copying files to /scratch...
starting benchmark...
/scratch/knn/venv/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
running only annoy
order: [Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), 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, 400000]), 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', 400, 40000]), 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', 400, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), 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', 400, 2000]), 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, 200000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), 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, 10000]), 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', 200, 4000]), 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', 400, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 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', 200, 20000]), 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, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 200])
Got a train set of size (60000 * 784)
Built index in 18.409999999999997
Index size:  304616.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0120678030, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1112.94 < 1290.95
  -> Decision False in time 0.0400000000, query time of that 0.0362820170, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1243.53 < 1251.59
  -> Decision False in time 0.0400000000, query time of that 0.0362039220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1693.78 < 1716.08
  -> Decision False in time 0.0100000000, query time of that 0.0088102680, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1230.18 < 1313.94
  -> Decision False in time 0.0200000000, query time of that 0.0196412210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1481.57 < 1527.88
  -> Decision False in time 0.0100000000, query time of that 0.0115589060, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1642.28 < 1645.27
  -> Decision False in time 0.0200000000, query time of that 0.0104572410, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1452.15 < 1476.72
  -> Decision False in time 0.0100000000, query time of that 0.0106264430, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1691.13 < 1739.1
  -> Decision False in time 0.0100000000, query time of that 0.0098357560, 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 65.59
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0163216640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1603.83 < 1658.77
  -> Decision False in time 0.1500000000, query time of that 0.1475511450, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1632.74 < 1657.61
  -> Decision False in time 0.0900000000, query time of that 0.0838701480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1603.69 < 1852.75
  -> Decision False in time 0.0200000000, query time of that 0.0180013070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1683.62 < 1706.61
  -> Decision False in time 0.0200000000, query time of that 0.0174455270, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1509.44 < 1526.7
  -> Decision False in time 0.0400000000, query time of that 0.0462009760, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1450.37 < 1495.81
  -> Decision False in time 0.0300000000, query time of that 0.0199529650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1856.53 < 1866.47
  -> Decision False in time 0.0200000000, query time of that 0.0196109820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1682.11 < 1873.17
  -> Decision False in time 0.0200000000, query time of that 0.0200102910, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 100000])
Got a train set of size (60000 * 784)
Built index in 33.870000000000005
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2209020910, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0800000000, query time of that 2.0670747250, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.5500000000, query time of that 20.4498680570, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2069618450, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0700000000, query time of that 2.0515500700, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.6200000000, query time of that 20.5079889900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3100000000, query time of that 0.2374210920, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3100000000, query time of that 2.1700984360, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 22.2600000000, query time of that 21.7756120150, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100000])
Got a train set of size (60000 * 784)
Built index in 65.21000000000004
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2265626900, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0200000000, query time of that 2.0076060280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.0800000000, query time of that 19.9912416650, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2118131420, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0400000000, query time of that 2.0224382270, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.8900000000, query time of that 19.8017230360, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3100000000, query time of that 0.2193721440, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3000000000, query time of that 2.1272444470, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.4400000000, query time of that 21.0750605100, 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 33.86000000000013
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0127678110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1378 < 1383.2
  -> Decision False in time 0.0900000000, query time of that 0.0911836950, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1320.09 < 1442.96
  -> Decision False in time 0.0400000000, query time of that 0.0402832880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1333.85 < 1366.58
  -> Decision False in time 0.0200000000, query time of that 0.0115554920, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1191.7 < 1233.18
  -> Decision False in time 0.0400000000, query time of that 0.0407575590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1193.36 < 1228.61
  -> Decision False in time 0.0200000000, query time of that 0.0203488350, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1371.81 < 1423.04
  -> Decision False in time 0.0100000000, query time of that 0.0118420380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1519.87 < 1522.16
  -> Decision False in time 0.0200000000, query time of that 0.0121999810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1544.94 < 1588.73
