copying files to /scratch...
starting benchmark...
/scratch/knn/venv/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
running only annoy
order: [Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]), 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, 40000]), 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', 200, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), 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, 400000]), 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, 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', 100, 200]), 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, 1000]), 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, 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', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), 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, 400000]), 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', 400, 200000]), 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', 100, 2000]), 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', 200, 400]), 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, 400]), 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', 100, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 100000])
Got a train set of size (60000 * 784)
Built index in 33.73
Index size:  396464.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1674461400, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5800000000, query time of that 1.5729925750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.4700000000, query time of that 15.4052687400, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1611824570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5500000000, query time of that 1.5381493920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.4200000000, query time of that 15.3487116830, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.1727945860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.7700000000, query time of that 1.6422081880, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1309.47 < 1526.23
  -> Decision False in time 9.7700000000, query time of that 9.7160911630, 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 65.31999999999994
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0193766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0279572700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2609694500, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1384.71 < 1391.76
  -> Decision False in time 0.3800000000, query time of that 0.3790302160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0292443660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1290.65 < 1362.46
  -> Decision False in time 0.2600000000, query time of that 0.2490188070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2204.56 < 2215.26
  -> Decision False in time 0.0900000000, query time of that 0.0892449380, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1122.46 < 1163.79
  -> Decision False in time 0.0600000000, query time of that 0.0356462980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1195.87 < 1207.3
  -> Decision False in time 0.0700000000, query time of that 0.0363997990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1185.49 < 1188.42
  -> Decision False in time 0.0400000000, query time of that 0.0339830920, 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 33.799999999999955
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008766667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0813522380, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7725942500, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.7600000000, query time of that 7.7009113560, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0805555530, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1017.33 < 1026.88
  -> Decision False in time 0.1700000000, query time of that 0.1679939470, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.1800000000, query time of that 8.0828982470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.0890012800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 0.9675913850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1427.29 < 1452.49
  -> Decision False in time 1.3800000000, query time of that 1.3260163440, 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 18.090000000000146
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0017150000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0510656700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5072913110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9600000000, query time of that 4.9079931520, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0533049230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1062.47 < 1075.55
  -> Decision False in time 0.1600000000, query time of that 0.1576238940, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1106.14 < 1123.05
  -> Decision False in time 2.7200000000, query time of that 2.6881030300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0669304240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0200000000, query time of that 0.6369699950, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2101.37 < 2150.16
  -> Decision False in time 0.7300000000, query time of that 0.5167037050, 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 33.799999999999955
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0044733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0382067910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3660207200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.6800000000, query time of that 3.6302931270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0429878540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1594.43 < 1606.03
  -> Decision False in time 0.1700000000, query time of that 0.1672164850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
772.328 < 797.299
  -> Decision False in time 0.4600000000, query time of that 0.4439547410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0447290170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 0.9900000000, query time of that 0.4997055120, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
981.44 < 999.963
  -> Decision False in time 0.1500000000, query time of that 0.0942771240, 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 33.830000000000155
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0113500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0262432650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2583325280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1316.26 < 1340.86
  -> Decision False in time 1.6200000000, query time of that 1.5906377800, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0269892870, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.2861343480, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1007.94 < 1078.87
  -> Decision False in time 0.2200000000, query time of that 0.2134617530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1029.49 < 1143.82
  -> Decision False in time 0.0500000000, query time of that 0.0290414930, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1416.15 < 1417.82
  -> Decision False in time 0.0500000000, query time of that 0.0306557660, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1658.89 < 1715.2
  -> Decision False in time 0.2100000000, query time of that 0.0973135820, 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 65.33000000000015
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0344483333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0260050290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2313027300, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1229.73 < 1258.28
  -> Decision False in time 0.1200000000, query time of that 0.1210632420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
867.421 < 901.085
  -> Decision False in time 0.0300000000, query time of that 0.0266485470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
990.034 < 1000.64
  -> Decision False in time 0.0500000000, query time of that 0.0437654550, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
969.451 < 1033.77
  -> Decision False in time 0.2600000000, query time of that 0.2563594090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1131.52 < 1250.63
  -> Decision False in time 0.0500000000, query time of that 0.0288891460, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1043.35 < 1048.24
  -> Decision False in time 0.0300000000, query time of that 0.0289199850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1158.67 < 1159.14
  -> Decision False in time 0.0300000000, query time of that 0.0313416920, 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 33.830000000000155
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Reject!
