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': 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': 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': 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': 800}]), 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': 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': 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': 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': 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': 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': 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': 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': 4}]), 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': 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': 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': 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': 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': 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': 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 7.460000000000001
Index size:  205272.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.2042050000
  Testing...
|S| = 20
|T| = 283
Reject!
1239.43 < 1240.96
  -> Decision False in time 0.0100000000, query time of that 0.0037109340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1298.51 < 1490.92
  -> Decision False in time 0.0300000000, query time of that 0.0229649330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1527.16 < 1578.67
  -> Decision False in time 0.0200000000, query time of that 0.0140532890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
985.464 < 989.546
  -> Decision False in time 0.0000000000, query time of that 0.0039917100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1491.56 < 1739.45
  -> Decision False in time 0.0200000000, query time of that 0.0067109260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1520.11 < 1619.77
  -> Decision False in time 0.0000000000, query time of that 0.0042164370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1308.16 < 1311.22
  -> Decision False in time 0.0100000000, query time of that 0.0039006290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
912.581 < 936.085
  -> Decision False in time 0.0100000000, query time of that 0.0032852830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1225.9 < 1229.43
  -> Decision False in time 0.0100000000, query time of that 0.0037599620, 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 14.740000000000002
Index size:  23308.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0021183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0170279510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1463396080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 1.5000000000, query time of that 1.4533605420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0177262390, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1631143010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1336.82 < 1339.03
  -> Decision False in time 0.1100000000, query time of that 0.1015949260, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1991.25 < 1994.6
  -> Decision False in time 0.0300000000, query time of that 0.0164491510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 0.9100000000, query time of that 0.1687470630, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1595.31 < 1640.23
  -> Decision False in time 1.0200000000, query time of that 0.2161579250, 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 7.590000000000003
Index size:  644.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.3849650000
  Testing...
|S| = 20
|T| = 283
Reject!
1471.76 < 1473.99
  -> Decision False in time 0.0000000000, query time of that 0.0035015330, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1090.09 < 1116.07
  -> Decision False in time 0.0100000000, query time of that 0.0082717300, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
843.093 < 880.124
  -> Decision False in time 0.0100000000, query time of that 0.0028149670, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1413.22 < 1478.17
  -> Decision False in time 0.0000000000, query time of that 0.0025464290, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1016.16 < 1057.12
  -> Decision False in time 0.0000000000, query time of that 0.0025933280, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1010.51 < 1060.12
  -> Decision False in time 0.0000000000, query time of that 0.0030115370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
952.845 < 1105.93
  -> Decision False in time 0.0100000000, query time of that 0.0025923910, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
937.708 < 1068.63
  -> Decision False in time 0.0000000000, query time of that 0.0027596230, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1436.55 < 1519.06
  -> Decision False in time 0.0100000000, query time of that 0.0026407960, 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 14.880000000000024
Index size:  436.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002600000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0614910920, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5200000000, query time of that 0.5078786130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.3400000000, query time of that 5.2826750450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0576772170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5900000000, query time of that 0.5754832570, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 5.9400000000, query time of that 5.7337660520, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0647762790, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0800000000, query time of that 0.7937575070, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 10.0700000000, query time of that 7.7991414610, 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 14.729999999999905
Index size:  1016.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008550000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0230351500, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2102215820, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.1800000000, query time of that 2.1332823070, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0232151540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2483618930, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1708.56 < 1721.11
  -> Decision False in time 0.1700000000, query time of that 0.1603536560, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0223893100, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 0.9500000000, query time of that 0.2818713080, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1649.75 < 1889.21
  -> Decision False in time 0.2400000000, query time of that 0.0931302440, 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 7.4500000000000455
Index size:  704.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.4312450000
  Testing...
|S| = 20
|T| = 283
Reject!