  -> Decision False in time 0.0100000000, query time of that 0.0133441170, 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 65.80999999999995
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0180089660, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.1532323140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1448.16 < 1599.17
  -> Decision False in time 0.0700000000, query time of that 0.0657878150, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1601.02 < 1623.68
  -> Decision False in time 0.0100000000, query time of that 0.0173377890, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1425.65 < 1554.15
  -> Decision False in time 0.0400000000, query time of that 0.0323425600, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1940.4 < 1979.75
  -> Decision False in time 0.0200000000, query time of that 0.0246024130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1714.8 < 1750.61
  -> Decision False in time 0.0200000000, query time of that 0.0168130950, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1212.82 < 1226.1
  -> Decision False in time 0.0200000000, query time of that 0.0184323100, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1165.67 < 1210.2
  -> Decision False in time 0.0200000000, query time of that 0.0161244420, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 400000])
Got a train set of size (60000 * 784)
Built index in 18.210000000000036
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.8100000000, query time of that 0.8097852220, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.6500000000, query time of that 7.6321152870, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 76.0100000000, query time of that 75.8809584910, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7793608900, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.7000000000, query time of that 7.6797173710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 76.8500000000, query time of that 76.7158783840, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8800000000, query time of that 0.7977542830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.8800000000, query time of that 7.7970605890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.8700000000, query time of that 77.5703213090, 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 65.98000000000047
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0352537440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3229297180, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1600.28 < 1601.72
  -> Decision False in time 0.6200000000, query time of that 0.6000556130, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0340800660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1355.29 < 1396.31
  -> Decision False in time 0.3100000000, query time of that 0.3016133660, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1287.25 < 1304.32
  -> Decision False in time 0.3300000000, query time of that 0.3249883190, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1131.93 < 1197.32
  -> Decision False in time 0.1200000000, query time of that 0.0371980780, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1553.56 < 1555.46
  -> Decision False in time 0.0600000000, query time of that 0.0399528680, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1615.02 < 1641.79
  -> Decision False in time 0.4200000000, query time of that 0.2043614940, 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 66.14999999999964
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1130493490, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0700000000, query time of that 1.0580956580, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.8100000000, query time of that 10.7335150780, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1076803360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1400000000, query time of that 1.1186535050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.2200000000, query time of that 11.1083470080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1293213070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4500000000, query time of that 1.3106588160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1676.36 < 1677.71
  -> Decision False in time 0.3600000000, query time of that 0.3560088380, 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 34.19000000000051
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0125267600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1191.25 < 1224.22
  -> Decision False in time 0.0300000000, query time of that 0.0212080900, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2052.24 < 2078.69
  -> Decision False in time 0.0200000000, query time of that 0.0246105890, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1691.95 < 1815.77
  -> Decision False in time 0.0200000000, query time of that 0.0127125520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1708.96 < 2081.76
  -> Decision False in time 0.0100000000, query time of that 0.0126969770, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1863.25 < 1873.2
  -> Decision False in time 0.0200000000, query time of that 0.0208023460, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1383.2 < 1497.62
  -> Decision False in time 0.0200000000, query time of that 0.0123853960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1618.91 < 1629.06
  -> Decision False in time 0.0100000000, query time of that 0.0127797120, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1363.13 < 1624.61
  -> Decision False in time 0.0100000000, query time of that 0.0125942870, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 200000])
Got a train set of size (60000 * 784)
Built index in 65.30999999999949
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3600197430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4400000000, query time of that 3.4301821840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.8900000000, query time of that 33.7923222600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3225022110, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.4100000000, query time of that 3.3884599050, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 34.0700000000, query time of that 33.9590975160, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4000000000, query time of that 0.3254117760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.6400000000, query time of that 3.5027451340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.9600000000, query time of that 34.5460777090, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 20000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 20000])
Got a train set of size (60000 * 784)
Built index in 65.46000000000004