1170.22 < 1203.88
  -> Decision False in time 0.0100000000, query time of that 0.0156936180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1300417620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1097.44 < 1115.68
  -> Decision False in time 0.2300000000, query time of that 0.2267927420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1456.8 < 1550.54
  -> Decision False in time 0.0200000000, query time of that 0.0150620380, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1339.27 < 1443.22
  -> Decision False in time 0.0300000000, query time of that 0.0335087130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1272.04 < 1276.59
  -> Decision False in time 0.0800000000, query time of that 0.0780712650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1124.87 < 1164.3
  -> Decision False in time 0.0200000000, query time of that 0.0152286730, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
823.688 < 843.889
  -> Decision False in time 0.0200000000, query time of that 0.0165377100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
906.148 < 979.233
  -> Decision False in time 0.0200000000, query time of that 0.0166117990, 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 18.060000000000173
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0006000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0851546620, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8000000000, query time of that 0.8020059510, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.9200000000, query time of that 7.8456418900, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0804028850, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.8100000000, query time of that 0.7860885760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.2100000000, query time of that 8.1267811720, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0873755050, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1619.26 < 1660.79
  -> Decision False in time 1.0200000000, query time of that 0.9494783990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
933.215 < 1193.7
  -> Decision False in time 0.6600000000, query time of that 0.6447936870, 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 33.73000000000002
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2867750270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.8300000000, query time of that 2.8148575860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 27.9100000000, query time of that 27.8380145500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2892659710, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.8100000000, query time of that 2.7900400730, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 27.9500000000, query time of that 27.8612789140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2859163770, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.9400000000, query time of that 2.8493364010, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 28.9500000000, query time of that 28.5804048480, 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 65.64999999999964
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5086527980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.9500000000, query time of that 4.9356171030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 49.3200000000, query time of that 49.2299353150, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.5020714880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.9000000000, query time of that 4.8835575970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 49.2600000000, query time of that 49.1584190350, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.4975952820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.2000000000, query time of that 4.9669860480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 50.3200000000, query time of that 50.0623230910, 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 18.06999999999971
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0042050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0337229320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3349974320, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.4100000000, query time of that 3.3653478240, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0380612270, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4100000000, query time of that 0.3719237070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1517.08 < 1526.55
  -> Decision False in time 0.5400000000, query time of that 0.5277078070, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0412567100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1592.3 < 1606.36
  -> Decision False in time 0.0500000000, query time of that 0.0418280270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1489.54 < 1509.78
  -> Decision False in time 0.5200000000, query time of that 0.2768410920, 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 33.81999999999971
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0756500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0147636020, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1309575840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1040.29 < 1129.22
  -> Decision False in time 0.0300000000, query time of that 0.0289445180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2270.92 < 2318.27
  -> Decision False in time 0.0200000000, query time of that 0.0152407130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1426.95 < 1440.66
  -> Decision False in time 0.0200000000, query time of that 0.0136680970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1048.84 < 1061.47
  -> Decision False in time 0.0400000000, query time of that 0.0451970180, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
911.314 < 915.479
  -> Decision False in time 0.0200000000, query time of that 0.0158392330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1112.36 < 1125.33
  -> Decision False in time 0.0200000000, query time of that 0.0152407600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2002.01 < 2027.87
  -> Decision False in time 0.0200000000, query time of that 0.0143550370, 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 33.94000000000051
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0543481210, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5300000000, query time of that 0.5212138970, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1400000000, query time of that 5.0879362210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0539476510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5700000000, query time of that 0.5463353090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1055.64 < 1173.95
  -> Decision False in time 1.5700000000, query time of that 1.5548229140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0614103170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0100000000, query time of that 0.6668668590, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1783.92 < 1909.62
  -> Decision False in time 0.6000000000, query time of that 0.4404570100, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 200])
Got a train set of size (60000 * 784)
Built index in 18.029999999999745
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Reject!