1063.68 < 1176.5
  -> Decision False in time 0.0000000000, query time of that 0.0032910110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1243.91 < 1388.48
  -> Decision False in time 0.0000000000, query time of that 0.0033384090, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1344.33 < 1526.9
  -> Decision False in time 0.0100000000, query time of that 0.0057765490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1488.45 < 1524.9
  -> Decision False in time 0.0000000000, query time of that 0.0025205300, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1485.92 < 1534.47
  -> Decision False in time 0.0100000000, query time of that 0.0025119130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1117.32 < 1118.65
  -> Decision False in time 0.0000000000, query time of that 0.0024832240, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1482.46 < 1543.67
  -> Decision False in time 0.0000000000, query time of that 0.0024461250, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
762.66 < 819.805
  -> Decision False in time 0.0100000000, query time of that 0.0027162240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
841.483 < 927.898
  -> Decision False in time 0.0000000000, query time of that 0.0026447190, 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': 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 7.559999999999945
Index size:  468.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.3322450000
  Testing...
|S| = 20
|T| = 283
Reject!
1863.93 < 1864.33
  -> Decision False in time 0.0100000000, query time of that 0.0040442990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1661.93 < 1707.19
  -> Decision False in time 0.0100000000, query time of that 0.0067645240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
853.632 < 880.316
  -> Decision False in time 0.0000000000, query time of that 0.0028741760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
827.09 < 827.474
  -> Decision False in time 0.0000000000, query time of that 0.0030170680, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1825.61 < 1833.42
  -> Decision False in time 0.0100000000, query time of that 0.0028512860, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1232.11 < 1251.7
  -> Decision False in time 0.0000000000, query time of that 0.0033243710, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1034.01 < 1050.17
  -> Decision False in time 0.0000000000, query time of that 0.0027936050, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
981.368 < 1064.68
  -> Decision False in time 0.0100000000, query time of that 0.0031188550, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1124.81 < 1127.67
  -> Decision False in time 0.0100000000, query time of that 0.0032198000, 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 7.610000000000014
Index size:  484.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1715166667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0000000000, query time of that 0.0060802180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1372.88 < 1418.89
  -> Decision False in time 0.0300000000, query time of that 0.0207744820, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1077.12 < 1121.84
  -> Decision False in time 0.0100000000, query time of that 0.0097735000, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1240.96 < 1287.62
  -> Decision False in time 0.0000000000, query time of that 0.0046158540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1623.77 < 1717.56
  -> Decision False in time 0.0100000000, query time of that 0.0054792590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1276.68 < 1296.23
  -> Decision False in time 0.0000000000, query time of that 0.0056602860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1726.76 < 1743.83
  -> Decision False in time 0.0200000000, query time of that 0.0054676600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1761.02 < 1825.17
  -> Decision False in time 0.0000000000, query time of that 0.0059752280, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1907.86 < 2002.19
  -> Decision False in time 0.0100000000, query time of that 0.0049782600, 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 13.92999999999995
Index size:  776.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0237783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0070533740, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0614299620, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1536.61 < 1576.33
  -> Decision False in time 0.2000000000, query time of that 0.1821143160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0065018810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1461.98 < 1478.95
  -> Decision False in time 0.0400000000, query time of that 0.0391715910, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1261.71 < 1368.08
  -> Decision False in time 0.0700000000, query time of that 0.0641710570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1168.59 < 1193.27
  -> Decision False in time 0.0900000000, query time of that 0.0064698920, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1059.07 < 1115.27
  -> Decision False in time 0.3100000000, query time of that 0.0279798290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1396.38 < 1436.24
  -> Decision False in time 0.0300000000, query time of that 0.0071580620, 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 7.460000000000036
Index size:  656.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.2813616667
  Testing...
|S| = 20
|T| = 283
Reject!