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0764976580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.6952185540, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.9900000000, query time of that 6.9221298770, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0707835810, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7438657990, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1633.85 < 1719.62
  -> Decision False in time 0.2700000000, query time of that 0.2696537020, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0850406640, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1715.07 < 1717.89
  -> Decision False in time 0.3900000000, query time of that 0.3736388890, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1437.88 < 1455.3
  -> Decision False in time 0.6700000000, query time of that 0.6478011420, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 1000])
Got a train set of size (60000 * 784)
Built index in 18.270000000000437
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0153290040, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1381026720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1858.04 < 1898.95
  -> Decision False in time 0.0700000000, query time of that 0.0696629640, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1672.51 < 1711.87
  -> Decision False in time 0.0200000000, query time of that 0.0159250510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1589.27 < 1645.02
  -> Decision False in time 0.1000000000, query time of that 0.0979896420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1683.68 < 1714.99
  -> Decision False in time 0.0900000000, query time of that 0.0852623290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1498.13 < 1566.74
  -> Decision False in time 0.0200000000, query time of that 0.0155399860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1640.06 < 1711.54
  -> Decision False in time 0.0200000000, query time of that 0.0165506410, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1513.94 < 1520.55
  -> Decision False in time 0.0700000000, query time of that 0.0175531490, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 400000])
Got a train set of size (60000 * 784)
Built index in 34.13000000000011
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.7103715340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.9500000000, query time of that 6.9406964140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 69.4100000000, query time of that 69.2841960900, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7100000000, query time of that 0.7004290040, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.9300000000, query time of that 6.9100433400, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 68.5000000000, query time of that 68.3708694080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.6999675980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.0800000000, query time of that 6.9817854990, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 70.4300000000, query time of that 70.1220582920, 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 18.23999999999978
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4426523070, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.3100000000, query time of that 4.3059339370, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.3600000000, query time of that 42.2561698520, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4290295130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.2800000000, query time of that 4.2605221420, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.7600000000, query time of that 42.6391067490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5500000000, query time of that 0.4726051640, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.4800000000, query time of that 4.3990202600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.9300000000, query time of that 43.6220131310, 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 18.31999999999971
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2400000000, query time of that 0.2441106650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3600000000, query time of that 2.3437366780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 23.2000000000, query time of that 23.1030170840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2245578460, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.3300000000, query time of that 2.3049463240, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 23.2200000000, query time of that 23.1129694150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.2686453620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.6300000000, query time of that 2.4466579220, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.6800000000, query time of that 24.1550471110, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 400])
Got a train set of size (60000 * 784)
Built index in 18.44999999999891
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0111426650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1810.59 < 1825.97
  -> Decision False in time 0.0200000000, query time of that 0.0226967380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1750.95 < 1756.08
  -> Decision False in time 0.0700000000, query time of that 0.0599251710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
944.639 < 949.809
  -> Decision False in time 0.0100000000, query time of that 0.0101218030, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1369.47 < 1432.31
  -> Decision False in time 0.0200000000, query time of that 0.0192180920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1805.78 < 1892.48
  -> Decision False in time 0.0100000000, query time of that 0.0106290780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1355.46 < 1414.62
  -> Decision False in time 0.0100000000, query time of that 0.0102460670, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1358.67 < 1412.3
  -> Decision False in time 0.0100000000, query time of that 0.0101468160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1957.24 < 2146.77
  -> Decision False in time 0.0100000000, query time of that 0.0102565020, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 1000])
Got a train set of size (60000 * 784)
Built index in 34.470000000001164
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0171402560, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.1556887230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1297.34 < 1336.95
  -> Decision False in time 0.1800000000, query time of that 0.1758812630, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0178115740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1379.68 < 1437.17
  -> Decision False in time 0.0600000000, query time of that 0.0570340510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
