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', 400, 10000]), 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, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 20000]), 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', 100, 200000]), 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', 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', 100, 100]), 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, 4000]), 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, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]), 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, 2000]), 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', 200, 100]), 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', 200, 40000]), 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', 100, 2000]), 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', 400, 100]), 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', 400, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), 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, 400]), 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', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200])]
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 10000])
Got a train set of size (60000 * 784)
Built index in 65.24
Index size:  514732.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0614211290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5400000000, query time of that 0.5300601950, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 5.1900000000, query time of that 5.1302498190, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0566532040, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1904.69 < 1939.76
  -> Decision False in time 0.4400000000, query time of that 0.4282306310, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1188.59 < 1320.85
  -> Decision False in time 0.5600000000, query time of that 0.5520057280, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0598496220, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1202.53 < 1230.44
  -> Decision False in time 0.7100000000, query time of that 0.5373127120, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1701.41 < 1712.43
  -> Decision False in time 0.0700000000, query time of that 0.0597168680, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 400000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 400000])
Got a train set of size (60000 * 784)
Built index in 65.48000000000002
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6431100840, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.1900000000, query time of that 6.1743997910, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.7800000000, query time of that 61.6752675180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6300000000, query time of that 0.6251908210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.1600000000, query time of that 6.1437232590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 61.2900000000, query time of that 61.1852866290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.6800000000, query time of that 0.6038110120, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.3200000000, query time of that 6.1814428240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 62.3500000000, query time of that 62.1661618310, 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 18.08999999999969
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2317208350, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3500000000, query time of that 2.3372629790, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 23.0300000000, query time of that 22.9483160660, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2406705060, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.2900000000, query time of that 2.2801599880, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 23.0600000000, query time of that 22.9424065810, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2262815870, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.5600000000, query time of that 2.4076107730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.1000000000, query time of that 23.6519501180, 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 18.120000000000346
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7685166310, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.7000000000, query time of that 7.6834540780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 76.8700000000, query time of that 76.7709407970, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.7727346610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.6700000000, query time of that 7.6488864520, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 76.4200000000, query time of that 76.3148883050, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8600000000, query time of that 0.7841655980, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.7400000000, query time of that 7.6201089090, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.5300000000, query time of that 76.7959319190, 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 18.1899999999996
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 0.0714746800, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6749189440, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7400000000, query time of that 6.6825970060, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0625209520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7038723300, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1542.4 < 1630.41
  -> Decision False in time 0.2400000000, query time of that 0.2316721620, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0903320370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0700000000, query time of that 0.8566695560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1655.51 < 1741.39
  -> Decision False in time 0.6400000000, query time of that 0.5778434750, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 40000])
Got a train set of size (60000 * 784)
Built index in 65.77999999999975
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1156141440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0800000000, query time of that 1.0774980140, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.6200000000, query time of that 10.5554836540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1089825170, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0768252800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 10.9500000000, query time of that 10.8443379650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1226941160, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1578.71 < 1678.18
  -> Decision False in time 1.0000000000, query time of that 0.9930360370, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1560.84 < 1585.45
  -> Decision False in time 1.0500000000, query time of that 1.0429153870, 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 18.159999999999854
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4300000000, query time of that 0.4334143770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.2800000000, query time of that 4.2717270640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.3600000000, query time of that 42.2703964860, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4359527190, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.1800000000, query time of that 4.1618624260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.4000000000, query time of that 42.2939961800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4361481560, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.4600000000, query time of that 4.3767297320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.0400000000, query time of that 42.7994362830, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200000])
Got a train set of size (60000 * 784)
Built index in 33.76000000000022
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3629516770, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.7000000000, query time of that 3.6956854030, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.5100000000, query time of that 36.4183952130, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3747525680, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.6400000000, query time of that 3.6179321040, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 36.1400000000, query time of that 36.0444069370, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.3728764290, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.8100000000, query time of that 3.6526492970, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 37.7300000000, query time of that 37.2608186500, 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 18.100000000000364
