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 SW-graph
order: [Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 5}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 1}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 4}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 50}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 100}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 25}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 400}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 20}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 15}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 200}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 30}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 15}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 10}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 10}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 800}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 3}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 20}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 2}]), Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 30}])]
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 5}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 5}])
Got a train set of size (60000 * 784)
Built index in 7.67
Index size:  205140.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.3419633333
  Testing...
|S| = 20
|T| = 283
Reject!
995.015 < 1101.24
  -> Decision False in time 0.0100000000, query time of that 0.0056097510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1318.9 < 1383.04
  -> Decision False in time 0.0100000000, query time of that 0.0076374550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1441.92 < 1593.36
  -> Decision False in time 0.0100000000, query time of that 0.0060354270, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2476.77 < 2567.05
  -> Decision False in time 0.0100000000, query time of that 0.0029200170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1386.45 < 1391.37
  -> Decision False in time 0.0000000000, query time of that 0.0027886210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1276.63 < 1335.77
  -> Decision False in time 0.0100000000, query time of that 0.0024851960, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1214.64 < 1267.45
  -> Decision False in time 0.0100000000, query time of that 0.0026697570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1153.39 < 1161.36
  -> Decision False in time 0.0000000000, query time of that 0.0030368190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1363.11 < 1409.01
  -> Decision False in time 0.0100000000, query time of that 0.0032123300, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 1}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 1}])
Got a train set of size (60000 * 784)
Built index in 7.840000000000003
Index size:  16296.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.5262233333
  Testing...
|S| = 20
|T| = 283
Reject!
1978.45 < 2333.79
  -> Decision False in time 0.0000000000, query time of that 0.0033289980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1350.21 < 1418.49
  -> Decision False in time 0.0000000000, query time of that 0.0034749240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1065.48 < 1113.89
  -> Decision False in time 0.0100000000, query time of that 0.0022874360, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1047.12 < 1201.03
  -> Decision False in time 0.0000000000, query time of that 0.0020900480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1213.95 < 1269.45
  -> Decision False in time 0.0000000000, query time of that 0.0025006320, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1333.75 < 1486.88
  -> Decision False in time 0.0100000000, query time of that 0.0024876110, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1615.64 < 1721.42
  -> Decision False in time 0.0000000000, query time of that 0.0023881560, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1669.71 < 1757.19
  -> Decision False in time 0.0000000000, query time of that 0.0021986090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1324.39 < 1343.69
  -> Decision False in time 0.0100000000, query time of that 0.0023648400, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 4}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 4}])
Got a train set of size (60000 * 784)
Built index in 7.339999999999996
Index size:  1532.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.3584850000
  Testing...
|S| = 20
|T| = 283
Reject!
1252.17 < 1313.16
  -> Decision False in time 0.0000000000, query time of that 0.0036625410, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1127.55 < 1224.25
  -> Decision False in time 0.0000000000, query time of that 0.0030655080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1136.59 < 1166.2
  -> Decision False in time 0.0100000000, query time of that 0.0033141930, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1542.8 < 1563.12
  -> Decision False in time 0.0000000000, query time of that 0.0027589780, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
903.571 < 989.829
  -> Decision False in time 0.0000000000, query time of that 0.0034041690, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1566.91 < 1661.14
  -> Decision False in time 0.0100000000, query time of that 0.0028451630, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
761.403 < 779.579
  -> Decision False in time 0.0000000000, query time of that 0.0027015270, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1291.63 < 1331.81
  -> Decision False in time 0.0100000000, query time of that 0.0030362730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2218.69 < 2446.47
  -> Decision False in time 0.0000000000, query time of that 0.0027372410, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 50}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 50}])
Got a train set of size (60000 * 784)
Built index in 15.509999999999991
Index size:  6772.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0061533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0111771950, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.0970069880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 1.0400000000, query time of that 0.9959970490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0127572190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1135520980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2049.76 < 2068.13
  -> Decision False in time 0.3700000000, query time of that 0.3545269610, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0115543000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2169.54 < 2188.46
  -> Decision False in time 0.7700000000, query time of that 0.1148577660, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1859.96 < 1874.75
  -> Decision False in time 0.1700000000, query time of that 0.0302016000, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 100}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 100}])
Got a train set of size (60000 * 784)
Built index in 15.350000000000023