839.058 < 911.502
  -> Decision False in time 0.2300000000, query time of that 0.2249805950, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2009.97 < 2015.7
  -> Decision False in time 0.0200000000, query time of that 0.0196221860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1380.82 < 1414.31
  -> Decision False in time 0.0300000000, query time of that 0.0197576780, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2281.9 < 2294.19
  -> Decision False in time 0.0100000000, query time of that 0.0179236980, 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 66.76999999999862
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0172116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0268980690, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2489889760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1644.03 < 1687.39
  -> Decision False in time 0.0600000000, query time of that 0.0592537220, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1917.49 < 2110.74
  -> Decision False in time 0.0300000000, query time of that 0.0289973160, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.2906815780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1581.43 < 1666.18
  -> Decision False in time 0.1300000000, query time of that 0.1289655300, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1569 < 1650.49
  -> Decision False in time 0.0500000000, query time of that 0.0319405200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1703.49 < 1704.65
  -> Decision False in time 0.0400000000, query time of that 0.0298776260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1854.92 < 1878.52
  -> Decision False in time 0.0600000000, query time of that 0.0347942830, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 10000])
Got a train set of size (60000 * 784)
Built index in 34.4900000000016
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0471559990, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.4498803530, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.5000000000, query time of that 4.4482286700, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0509053140, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4764695020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1823.23 < 1905.66
  -> Decision False in time 1.8800000000, query time of that 1.8538551590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0600923040, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1826.19 < 1856.82
  -> Decision False in time 0.2900000000, query time of that 0.2184456040, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1394.58 < 1408.57
  -> Decision False in time 0.2700000000, query time of that 0.2000385900, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200000])
Got a train set of size (60000 * 784)
Built index in 34.280000000000655
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3692036520, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.7200000000, query time of that 3.7049941660, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.9300000000, query time of that 36.8267356740, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4100000000, query time of that 0.3912755410, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.7600000000, query time of that 3.7485856730, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.5200000000, query time of that 36.4035211100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.3866165770, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.9200000000, query time of that 3.7941801260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 38.0000000000, query time of that 37.6298668080, 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 65.6299999999992
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0204066680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1981222160, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1267.33 < 1393.47
  -> Decision False in time 0.1200000000, query time of that 0.1162923570, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1626.14 < 1628.21
  -> Decision False in time 0.0300000000, query time of that 0.0212042550, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1126.41 < 1152.12
  -> Decision False in time 0.0200000000, query time of that 0.0220560040, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1287.46 < 1309.14
  -> Decision False in time 0.0500000000, query time of that 0.0514219970, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1149.7 < 1227.35
  -> Decision False in time 0.0700000000, query time of that 0.0257229400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1615.32 < 1632.95
  -> Decision False in time 0.0300000000, query time of that 0.0258512040, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1484.39 < 1487.05
  -> Decision False in time 0.0600000000, query time of that 0.0285503230, 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 18.219999999999345
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0654161810, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6851738480, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7600000000, query time of that 6.6953718840, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0764832760, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7103586210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 7.1200000000, query time of that 7.0191004130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0858268010, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1500000000, query time of that 0.9314664810, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1618.56 < 1694.45
  -> Decision False in time 0.5200000000, query time of that 0.4881620530, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 10000])
Got a train set of size (60000 * 784)
Built index in 65.73999999999978
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0495319790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4867237830, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9500000000, query time of that 4.8873246020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0538672230, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1886.56 < 1902.65
  -> Decision False in time 0.5100000000, query time of that 0.5017483850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1736.77 < 1741.7
  -> Decision False in time 4.4100000000, query time of that 4.3575719030, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0643036380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1801.72 < 1804.86
  -> Decision False in time 0.2700000000, query time of that 0.2020402320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1606.18 < 1631.57