1293.39 < 1306.27
  -> Decision False in time 0.0200000000, query time of that 0.0120245700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.1004762170, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1469.79 < 1486.25
  -> Decision False in time 0.0800000000, query time of that 0.0718754640, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0112318940, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
981.688 < 1064.02
  -> Decision False in time 0.0300000000, query time of that 0.0217207160, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1525.69 < 1543.81
  -> Decision False in time 0.0300000000, query time of that 0.0361132820, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2129.92 < 2158.49
  -> Decision False in time 0.0200000000, query time of that 0.0107241750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1202.55 < 1212.02
  -> Decision False in time 0.0100000000, query time of that 0.0116369130, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1270.93 < 1305.7
  -> Decision False in time 0.0100000000, query time of that 0.0118756050, 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 33.600000000000364
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0385416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0181267410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1778.16 < 1782.48
  -> Decision False in time 0.1400000000, query time of that 0.1362685210, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1008.55 < 1048.01
  -> Decision False in time 0.1300000000, query time of that 0.1269561610, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1464.03 < 1475.48
  -> Decision False in time 0.0200000000, query time of that 0.0173635490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
915.086 < 1184.07
  -> Decision False in time 0.0700000000, query time of that 0.0650439590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1286.9 < 1293.76
  -> Decision False in time 0.0400000000, query time of that 0.0466787610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1365.59 < 1393.8
  -> Decision False in time 0.0300000000, query time of that 0.0214077560, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1390.4 < 1392.9
  -> Decision False in time 0.0200000000, query time of that 0.0193678850, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1007.85 < 1022.92
  -> Decision False in time 0.0300000000, query time of that 0.0219648060, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 1000])
Got a train set of size (60000 * 784)
Built index in 17.960000000000036
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0427616667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0148160740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1738.56 < 2035.69
  -> Decision False in time 0.1300000000, query time of that 0.1221451090, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2110.6 < 2148.26
  -> Decision False in time 0.2000000000, query time of that 0.1944335170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
985.039 < 1018.22
  -> Decision False in time 0.0200000000, query time of that 0.0153114360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1642.8 < 1652.34
  -> Decision False in time 0.0300000000, query time of that 0.0336126250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1302.53 < 1303.09
  -> Decision False in time 0.1500000000, query time of that 0.1401360490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1493.25 < 1543.2
  -> Decision False in time 0.0200000000, query time of that 0.0156443530, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2014.58 < 2040.41
  -> Decision False in time 0.0200000000, query time of that 0.0169456800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
964.135 < 978.923
  -> Decision False in time 0.1000000000, query time of that 0.0336277230, 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 64.82999999999993
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0216999040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1948593700, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1437.87 < 1458.36
  -> Decision False in time 0.0700000000, query time of that 0.0676442840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1347.64 < 1381.95
  -> Decision False in time 0.0200000000, query time of that 0.0236808600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1303.53 < 1336.04
  -> Decision False in time 0.0300000000, query time of that 0.0225367250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
933.079 < 957.755
  -> Decision False in time 0.0700000000, query time of that 0.0753668850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1013.58 < 1066.05
  -> Decision False in time 0.0300000000, query time of that 0.0260552400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
986.666 < 1077.59
  -> Decision False in time 0.0300000000, query time of that 0.0240252610, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
989.053 < 1020.45
  -> Decision False in time 0.0200000000, query time of that 0.0222331980, 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 64.85999999999967
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0833606200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.8600000000, query time of that 0.8503988130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 8.3300000000, query time of that 8.2763676400, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0909111070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.9100000000, query time of that 0.8860332430, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 8.8100000000, query time of that 8.7165623230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0956737940, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1700000000, query time of that 1.0236672420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
714.855 < 1090.28
  -> Decision False in time 2.8700000000, query time of that 2.8399813520, 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 65.27999999999975
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0660183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0207799410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1943984590, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1401.52 < 1492.33
  -> Decision False in time 0.8000000000, query time of that 0.7780100270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1815.27 < 1825.19
  -> Decision False in time 0.0200000000, query time of that 0.0218444290, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1029.68 < 1041.39
  -> Decision False in time 0.0400000000, query time of that 0.0359858260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
950.593 < 1019.98
  -> Decision False in time 0.0400000000, query time of that 0.0428061920, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1062.25 < 1108.94
  -> Decision False in time 0.0300000000, query time of that 0.0237034210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1188.54 < 1210.35
  -> Decision False in time 0.0200000000, query time of that 0.0249547780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
912.481 < 959.69
  -> Decision False in time 0.0300000000, query time of that 0.0236729360, 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 18.039999999999964
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3290153870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.1600000000, query time of that 3.1469723790, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 31.4300000000, query time of that 31.3464539390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3268548720, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.1600000000, query time of that 3.1441661080, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 31.3200000000, query time of that 31.2222601900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3144151860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.4500000000, query time of that 3.2291943080, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 32.4500000000, query time of that 32.0506834480, 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 17.93000000000029