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0107535780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1793.01 < 1828.04
  -> Decision False in time 0.0400000000, query time of that 0.0362758370, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1955.29 < 1957.15
  -> Decision False in time 0.0200000000, query time of that 0.0260764290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1329.58 < 1428.68
  -> Decision False in time 0.0200000000, query time of that 0.0098603310, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1297.43 < 1336.16
  -> Decision False in time 0.0200000000, query time of that 0.0192884340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1694.28 < 1741.4
  -> Decision False in time 0.0200000000, query time of that 0.0208594910, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
2007.15 < 2018.75
  -> Decision False in time 0.0100000000, query time of that 0.0107487260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1490.07 < 1624.15
  -> Decision False in time 0.0100000000, query time of that 0.0105010140, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1597.37 < 1615.49
  -> Decision False in time 0.0200000000, query time of that 0.0106058950, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 1000])
Got a train set of size (60000 * 784)
Built index in 33.82999999999993
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0161490640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1601.97 < 1648.27
  -> Decision False in time 0.1600000000, query time of that 0.1532723020, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1703.63 < 1717.99
  -> Decision False in time 0.0300000000, query time of that 0.0372446540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1336.42 < 1345.64
  -> Decision False in time 0.0200000000, query time of that 0.0168044880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1977.38 < 2016.85
  -> Decision False in time 0.0700000000, query time of that 0.0680912440, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1672.57 < 1673.32
  -> Decision False in time 0.0600000000, query time of that 0.0602848860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1508.59 < 1512.31
  -> Decision False in time 0.0200000000, query time of that 0.0167460350, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1194.2 < 1215.01
  -> Decision False in time 0.0200000000, query time of that 0.0205707700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1670.4 < 1814.27
  -> Decision False in time 0.0500000000, query time of that 0.0197541130, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 100])
Got a train set of size (60000 * 784)
Built index in 18.139999999999418
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 0.0103489330, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1477.82 < 1563.1
  -> Decision False in time 0.0400000000, query time of that 0.0328624750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1641.7 < 1643
  -> Decision False in time 0.0500000000, query time of that 0.0530243520, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1407.71 < 1456.74
  -> Decision False in time 0.0100000000, query time of that 0.0100212680, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1481.25 < 1493.14
  -> Decision False in time 0.0100000000, query time of that 0.0101714100, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1820.18 < 1872.64
  -> Decision False in time 0.0200000000, query time of that 0.0131693770, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1813 < 1878.86
  -> Decision False in time 0.0100000000, query time of that 0.0102176990, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1598.34 < 1685.11
  -> Decision False in time 0.0100000000, query time of that 0.0097903560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1981.12 < 2065.12
  -> Decision False in time 0.0100000000, query time of that 0.0109582950, 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 65.21999999999935
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0722503920, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.7094639100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 7.0200000000, query time of that 6.9616685170, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0745768600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7486136760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1637.75 < 1648.02
  -> Decision False in time 0.3800000000, query time of that 0.3725866760, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0896341350, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1500000000, query time of that 0.9679167060, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1703.49 < 1732.37
  -> Decision False in time 1.0700000000, query time of that 1.0069665240, 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 18.1200000000008
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0287770510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2629490640, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1442.97 < 1462.8
  -> Decision False in time 0.0500000000, query time of that 0.0522863360, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0274168100, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3200000000, query time of that 0.2902132600, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1373.71 < 1417.52
  -> Decision False in time 0.1500000000, query time of that 0.1403059740, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1956.41 < 1987.5
  -> Decision False in time 0.0300000000, query time of that 0.0265950770, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1506.16 < 1515.96
  -> Decision False in time 0.0400000000, query time of that 0.0310362920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2039.71 < 2092.27
  -> Decision False in time 0.1300000000, query time of that 0.0694898330, 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 65.18000000000029
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1887431110, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.9400000000, query time of that 1.9271876330, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.6400000000, query time of that 19.5681096500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1992094970, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0100000000, query time of that 1.9700284730, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.5800000000, query time of that 19.4973293070, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2173573750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2400000000, query time of that 2.0912862010, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1909.67 < 1939.52
  -> Decision False in time 1.8800000000, query time of that 1.8664502930, 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 33.909999999999854
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2033878030, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.1100000000, query time of that 2.0977587720, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.4200000000, query time of that 20.3479056600, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2088315570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0300000000, query time of that 2.0044839010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.4400000000, query time of that 20.3416495260, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2154422900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3600000000, query time of that 2.2126158000, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.7700000000, query time of that 21.3531840110, 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 34.02000000000044
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0679424750, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6900000000, query time of that 0.6741130780, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.6400000000, query time of that 6.5871024880, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0900000000, query time of that 0.0739580010, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.6959604560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1625.03 < 1635.99