Index size:  1092.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0021500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0152813790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1396756830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 1.4900000000, query time of that 1.4303720800, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0177474410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1682221730, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 1.7900000000, query time of that 1.6520858700, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0198077480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1342.67 < 1491.91
  -> Decision False in time 0.0200000000, query time of that 0.0171565260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
834.047 < 885.376
  -> Decision False in time 0.6000000000, query time of that 0.1444887040, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 25}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 25}])
Got a train set of size (60000 * 784)
Built index in 7.810000000000002
Index size:  608.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1495033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0000000000, query time of that 0.0061059430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1581.11 < 1594.52
  -> Decision False in time 0.0200000000, query time of that 0.0165597100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
943.518 < 1016.87
  -> Decision False in time 0.0400000000, query time of that 0.0352020250, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
750.359 < 802.057
  -> Decision False in time 0.0000000000, query time of that 0.0048555650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
889.915 < 902.634
  -> Decision False in time 0.0100000000, query time of that 0.0053826550, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1337.08 < 1360.55
  -> Decision False in time 0.0100000000, query time of that 0.0049377990, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1099.02 < 1152.64
  -> Decision False in time 0.0000000000, query time of that 0.0053047150, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1401.69 < 1437.66
  -> Decision False in time 0.0100000000, query time of that 0.0053853540, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1301.96 < 1361.26
  -> Decision False in time 0.0100000000, query time of that 0.0057058270, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 400}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 400}])
Got a train set of size (60000 * 784)
Built index in 15.25
Index size:  748.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003283333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0361946560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3444406050, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1286.52 < 1370.92
  -> Decision False in time 0.9300000000, query time of that 0.9148167390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0389209320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3603873900, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 3.7900000000, query time of that 3.6725850440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0379220840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0100000000, query time of that 0.4146622210, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1160.09 < 1161.92
  -> Decision False in time 3.0600000000, query time of that 1.5242520810, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 20}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 20}])
Got a train set of size (60000 * 784)
Built index in 7.800000000000068
Index size:  672.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1810283333
  Testing...
|S| = 20
|T| = 283
Reject!
885.028 < 894.048
  -> Decision False in time 0.0100000000, query time of that 0.0058996570, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1125.01 < 1228.85
  -> Decision False in time 0.0400000000, query time of that 0.0407965390, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
657.78 < 923.237
  -> Decision False in time 0.0100000000, query time of that 0.0110087840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1147.72 < 1173.25
  -> Decision False in time 0.0100000000, query time of that 0.0043792870, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1211.79 < 1273.08
  -> Decision False in time 0.0000000000, query time of that 0.0051009540, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
977.117 < 1053.76
  -> Decision False in time 0.0100000000, query time of that 0.0053207520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
831.028 < 917.577
  -> Decision False in time 0.0100000000, query time of that 0.0055155150, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2183.18 < 2216.58
  -> Decision False in time 0.0000000000, query time of that 0.0045581510, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
806.123 < 807.622
  -> Decision False in time 0.0100000000, query time of that 0.0051039100, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 15}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 15}])
Got a train set of size (60000 * 784)
Built index in 15.149999999999977
Index size:  1240.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0346083333
  Testing...
|S| = 20
|T| = 283
Reject!
2001.35 < 2151.92
  -> Decision False in time 0.0100000000, query time of that 0.0065714790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0551074650, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2187.59 < 2253.82
  -> Decision False in time 0.0400000000, query time of that 0.0347194440, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1231.02 < 1252.52
  -> Decision False in time 0.0100000000, query time of that 0.0057639670, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1023.29 < 1028.76
  -> Decision False in time 0.0100000000, query time of that 0.0133333250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
965.568 < 1019.35
  -> Decision False in time 0.0100000000, query time of that 0.0071764150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
789.721 < 791.343
  -> Decision False in time 0.0100000000, query time of that 0.0061217070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1126.69 < 1182.52
  -> Decision False in time 0.0100000000, query time of that 0.0069611030, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1153.86 < 1174.77
  -> Decision False in time 0.0300000000, query time of that 0.0063650350, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 200}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 200}])
Got a train set of size (60000 * 784)
Built index in 15.620000000000005
Index size:  932.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009266667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0247270920, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2262939820, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.2400000000, query time of that 2.1809846320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0251046070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2615424250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
2045.59 < 2161.28
  -> Decision False in time 2.1000000000, query time of that 2.0541247170, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0276659030, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0000000000, query time of that 0.2916592760, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1373.49 < 1545.17