  -> Decision False in time 0.6700000000, query time of that 0.5040341900, 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 18.25
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0028783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0425701770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4300510810, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4100000000, query time of that 4.3524226960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0484980260, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4645728560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1318.99 < 1320.72
  -> Decision False in time 1.7300000000, query time of that 1.7051149140, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1720.41 < 1777.36
  -> Decision False in time 0.0600000000, query time of that 0.0573963650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1514.37 < 1597.79
  -> Decision False in time 0.4000000000, query time of that 0.2685542460, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1636.62 < 1678.87
  -> Decision False in time 0.1300000000, query time of that 0.0913201880, 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 34.100000000000364
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1126367700, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0800000000, query time of that 1.0729995550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.7600000000, query time of that 10.6849460360, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1146759910, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.0600000000, query time of that 1.0438976900, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 10.8600000000, query time of that 10.7679654150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1173267610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.2500000000, query time of that 1.1122855020, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1944.22 < 1962.21
  -> Decision False in time 2.8700000000, query time of that 2.8315911540, 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 34.32999999999993
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0296903160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2828945200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 2.8600000000, query time of that 2.8133699390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0337379790, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3400000000, query time of that 0.3191190350, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1702.67 < 1796.17
  -> Decision False in time 0.7200000000, query time of that 0.7051862900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1825.64 < 1936.86
  -> Decision False in time 0.0400000000, query time of that 0.0356508900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1726.34 < 1809
  -> Decision False in time 0.0500000000, query time of that 0.0365027830, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1780.05 < 1793.56
  -> Decision False in time 0.2200000000, query time of that 0.1147977940, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 2000])
Got a train set of size (60000 * 784)
Built index in 18.360000000000582
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0229533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0198757940, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1868101570, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2058.65 < 2124.4
  -> Decision False in time 0.4900000000, query time of that 0.4779095410, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0196580430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1622.58 < 1751.88
  -> Decision False in time 0.0800000000, query time of that 0.0759371500, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1644.02 < 1695.51
  -> Decision False in time 0.0500000000, query time of that 0.0517412470, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1256.14 < 1350.67
  -> Decision False in time 0.0200000000, query time of that 0.0203593130, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1214.73 < 1284.46
  -> Decision False in time 0.1200000000, query time of that 0.0491912750, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1378.12 < 1380.38
  -> Decision False in time 0.0200000000, query time of that 0.0230305490, 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 66.19000000000051
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6417946820, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.3300000000, query time of that 6.3176944840, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 62.4100000000, query time of that 62.2874394370, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6314260910, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.1700000000, query time of that 6.1511424710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 62.1000000000, query time of that 61.9709543130, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7400000000, query time of that 0.6547723340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.4200000000, query time of that 6.2713701410, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 62.8300000000, query time of that 62.5735052270, 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 18.400000000001455
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1000000000, query time of that 0.1024585540, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1000000000, query time of that 1.0840478080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 11.0000000000, query time of that 10.9216292960, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1300000000, query time of that 0.1172259330, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1400000000, query time of that 1.1252960530, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1720.82 < 1755.99
  -> Decision False in time 2.5200000000, query time of that 2.4970672950, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1146061610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4600000000, query time of that 1.3233287200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1586.83 < 1599.52
  -> Decision False in time 2.3000000000, query time of that 2.2843517860, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 4000])
Got a train set of size (60000 * 784)
Built index in 18.18000000000029
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0302236250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1500.67 < 1558.05
  -> Decision False in time 0.1400000000, query time of that 0.1422764980, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1729.6 < 1805.45
  -> Decision False in time 0.6100000000, query time of that 0.6025897530, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0305315450, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.2895346510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1562.93 < 1595.64