  -> Decision False in time 0.5100000000, query time of that 0.5037019840, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1700000000, query time of that 0.0819803180, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1209.75 < 1231.04
  -> Decision False in time 0.4800000000, query time of that 0.4336512950, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1928.98 < 1953.12
  -> Decision False in time 0.9300000000, query time of that 0.8454172120, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 4000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 4000])
Got a train set of size (60000 * 784)
Built index in 33.75
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0292843550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2800000000, query time of that 0.2807702060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1429.95 < 1437.06
  -> Decision False in time 1.2700000000, query time of that 1.2594965350, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0318575600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3500000000, query time of that 0.3025996790, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1165.26 < 1166.93
  -> Decision False in time 0.0600000000, query time of that 0.0560085210, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0321567940, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1265.93 < 1280.44
  -> Decision False in time 0.0800000000, query time of that 0.0330193650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2008.44 < 2109.06
  -> Decision False in time 0.2600000000, query time of that 0.1188087870, 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 18.13000000000102
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0145503320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.1322712110, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1302.14 < 1336.13
  -> Decision False in time 0.0500000000, query time of that 0.0470910930, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1605.78 < 1642.47
  -> Decision False in time 0.0200000000, query time of that 0.0155290640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1182.29 < 1220.36
  -> Decision False in time 0.0200000000, query time of that 0.0244933870, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1424.83 < 1437.96
  -> Decision False in time 0.0200000000, query time of that 0.0213028620, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1628.13 < 1675.43
  -> Decision False in time 0.0200000000, query time of that 0.0158858630, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1501.51 < 1664.18
  -> Decision False in time 0.1000000000, query time of that 0.0303672320, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1050.42 < 1106.73
  -> Decision False in time 0.0200000000, query time of that 0.0162665950, 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 33.94000000000051
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0210227620, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.2014065290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1637.89 < 1769.69
  -> Decision False in time 0.9700000000, query time of that 0.9525336020, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0227000860, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1390.57 < 1472.97
  -> Decision False in time 0.1200000000, query time of that 0.1236453120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1631.64 < 1868.21
  -> Decision False in time 0.2100000000, query time of that 0.2017360240, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.0235548570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1361.27 < 1432.07
  -> Decision False in time 0.1000000000, query time of that 0.0398771620, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1618.6 < 1717.31
  -> Decision False in time 0.1200000000, query time of that 0.0519582820, 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 34.07999999999993
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6967156470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.8800000000, query time of that 6.8727561130, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 68.7400000000, query time of that 68.6423550310, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6997156320, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.8900000000, query time of that 6.8643696970, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 68.6600000000, query time of that 68.5506036480, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7800000000, query time of that 0.6999865070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.0400000000, query time of that 6.9532543240, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 70.0900000000, query time of that 69.7744871720, 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 33.82999999999993
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0116933780, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1499.08 < 1501.02
  -> Decision False in time 0.0900000000, query time of that 0.0830508980, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1761.73 < 1825.97
  -> Decision False in time 0.0800000000, query time of that 0.0751186160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1799.9 < 1825.17
  -> Decision False in time 0.0200000000, query time of that 0.0121515610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1453.51 < 1567.62
  -> Decision False in time 0.0300000000, query time of that 0.0273783920, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1680.22 < 1714.99
  -> Decision False in time 0.0100000000, query time of that 0.0121091500, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1723.85 < 1836.57
  -> Decision False in time 0.0100000000, query time of that 0.0121844260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1816.28 < 1888.85
  -> Decision False in time 0.0200000000, query time of that 0.0133133150, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1452.53 < 1482.57
  -> Decision False in time 0.0100000000, query time of that 0.0113738540, 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 65.38000000000102
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3546208510, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4700000000, query time of that 3.4622655880, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.6100000000, query time of that 33.5316397930, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3700000000, query time of that 0.3583831720, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.3500000000, query time of that 3.3330910510, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 34.0300000000, query time of that 33.9301335220, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4700000000, query time of that 0.3914990300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.6700000000, query time of that 3.4922927770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1800.25 < 1835.47
  -> Decision False in time 7.8300000000, query time of that 7.7977066970, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 40000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 40000])
Got a train set of size (60000 * 784)
Built index in 33.8700000000008
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1036355580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0900000000, query time of that 1.0805337700, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.2700000000, query time of that 10.2084285460, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1033636200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1000000000, query time of that 1.0639267560, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 10.8000000000, query time of that 10.6703128310, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1900000000, query time of that 0.1145459370, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1954.86 < 1978.16
  -> Decision False in time 0.4200000000, query time of that 0.4106590390, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1714.57 < 1729.31
  -> Decision False in time 7.3300000000, query time of that 7.2711288820, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 10000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 10000])
Got a train set of size (60000 * 784)
Built index in 33.850000000000364