  -> Decision False in time 1.3200000000, query time of that 0.4712682770, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 30}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 30}])
Got a train set of size (60000 * 784)
Built index in 15.120000000000005
Index size:  268.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0133050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0090735110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0763721810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
842.916 < 873.654
  -> Decision False in time 0.2600000000, query time of that 0.2498343710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0075144450, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1368.21 < 1416.14
  -> Decision False in time 0.0100000000, query time of that 0.0084204320, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1105.91 < 1149.93
  -> Decision False in time 0.0800000000, query time of that 0.0714724040, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1297.87 < 1299.77
  -> Decision False in time 0.0400000000, query time of that 0.0104010390, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1263.11 < 1327.97
  -> Decision False in time 0.0100000000, query time of that 0.0096389450, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2143.86 < 2163.53
  -> Decision False in time 0.1800000000, query time of that 0.0266806240, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 15}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 15}])
Got a train set of size (60000 * 784)
Built index in 7.6200000000000045
Index size:  0.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.2211233333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0047527510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1725.59 < 1765.61
  -> Decision False in time 0.0100000000, query time of that 0.0081459630, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1124.83 < 1309.17
  -> Decision False in time 0.0100000000, query time of that 0.0070142990, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1774.55 < 1797.97
  -> Decision False in time 0.0000000000, query time of that 0.0041240560, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2012.92 < 2062.16
  -> Decision False in time 0.0100000000, query time of that 0.0086785310, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1023.88 < 1026.31
  -> Decision False in time 0.0000000000, query time of that 0.0044156410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1278.33 < 1444.24
  -> Decision False in time 0.0100000000, query time of that 0.0044173770, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1415.21 < 1416.59
  -> Decision False in time 0.0000000000, query time of that 0.0042722530, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
493.725 < 815.515
  -> Decision False in time 0.0100000000, query time of that 0.0044887980, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 10}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 10}])
Got a train set of size (60000 * 784)
Built index in 14.809999999999945
Index size:  220.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0525983333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0061237010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0488592520, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2002.57 < 2020.04
  -> Decision False in time 0.0200000000, query time of that 0.0178716960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1358.54 < 1358.87
  -> Decision False in time 0.0100000000, query time of that 0.0052887220, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1021.68 < 1030.38
  -> Decision False in time 0.0100000000, query time of that 0.0053548820, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1578.44 < 1625.95
  -> Decision False in time 0.0100000000, query time of that 0.0096884850, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
923.579 < 935.931
  -> Decision False in time 0.0700000000, query time of that 0.0058824170, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1267.29 < 1287.17
  -> Decision False in time 0.0100000000, query time of that 0.0059657280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1401.34 < 1418.36
  -> Decision False in time 0.0100000000, query time of that 0.0069223540, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 10}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 10}])
Got a train set of size (60000 * 784)
Built index in 7.600000000000023
Index size:  360.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.2600866667
  Testing...
|S| = 20
|T| = 283
Reject!
1582.39 < 1741.36
  -> Decision False in time 0.0100000000, query time of that 0.0043362550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1478.86 < 1532.73
  -> Decision False in time 0.0000000000, query time of that 0.0068016530, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1310.15 < 1443.08
  -> Decision False in time 0.0100000000, query time of that 0.0046902690, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1106.47 < 1121.65
  -> Decision False in time 0.0000000000, query time of that 0.0036673270, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
790.936 < 797.447
  -> Decision False in time 0.0100000000, query time of that 0.0038737680, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1412.05 < 1419.67
  -> Decision False in time 0.0000000000, query time of that 0.0039743750, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1185.18 < 1210.5
  -> Decision False in time 0.0100000000, query time of that 0.0038104000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1646.73 < 1661.18
  -> Decision False in time 0.0000000000, query time of that 0.0036700010, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1291.57 < 1297.03
  -> Decision False in time 0.0100000000, query time of that 0.0036297440, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 800}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 800}])
Got a train set of size (60000 * 784)
Built index in 15.170000000000073
Index size:  228.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0001500000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0553094340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.5432660750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.5300000000, query time of that 5.4612049950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0529198000, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.6100000000, query time of that 0.5808442140, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 5.8800000000, query time of that 5.7828023680, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0639536360, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 0.9900000000, query time of that 0.6681051820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1598.03 < 1889.67
  -> Decision False in time 7.5200000000, query time of that 5.7186093470, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 3}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 3}])
Got a train set of size (60000 * 784)
Built index in 7.130000000000109
Index size:  0.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.3941150000
  Testing...
|S| = 20
|T| = 283
Reject!