  -> Decision False in time 0.1400000000, query time of that 0.1459875100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1503.19 < 1535.46
  -> Decision False in time 0.0400000000, query time of that 0.0303606940, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1545.52 < 1551.74
  -> Decision False in time 0.1500000000, query time of that 0.0701098640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1705.64 < 1769.18
  -> Decision False in time 0.1300000000, query time of that 0.0736269750, 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 22.25
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0109414320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1688.5 < 1711.84
  -> Decision False in time 0.0500000000, query time of that 0.0466306230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1820.81 < 1851.49
  -> Decision False in time 0.0200000000, query time of that 0.0162131980, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1608.91 < 1633.65
  -> Decision False in time 0.0100000000, query time of that 0.0095304570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1509.51 < 1619.8
  -> Decision False in time 0.0100000000, query time of that 0.0132553140, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1784.25 < 1864.41
  -> Decision False in time 0.0200000000, query time of that 0.0162166950, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1604.94 < 1697.1
  -> Decision False in time 0.0100000000, query time of that 0.0103170470, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1748.7 < 1787.25
  -> Decision False in time 0.0200000000, query time of that 0.0105068390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
961.075 < 962.79
  -> Decision False in time 0.0100000000, query time of that 0.0101261760, 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 33.909999999999854
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0229691750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2071753250, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1423.87 < 1547.03
  -> Decision False in time 0.0600000000, query time of that 0.0632567640, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
2003.34 < 2034.04
  -> Decision False in time 0.0300000000, query time of that 0.0238850210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2337907510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1630.61 < 1787.07
  -> Decision False in time 0.0500000000, query time of that 0.0519433440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1821.2 < 1858.04
  -> Decision False in time 0.0300000000, query time of that 0.0248030610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1116.03 < 1140.9
  -> Decision False in time 0.2500000000, query time of that 0.0854510580, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1198.83 < 1204.84
  -> Decision False in time 0.0200000000, query time of that 0.0241473510, 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 33.909999999999854
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Reject!
1827.95 < 1853.71
  -> Decision False in time 0.0100000000, query time of that 0.0130518160, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1975.15 < 2008.27
  -> Decision False in time 0.0900000000, query time of that 0.0873457710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1480.37 < 1558.45
  -> Decision False in time 0.1000000000, query time of that 0.0873510500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1987.67 < 2215.1
  -> Decision False in time 0.0100000000, query time of that 0.0112731630, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1626.23 < 1642.21
  -> Decision False in time 0.0100000000, query time of that 0.0123358230, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1877.52 < 2124.38
  -> Decision False in time 0.0300000000, query time of that 0.0298703100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1508.12 < 1536.75
  -> Decision False in time 0.0200000000, query time of that 0.0137671340, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1756.51 < 1802.07
  -> Decision False in time 0.0100000000, query time of that 0.0133466170, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1268.71 < 1317.3
  -> Decision False in time 0.0200000000, query time of that 0.0138200890, 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 33.87000000000262
Index size:  395600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0719330920, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6757464380, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.6800000000, query time of that 6.6109532350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0666063130, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7086724850, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1745.53 < 1780.88
  -> Decision False in time 1.3400000000, query time of that 1.3248108080, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0713789480, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0700000000, query time of that 0.7385167120, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1733.99 < 1738.94
  -> Decision False in time 2.2000000000, query time of that 1.7669182780, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100])
Got a train set of size (60000 * 784)
Built index in 65.87999999999738
Index size:  514400.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Reject!
1658.63 < 1678.46
  -> Decision False in time 0.0100000000, query time of that 0.0167679010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1535.34 < 1540.75
  -> Decision False in time 0.0400000000, query time of that 0.0404656060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1269.32 < 1292.78
  -> Decision False in time 0.2000000000, query time of that 0.1894242690, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1263.15 < 1269.32
  -> Decision False in time 0.0200000000, query time of that 0.0164144870, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1981.67 < 1988.46
  -> Decision False in time 0.0100000000, query time of that 0.0156962140, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1165.6 < 1175.19
  -> Decision False in time 0.0200000000, query time of that 0.0148080410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1452.98 < 1526.07
  -> Decision False in time 0.0400000000, query time of that 0.0184235300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1396.05 < 1526.18
  -> Decision False in time 0.0200000000, query time of that 0.0173687690, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1348.86 < 1701.67
  -> Decision False in time 0.0200000000, query time of that 0.0186772910, with c1=5.0000000000, c2=0.1000000000
