in time 0.0100000000, query time of that 0.0111405720, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1596.43 < 1680.04
  -> Decision False in time 0.0200000000, query time of that 0.0191689590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1606.3 < 1638.91
  -> Decision False in time 0.0700000000, query time of that 0.0644994600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1243.77 < 1282.19
  -> Decision False in time 0.0100000000, query time of that 0.0118209250, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
872.374 < 1042.71
  -> Decision False in time 0.0100000000, query time of that 0.0121608720, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1688.09 < 1697.61
  -> Decision False in time 0.0200000000, query time of that 0.0114086180, 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 33.55999999999949
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0391739680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3665737770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.6300000000, query time of that 3.5954118240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0391803400, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1428.06 < 1460.07
  -> Decision False in time 0.2900000000, query time of that 0.2874603450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
754.225 < 791.829
  -> Decision False in time 0.1300000000, query time of that 0.1261825370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0457572200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
887.445 < 948.449
  -> Decision False in time 0.2300000000, query time of that 0.1418888110, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1310.72 < 1340.44
  -> Decision False in time 0.5500000000, query time of that 0.3157448500, 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 33.539999999999964
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0159143930, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
995.409 < 996.462
  -> Decision False in time 0.0900000000, query time of that 0.0903910760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1247.4 < 1437.78
  -> Decision False in time 0.1300000000, query time of that 0.1248265440, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0142868260, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1303.11 < 1332.02
  -> Decision False in time 0.0300000000, query time of that 0.0211007090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1190.17 < 1256.51
  -> Decision False in time 0.0100000000, query time of that 0.0143204700, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
881.293 < 1056.42
  -> Decision False in time 0.0300000000, query time of that 0.0162307570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1091.63 < 1099.7
  -> Decision False in time 0.0200000000, query time of that 0.0173206580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1452.86 < 1481.82
  -> Decision False in time 0.0200000000, query time of that 0.0154502140, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 4000])
Got a train set of size (60000 * 784)
Built index in 64.98999999999978
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0322621340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3241393590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.2600000000, query time of that 3.2224518880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0375762220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1240.97 < 1271.13
  -> Decision False in time 0.1800000000, query time of that 0.1720100330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1025.73 < 1087.23
  -> Decision False in time 0.1800000000, query time of that 0.1791027440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0420097670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1940.65 < 1941.15
  -> Decision False in time 0.1400000000, query time of that 0.0889582910, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1872.47 < 1885.54
  -> Decision False in time 0.0500000000, query time of that 0.0426961110, 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 33.73999999999887
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0810997090, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7775757040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8100000000, query time of that 7.7447769660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0791815960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8110294610, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1800000000, query time of that 8.0344761510, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0862109640, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
847.323 < 1006.93
  -> Decision False in time 0.6900000000, query time of that 0.6606506510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1387.45 < 1496.03
  -> Decision False in time 3.8900000000, query time of that 3.7856156980, 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 18.040000000000873
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0427616667
  Testing...
|S| = 20
|T| = 283
Reject!
1494.57 < 1515.46
  -> Decision False in time 0.0200000000, query time of that 0.0146007970, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1281.25 < 1305.28
  -> Decision False in time 0.1300000000, query time of that 0.1303404350, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1365.67 < 1409.34
  -> Decision False in time 0.2300000000, query time of that 0.2237303870, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1580.43 < 1581.11
  -> Decision False in time 0.0200000000, query time of that 0.0147143650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2114.42 < 2121.52
  -> Decision False in time 0.0700000000, query time of that 0.0697998310, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1389.47 < 1570.08
  -> Decision False in time 0.0200000000, query time of that 0.0135384710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1698.06 < 1830.71
  -> Decision False in time 0.0200000000, query time of that 0.0166830590, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1552.93 < 1619.22
  -> Decision False in time 0.0100000000, query time of that 0.0154766970, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1477.74 < 1481.5
  -> Decision False in time 0.0200000000, query time of that 0.0161341200, 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 33.600000000000364
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0143942660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1471.04 < 1531.61
  -> Decision False in time 0.0400000000, query time of that 0.0354754960, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1613.96 < 1670.02
  -> Decision False in time 0.0700000000, query time of that 0.0720202900, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0142865300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1444.2 < 1475.52
  -> Decision False in time 0.0700000000, query time of that 0.0657079210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
921.012 < 934.16
  -> Decision False in time 0.0300000000, query time of that 0.0254477610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1103.58 < 1128.29
  -> Decision False in time 0.0100000000, query time of that 0.0133293600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
983.145 < 988.155
  -> Decision False in time 0.0200000000, query time of that 0.0164217360, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
758.411 < 780.794
  -> Decision False in time 0.0200000000, query time of that 0.0167200340, 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 18.0
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0175981570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1692000000, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 1.7100000000, query time of that 1.6673715380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0179974110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1824.18 < 1872.88
  -> Decision False in time 0.2000000000, query time of that 0.1901528530, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1211.06 < 1227.98
  -> Decision False in time 0.0500000000, query time of that 0.0411855120, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1038.31 < 1062.61
  -> Decision False in time 0.0200000000, query time of that 0.0202439490, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2154.7 < 2244.8
  -> Decision False in time 0.0300000000, query time of that 0.0209642030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
834.632 < 905.635
  -> Decision False in time 0.0200000000, query time of that 0.0205131340, 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 33.600000000000364
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2868642340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.7800000000, query time of that 2.7713909840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.9900000000, query time of that 27.9227398980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2918375470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.7900000000, query time of that 2.7786054630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 27.9600000000, query time of that 27.8723172850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.2873573420, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.9600000000, query time of that 2.8372794700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 29.0200000000, query time of that 28.6077601100, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 20000])
Got a train set of size (60000 * 784)
Built index in 64.76000000000022
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0627829510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5844205390, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.8500000000, query time of that 5.7891221060, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0633195510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6188713330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