1623.78 < 1676.51
  -> Decision False in time 0.0000000000, query time of that 0.0037013650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1091.22 < 1186.83
  -> Decision False in time 0.0000000000, query time of that 0.0039515460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1307.37 < 1316.94
  -> Decision False in time 0.0100000000, query time of that 0.0056727380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1482.28 < 1492.56
  -> Decision False in time 0.0000000000, query time of that 0.0026276410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1207.69 < 1333.98
  -> Decision False in time 0.0100000000, query time of that 0.0029293750, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
959.956 < 1081.51
  -> Decision False in time 0.0000000000, query time of that 0.0029606670, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1187.35 < 1393.5
  -> Decision False in time 0.0100000000, query time of that 0.0028888320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
842.895 < 843.168
  -> Decision False in time 0.0000000000, query time of that 0.0027425580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1058.47 < 1075.3
  -> Decision False in time 0.0100000000, query time of that 0.0031685240, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 20}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 10}, False, {'efSearch': 20}])
Got a train set of size (60000 * 784)
Built index in 15.200000000000045
Index size:  0.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0237933333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0079094150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0614190380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1217.76 < 1236.21
  -> Decision False in time 0.6500000000, query time of that 0.6043774950, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0078194160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1139.04 < 1158.22
  -> Decision False in time 0.0300000000, query time of that 0.0233899950, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1052.85 < 1056.61
  -> Decision False in time 0.0700000000, query time of that 0.0602476050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1171.12 < 1198.84
  -> Decision False in time 0.0100000000, query time of that 0.0066030760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1087.8 < 1174.65
  -> Decision False in time 0.0500000000, query time of that 0.0073413220, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1773.93 < 1803.31
  -> Decision False in time 0.0200000000, query time of that 0.0071046500, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 2}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 2}])
Got a train set of size (60000 * 784)
Built index in 7.350000000000136
Index size:  520.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.4333066667
  Testing...
|S| = 20
|T| = 283
Reject!
981.722 < 986.403
  -> Decision False in time 0.0000000000, query time of that 0.0032228320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1757.69 < 1928.47
  -> Decision False in time 0.0100000000, query time of that 0.0029825870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1294.05 < 1298.45
  -> Decision False in time 0.0000000000, query time of that 0.0038483980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1651.08 < 1652.25
  -> Decision False in time 0.0000000000, query time of that 0.0025805010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
694.502 < 867.291
  -> Decision False in time 0.0100000000, query time of that 0.0023271720, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
913.525 < 972.525
  -> Decision False in time 0.0000000000, query time of that 0.0025562790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1366.24 < 1382.3
  -> Decision False in time 0.0000000000, query time of that 0.0025715980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
977.246 < 991.814
  -> Decision False in time 0.0100000000, query time of that 0.0025505990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1080.57 < 1159.41
  -> Decision False in time 0.0000000000, query time of that 0.0024207960, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='SW-graph', constructor='NmslibReuseIndex', module='ann_benchmarks.algorithms.nmslib', docker_tag='ann-benchmarks-nmslib', arguments=['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 30}]) ...
Trying to instantiate ann_benchmarks.algorithms.nmslib.NmslibReuseIndex(['euclidean', 'sw-graph', {'NN': 5}, False, {'efSearch': 30}])
Got a train set of size (60000 * 784)
Built index in 7.779999999999973
Index size:  0.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1627183333
  Testing...
|S| = 20
|T| = 283
Reject!
1490.2 < 1564.92
  -> Decision False in time 0.0100000000, query time of that 0.0061947980, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
958.068 < 972.831
  -> Decision False in time 0.0300000000, query time of that 0.0293023710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1566.61 < 1780.51
  -> Decision False in time 0.0700000000, query time of that 0.0668047480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1262.33 < 1300
  -> Decision False in time 0.0100000000, query time of that 0.0061034660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1622.9 < 1647.5
  -> Decision False in time 0.0100000000, query time of that 0.0106357500, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1939.71 < 1985.09
  -> Decision False in time 0.0100000000, query time of that 0.0067070520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1377.87 < 1393.21
  -> Decision False in time 0.0100000000, query time of that 0.0064428090, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1325.29 < 1440.92
  -> Decision False in time 0.0100000000, query time of that 0.0052870320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1593.74 < 1932.58
  -> Decision False in time 0.0000000000, query time of that 0.0057495970, with c1=5.0000000000, c2=0.1000000000