1278.32 < 1410.87
  -> Decision False in time 0.0100000000, query time of that 0.0042529850, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1509.74 < 1556.23
  -> Decision False in time 0.0000000000, query time of that 0.0052270690, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1345.99 < 1369.9
  -> Decision False in time 0.0100000000, query time of that 0.0033614120, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1201.27 < 1207.8
  -> Decision False in time 0.0000000000, query time of that 0.0033633140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2261.82 < 2272.51
  -> Decision False in time 0.0100000000, query time of that 0.0035710130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
862.997 < 941.786
  -> Decision False in time 0.0000000000, query time of that 0.0036834890, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1053.2 < 1076.46
  -> Decision False in time 0.0100000000, query time of that 0.0035794740, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1537.4 < 1561.34
  -> Decision False in time 0.0000000000, query time of that 0.0037095970, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1089.22 < 1170.93
  -> Decision False in time 0.0100000000, query time of that 0.0036265210, 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 14.649999999999977
Index size:  1156.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0347733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0067623430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2510.82 < 2559.98
  -> Decision False in time 0.0100000000, query time of that 0.0137084040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1086.06 < 1207.75
  -> Decision False in time 0.1200000000, query time of that 0.1063539200, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0058292410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1779.92 < 1803.95
  -> Decision False in time 0.0600000000, query time of that 0.0467463670, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1658.45 < 1702.19
  -> Decision False in time 0.0200000000, query time of that 0.0190773220, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1556.48 < 1556.73
  -> Decision False in time 0.0200000000, query time of that 0.0067019030, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1336.81 < 1339.31
  -> Decision False in time 0.0200000000, query time of that 0.0062680880, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1580.59 < 1610.29
  -> Decision False in time 0.0400000000, query time of that 0.0064102140, 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 14.57000000000005
Index size:  1004.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0004283333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0373362340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3306467380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 3.3700000000, query time of that 3.3273515400, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0352764140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3900000000, query time of that 0.3667357210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1843.63 < 1875.34
  -> Decision False in time 1.8400000000, query time of that 1.8067958010, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0372713200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0200000000, query time of that 0.4049188800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
930.278 < 1143.26
  -> Decision False in time 6.7800000000, query time of that 3.2370166060, 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 7.440000000000055
Index size:  0.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.3569700000
  Testing...
|S| = 20
|T| = 283
Reject!
1348.45 < 1531.85
  -> Decision False in time 0.0000000000, query time of that 0.0037019270, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1381.94 < 1424.11
  -> Decision False in time 0.0100000000, query time of that 0.0042705540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1338.94 < 1344.99
  -> Decision False in time 0.0000000000, query time of that 0.0050938120, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1698.61 < 1948.8
  -> Decision False in time 0.0000000000, query time of that 0.0025762240, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1096.85 < 1129.15
  -> Decision False in time 0.0100000000, query time of that 0.0029255520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1163.56 < 1185.91
  -> Decision False in time 0.0000000000, query time of that 0.0029000930, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1088.17 < 1092.99
  -> Decision False in time 0.0100000000, query time of that 0.0028564530, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1708.68 < 1909.48
  -> Decision False in time 0.0000000000, query time of that 0.0029691430, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1545.3 < 1583.82
  -> Decision False in time 0.0000000000, query time of that 0.0030722650, 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 7.169999999999845
Index size:  496.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1324050000
  Testing...
|S| = 20
|T| = 283
Reject!
1769.15 < 1792.85
  -> Decision False in time 0.0100000000, query time of that 0.0061784640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1143.64 < 1173.56
  -> Decision False in time 0.0100000000, query time of that 0.0098925580, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1056.55 < 1085.97
  -> Decision False in time 0.0400000000, query time of that 0.0334538260, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1584.24 < 1602.04
  -> Decision False in time 0.0000000000, query time of that 0.0055074150, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1477.54 < 1591.94
  -> Decision False in time 0.0100000000, query time of that 0.0059136740, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1840.04 < 1841.17
  -> Decision False in time 0.0100000000, query time of that 0.0060254650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1465.91 < 1542.45
  -> Decision False in time 0.0000000000, query time of that 0.0064582300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1208.01 < 1461.76
  -> Decision False in time 0.0200000000, query time of that 0.0057200410, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
859.769 < 882.009
  -> Decision False in time 0.0100000000, query time of that 0.0068051700, 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 14.769999999999982
Index size:  816.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0137283333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0090964220, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0767494180, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1222.64 < 1251.84
  -> Decision False in time 0.5500000000, query time of that 0.5230194180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0087332670, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1920.91 < 2054
  -> Decision False in time 0.0100000000, query time of that 0.0089327610, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1152.08 < 1231
  -> Decision False in time 0.0100000000, query time of that 0.0179089570, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
994.395 < 1017.84
  -> Decision False in time 0.0400000000, query time of that 0.0083675050, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1152.65 < 1165.29
  -> Decision False in time 0.2800000000, query time of that 0.0357355720, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1376.6 < 1439.81
  -> Decision False in time 0.0200000000, query time of that 0.0092081820, 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 7.5900000000001455
Index size:  0.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.5248416667
  Testing...