955.328 < 1001.15
  -> Decision False in time 1.0100000000, query time of that 0.9985604530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0704803900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1372.47 < 1400.24
  -> Decision False in time 0.6800000000, query time of that 0.5505222860, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1336.82 < 1339.03
  -> Decision False in time 0.1100000000, query time of that 0.1012501650, 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 33.469999999999345
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0215261750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1992855880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1204.14 < 1217.37
  -> Decision False in time 0.4900000000, query time of that 0.4751162500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0215278020, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1462.86 < 1467.08
  -> Decision False in time 0.0800000000, query time of that 0.0744776090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1045.68 < 1087.08
  -> Decision False in time 0.0600000000, query time of that 0.0620013050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
888.365 < 961.953
  -> Decision False in time 0.0200000000, query time of that 0.0240546270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1467.39 < 1499.98
  -> Decision False in time 0.1200000000, query time of that 0.0518355630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1467.53 < 1487.7
  -> Decision False in time 0.0300000000, query time of that 0.0244850200, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100])
Got a train set of size (60000 * 784)
Built index in 64.65999999999985
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0194719520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1921401480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1374.96 < 1390.11
  -> Decision False in time 0.1000000000, query time of that 0.0905530560, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1775.5 < 1806.88
  -> Decision False in time 0.0200000000, query time of that 0.0187552790, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1255.62 < 1276.57
  -> Decision False in time 0.0200000000, query time of that 0.0195019740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1109.69 < 1137.92
  -> Decision False in time 0.0200000000, query time of that 0.0243749440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2020.96 < 2106.23
  -> Decision False in time 0.0700000000, query time of that 0.0224496090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1297.4 < 1335.66
  -> Decision False in time 0.0200000000, query time of that 0.0215041020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1016.27 < 1088.37
  -> Decision False in time 0.0300000000, query time of that 0.0234852180, 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 64.67999999999847
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5193664490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.0300000000, query time of that 5.0220850110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.3800000000, query time of that 49.2899965710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5087799580, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.8900000000, query time of that 4.8775515330, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 48.9800000000, query time of that 48.8816548580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5045096720, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.0500000000, query time of that 4.9676075300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 49.9800000000, query time of that 49.5787176090, 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 33.530000000000655
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0255867010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1055.64 < 1122.91
  -> Decision False in time 0.0900000000, query time of that 0.0889258850, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1405.42 < 1432.52
  -> Decision False in time 0.3300000000, query time of that 0.3213733010, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0261752190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1402.63 < 1416.37
  -> Decision False in time 0.0300000000, query time of that 0.0333632110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1347.94 < 1358.43
  -> Decision False in time 0.0500000000, query time of that 0.0476159900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0293508960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
819.525 < 830.41
  -> Decision False in time 0.2100000000, query time of that 0.0955994300, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1405.65 < 1409.18
  -> Decision False in time 0.0300000000, query time of that 0.0299653820, 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 65.04000000000087
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0819206300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8400000000, query time of that 0.8356715300, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1399.22 < 1416.25
  -> Decision False in time 5.3000000000, query time of that 5.2659707800, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0841637550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8900000000, query time of that 0.8743002110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
945.299 < 982.03
  -> Decision False in time 3.2900000000, query time of that 3.2644229710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1015356100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 1.0220380460, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1809.51 < 1823.88
  -> Decision False in time 5.2900000000, query time of that 5.2297210810, 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 65.13999999999942
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0214620220, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
914.55 < 977.574
  -> Decision False in time 0.0800000000, query time of that 0.0798432020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
978.198 < 1016.48
  -> Decision False in time 0.0500000000, query time of that 0.0503505160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0220636860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
989.644 < 1023.72
  -> Decision False in time 0.0400000000, query time of that 0.0350775070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1152.2 < 1172.14
  -> Decision False in time 0.0400000000, query time of that 0.0481447990, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
806.707 < 823.491
  -> Decision False in time 0.0200000000, query time of that 0.0235166910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1113.2 < 1114.25
  -> Decision False in time 0.0300000000, query time of that 0.0231924910, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1077.35 < 1124.79
  -> Decision False in time 0.0200000000, query time of that 0.0246706400, 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 33.82000000000153
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0555183420, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5275551290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1700000000, query time of that 5.1114456650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0559932520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5494331610, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1582.69 < 1603.5
  -> Decision False in time 1.0100000000, query time of that 1.0029228080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0601547290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2152.83 < 2201.01
  -> Decision False in time 0.2600000000, query time of that 0.1987832830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1410.46 < 1512.06
  -> Decision False in time 0.3100000000, query time of that 0.2322234530, 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 33.79000000000087
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5582371610, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.3800000000, query time of that 5.3724753220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.6600000000, query time of that 53.5598889070, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5423129300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.3900000000, query time of that 5.3710375400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.8200000000, query time of that 53.7181268130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.5599999700, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.5200000000, query time of that 5.4270374690, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 54.3700000000, query time of that 54.0527532560, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 40000])
Got a train set of size (60000 * 784)
Built index in 17.8799999999992
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0006000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0851429960, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7841074110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.8600000000, query time of that 7.7900182110, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0847959950, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8300000000, query time of that 0.8134582910, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1100000000, query time of that 8.0267887980, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.0951509910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.2600000000, query time of that 0.9857987750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1926.57 < 1934.06
  -> Decision False in time 1.3600000000, query time of that 1.3214718850, with c1=5.0000000000, c2=0.1000000000