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0119383333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0235097070, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2222965970, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1062 < 1135.53
  -> Decision False in time 1.2300000000, query time of that 1.2068105000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1068.96 < 1075.89
  -> Decision False in time 0.0200000000, query time of that 0.0233740120, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2492857720, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1388.18 < 1427.89
  -> Decision False in time 0.1000000000, query time of that 0.0962335670, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
991.266 < 1051.61
  -> Decision False in time 0.0300000000, query time of that 0.0259052480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1037.9 < 1054.7
  -> Decision False in time 0.0500000000, query time of that 0.0283135060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1549.42 < 1569.88
  -> Decision False in time 0.1100000000, query time of that 0.0500785770, 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 18.06999999999971
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000900000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1652607050, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.6800000000, query time of that 1.6701007020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 16.6900000000, query time of that 16.6235077070, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1622117640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.7000000000, query time of that 1.6846684360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 16.8000000000, query time of that 16.6078099030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.1778169000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8600000000, query time of that 1.7621437520, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 18.0200000000, query time of that 17.5870555180, 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 65.39999999999964
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0104533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0338683290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3278198870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1705.1 < 1710.73
  -> Decision False in time 1.5100000000, query time of that 1.4876218980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0355807000, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2109.7 < 2133.28
  -> Decision False in time 0.0400000000, query time of that 0.0383006360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1981.4 < 1997.77
  -> Decision False in time 0.1600000000, query time of that 0.1530959190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1450.23 < 1460.94
  -> Decision False in time 0.0500000000, query time of that 0.0421854710, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1098.17 < 1138.8
  -> Decision False in time 0.0500000000, query time of that 0.0412721020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1909.01 < 1918.04
  -> Decision False in time 0.0400000000, query time of that 0.0343094290, 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 33.75
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5560701130, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.3900000000, query time of that 5.3743275370, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 53.7200000000, query time of that 53.6233339050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.5600000000, query time of that 0.5539724440, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 5.4100000000, query time of that 5.3929505870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 53.4800000000, query time of that 53.3777634520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.5537250130, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 5.4400000000, query time of that 5.3556173620, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 54.6400000000, query time of that 54.3937268360, 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 64.69000000000051
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0020216667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0627946120, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5810453930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.8800000000, query time of that 5.8176115290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0578176110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6600000000, query time of that 0.6292443030, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1441.03 < 1449.41
  -> Decision False in time 0.3600000000, query time of that 0.3471545830, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0729492460, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1118.27 < 1163.8
  -> Decision False in time 0.1800000000, query time of that 0.1618503120, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1375.46 < 1394.86
  -> Decision False in time 0.7500000000, query time of that 0.6196967290, 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 64.64999999999964
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000716667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2750233860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.6700000000, query time of that 2.6528325810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 26.2800000000, query time of that 26.2131809460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2599995280, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.6500000000, query time of that 2.6312519180, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 26.5000000000, query time of that 26.4142881570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.2867138700, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.8300000000, query time of that 2.7082242170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 27.3700000000, query time of that 27.0027173270, 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 64.95999999999913
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1539788720, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.5400000000, query time of that 1.5319710270, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 15.1500000000, query time of that 15.0837647420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1568809110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.5600000000, query time of that 1.5416072020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 15.5600000000, query time of that 15.4410799660, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.1574733550, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.8700000000, query time of that 1.6503356580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1434.01 < 1477.51
  -> Decision False in time 6.2100000000, query time of that 6.1780855900, 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 17.8799999999992
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0231166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0186079110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1695938810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1010.67 < 1155.93
  -> Decision False in time 1.0500000000, query time of that 1.0296608300, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0187660990, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1735.72 < 1766.74
  -> Decision False in time 0.0200000000, query time of that 0.0184563880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1919.06 < 1982.91
  -> Decision False in time 0.0500000000, query time of that 0.0462112270, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1036.59 < 1040.75
  -> Decision False in time 0.0200000000, query time of that 0.0203441980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
914.831 < 916.666
  -> Decision False in time 0.0800000000, query time of that 0.0200865540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
757.048 < 800.65
  -> Decision False in time 0.0200000000, query time of that 0.0192787110, 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:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0213600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0224426530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.2015839980, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1045.27 < 1087.83