|S| = 20
|T| = 283
Reject!
1197.23 < 1223.55
  -> Decision False in time 0.0000000000, query time of that 0.0036483860, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1053.89 < 1208.9
  -> Decision False in time 0.0000000000, query time of that 0.0024921640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1440.89 < 1489.83
  -> Decision False in time 0.0100000000, query time of that 0.0029596580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1355.97 < 1390.57
  -> Decision False in time 0.0000000000, query time of that 0.0026409620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2091.09 < 2258.92
  -> Decision False in time 0.0000000000, query time of that 0.0023977810, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
985.671 < 1090.37
  -> Decision False in time 0.0100000000, query time of that 0.0022144590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1452.64 < 1474.49
  -> Decision False in time 0.0000000000, query time of that 0.0026534330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1763.66 < 1915.5
  -> Decision False in time 0.0000000000, query time of that 0.0025320880, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1288.24 < 1384.01
  -> Decision False in time 0.0100000000, query time of that 0.0021435690, 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 7.519999999999982
Index size:  0.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1667516667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0000000000, query time of that 0.0055140330, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1635.91 < 1739.72
  -> Decision False in time 0.0200000000, query time of that 0.0195139230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1931.18 < 1953.5
  -> Decision False in time 0.0500000000, query time of that 0.0385089460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1672.22 < 1777.91
  -> Decision False in time 0.0000000000, query time of that 0.0048145410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1242.23 < 1333.02
  -> Decision False in time 0.0100000000, query time of that 0.0051779020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1412.92 < 1538.26
  -> Decision False in time 0.0000000000, query time of that 0.0050677580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1169.12 < 1272.99
  -> Decision False in time 0.0100000000, query time of that 0.0048518080, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1194.87 < 1281.69
  -> Decision False in time 0.0100000000, query time of that 0.0047789270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1205.34 < 1333.61
  -> Decision False in time 0.0000000000, query time of that 0.0054239390, 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 14.819999999999936
Index size:  804.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0059450000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0113890320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1013528830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1378.24 < 1422.74
  -> Decision False in time 0.8700000000, query time of that 0.8421341480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0101706090, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1142.83 < 1155.82
  -> Decision False in time 0.1300000000, query time of that 0.1129020130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1784.18 < 1965.83
  -> Decision False in time 0.0400000000, query time of that 0.0380906000, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0113551230, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1254.75 < 1412.23
  -> Decision False in time 0.0800000000, query time of that 0.0121362250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1735.74 < 1737.8
  -> Decision False in time 0.0700000000, query time of that 0.0129458820, 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 14.920000000000073
Index size:  860.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0522133333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0059617600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
994.249 < 1012.19
  -> Decision False in time 0.0100000000, query time of that 0.0106084130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
965.428 < 982.953
  -> Decision False in time 0.0900000000, query time of that 0.0882518050, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0052506100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1287.4 < 1287.67
  -> Decision False in time 0.0200000000, query time of that 0.0176752270, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1462.12 < 1473.46
  -> Decision False in time 0.0100000000, query time of that 0.0089943410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
901.777 < 974.168
  -> Decision False in time 0.0400000000, query time of that 0.0054086740, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1341.02 < 1446.72
  -> Decision False in time 0.0200000000, query time of that 0.0058110450, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
960.65 < 961.239
  -> Decision False in time 0.0400000000, query time of that 0.0055997670, with c1=5.0000000000, c2=0.1000000000