  -> Decision False in time 0.5200000000, query time of that 0.5028771130, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0230498780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1392.71 < 1420.34
  -> Decision False in time 0.0500000000, query time of that 0.0549427980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1780.07 < 1845.46
  -> Decision False in time 0.0800000000, query time of that 0.0789056320, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1251 < 1255.22
  -> Decision False in time 0.0500000000, query time of that 0.0249045210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1570.19 < 1594.81
  -> Decision False in time 0.2000000000, query time of that 0.0760148420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1968.57 < 2028.06
  -> Decision False in time 0.0300000000, query time of that 0.0242456650, 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 33.67000000000007
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0739850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0156981550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1378.44 < 1423.04
  -> Decision False in time 0.0800000000, query time of that 0.0771758520, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1322.83 < 1479.02
  -> Decision False in time 0.1900000000, query time of that 0.1812254900, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2093.99 < 2104.07
  -> Decision False in time 0.0100000000, query time of that 0.0138688250, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1274.27 < 1469.28
  -> Decision False in time 0.0200000000, query time of that 0.0147973000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1565.63 < 1646.76
  -> Decision False in time 0.0300000000, query time of that 0.0317059530, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1283.43 < 1289.3
  -> Decision False in time 0.0200000000, query time of that 0.0157533570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1452.82 < 1502.2
  -> Decision False in time 0.0200000000, query time of that 0.0166343870, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2116.03 < 2169.06
  -> Decision False in time 0.0200000000, query time of that 0.0161543780, 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 64.86999999999898
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0043450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0451343990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4378316650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3500000000, query time of that 4.2989920610, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0517449260, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4772133430, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1403.22 < 1433.31
  -> Decision False in time 0.2700000000, query time of that 0.2635271440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.0492391760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
982.145 < 1103.1
  -> Decision False in time 0.2600000000, query time of that 0.1745684370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1765.89 < 1825.62
  -> Decision False in time 0.0500000000, query time of that 0.0530187080, 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 17.93000000000029
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0824850000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0110825070, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1023020370, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1388.49 < 1391.73
  -> Decision False in time 0.0500000000, query time of that 0.0456540670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0125119320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1057.8 < 1077.77
  -> Decision False in time 0.0100000000, query time of that 0.0120028930, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1450.14 < 1537.92
  -> Decision False in time 0.0500000000, query time of that 0.0469501470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1275.91 < 1302.76
  -> Decision False in time 0.0100000000, query time of that 0.0115251650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
953.285 < 975.972
  -> Decision False in time 0.0100000000, query time of that 0.0113832220, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1324.37 < 1394.79
  -> Decision False in time 0.0200000000, query time of that 0.0122963980, 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 64.76999999999862
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0674266667
  Testing...
|S| = 20
|T| = 283
Reject!
1194.93 < 1242.32
  -> Decision False in time 0.0200000000, query time of that 0.0216557730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1037.64 < 1041.23
  -> Decision False in time 0.1200000000, query time of that 0.1138206860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1396.97 < 1502.78
  -> Decision False in time 0.0700000000, query time of that 0.0655470970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1412.52 < 1455.96
  -> Decision False in time 0.0200000000, query time of that 0.0225073510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1650.52 < 1718.72
  -> Decision False in time 0.0300000000, query time of that 0.0269735010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
969.222 < 1006.41
  -> Decision False in time 0.0200000000, query time of that 0.0231589680, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
879.694 < 939.159
  -> Decision False in time 0.0400000000, query time of that 0.0220067670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
832.058 < 850.006
  -> Decision False in time 0.0300000000, query time of that 0.0263782230, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1288.86 < 1372.69
  -> Decision False in time 0.0200000000, query time of that 0.0246793810, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 100])
Got a train set of size (60000 * 784)
Built index in 17.959999999999127
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0847450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0107582890, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1532.6 < 1539.43
  -> Decision False in time 0.0200000000, query time of that 0.0202821880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1605.49 < 1607.55
  -> Decision False in time 0.0800000000, query time of that 0.0699385670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
859.712 < 868.626
  -> Decision False in time 0.0100000000, query time of that 0.0108446940, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2080.59 < 2116.5
  -> Decision False in time 0.0100000000, query time of that 0.0111196110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1084.26 < 1091.41
  -> Decision False in time 0.0200000000, query time of that 0.0156329200, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
983.442 < 1002.57
  -> Decision False in time 0.0100000000, query time of that 0.0131486060, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
866.309 < 881.35
  -> Decision False in time 0.0200000000, query time of that 0.0120313030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
887.202 < 986.484
  -> Decision False in time 0.0300000000, query time of that 0.0123561520, 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 17.94000000000051
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.5800000000, query time of that 0.5802375620, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 5.9700000000, query time of that 5.9597615670, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 59.8500000000, query time of that 59.7490342790, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6000000000, query time of that 0.5975644070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.0600000000, query time of that 6.0301628110, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 59.7900000000, query time of that 59.6836806780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6033490100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.0800000000, query time of that 5.9943585320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 60.2000000000, query time of that 59.8441410820, with c1=5.0000000000, c2=0.1000000000