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0466495010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4467136770, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4300000000, query time of that 4.3858493540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0483402630, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5000000000, query time of that 0.4743333170, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1921.75 < 1946.22
  -> Decision False in time 0.9700000000, query time of that 0.9627752580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1513.47 < 1529.75
  -> Decision False in time 0.0700000000, query time of that 0.0556335120, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1422.26 < 1429.83
  -> Decision False in time 0.5100000000, query time of that 0.3380885200, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1589.18 < 1599.25
  -> Decision False in time 0.0500000000, query time of that 0.0520357330, 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 18.080000000001746
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0229533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0192707170, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1800000000, query time of that 0.1834207460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1606.8 < 1751.53
  -> Decision False in time 0.1300000000, query time of that 0.1259964620, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1751.32 < 1756.56
  -> Decision False in time 0.0200000000, query time of that 0.0199622640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1695.18 < 1770.79
  -> Decision False in time 0.0400000000, query time of that 0.0308776810, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1198.19 < 1208.99
  -> Decision False in time 0.0500000000, query time of that 0.0502813650, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1833.72 < 1852.14
  -> Decision False in time 0.0300000000, query time of that 0.0205893570, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1668.73 < 1670.47
  -> Decision False in time 0.2300000000, query time of that 0.0677751920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1708.02 < 1721.06
  -> Decision False in time 0.0200000000, query time of that 0.0234222330, 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 65.70000000000073
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0214100970, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1980067230, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1711.79 < 1718.07
  -> Decision False in time 0.6200000000, query time of that 0.6052553330, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0229403610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1146.43 < 1385.78
  -> Decision False in time 0.0400000000, query time of that 0.0362598360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1714.09 < 1776.13
  -> Decision False in time 0.0500000000, query time of that 0.0519726280, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1571.74 < 1578.62
  -> Decision False in time 0.0300000000, query time of that 0.0229481840, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1798.5 < 1802.62
  -> Decision False in time 0.0200000000, query time of that 0.0226978800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1376.4 < 1381.55
  -> Decision False in time 0.1100000000, query time of that 0.0498038880, 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 65.54999999999927
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0178893260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1835.31 < 1948.96
  -> Decision False in time 0.1400000000, query time of that 0.1372432930, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1754.17 < 1790.11
  -> Decision False in time 0.0600000000, query time of that 0.0530031250, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1688.64 < 1707.57
  -> Decision False in time 0.0100000000, query time of that 0.0150510690, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1530.96 < 1568.39
  -> Decision False in time 0.0700000000, query time of that 0.0623902300, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1514.51 < 1615
  -> Decision False in time 0.0600000000, query time of that 0.0591089900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1816.64 < 1836.53
  -> Decision False in time 0.0200000000, query time of that 0.0177035380, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1606.26 < 1785.25
  -> Decision False in time 0.0200000000, query time of that 0.0174505960, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1672.73 < 1747.32
  -> Decision False in time 0.0100000000, query time of that 0.0181301780, 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 18.139999999999418
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0028783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0441727140, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4485531080, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2022.61 < 2107.11
  -> Decision False in time 4.2700000000, query time of that 4.2221057030, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0467859610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4800000000, query time of that 0.4576847120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1757.02 < 1764.56
  -> Decision False in time 3.0300000000, query time of that 2.9986307540, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1400000000, query time of that 0.0494375860, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1653.19 < 1672.04
  -> Decision False in time 0.4000000000, query time of that 0.2761001250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1851.35 < 1916.39
  -> Decision False in time 0.6400000000, query time of that 0.4364981600, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 2000])
Got a train set of size (60000 * 784)
Built index in 65.45000000000073
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0172116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0273926250, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1720.58 < 1783.97
  -> Decision False in time 0.1000000000, query time of that 0.1019332580, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2040.43 < 2057.46
  -> Decision False in time 0.1400000000, query time of that 0.1347177110, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0283930360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1462.49 < 1514.61
  -> Decision False in time 0.2200000000, query time of that 0.2206483280, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1702.42 < 1707.75
  -> Decision False in time 0.1500000000, query time of that 0.1420798730, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1529.75 < 1533.39
  -> Decision False in time 0.0200000000, query time of that 0.0269751430, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1901.22 < 1912.09
  -> Decision False in time 0.0300000000, query time of that 0.0252935880, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1672.95 < 1753.51
  -> Decision False in time 0.1000000000, query time of that 0.0435355310, 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 18.159999999999854
Index size:  304256.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1144301340, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0800000000, query time of that 1.0700885440, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.9300000000, query time of that 10.8614570790, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1119934620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1100000000, query time of that 1.1032123070, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.1300000000, query time of that 11.0376230110, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1208234850, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.3400000000, query time of that 1.2396604650, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1869.64 < 1885.56
  -> Decision False in time 1.3200000000, query time of that 1.3076921870, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 200, 200])
Got a train set of size (60000 * 784)
Built index in 33.82999999999811
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0122618580, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1956.78 < 1968.66
  -> Decision False in time 0.0100000000, query time of that 0.0141004550, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1469.41 < 1570.74
  -> Decision False in time 0.0700000000, query time of that 0.0602053070, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1948.6 < 2052.01
  -> Decision False in time 0.0100000000, query time of that 0.0129182880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
974.181 < 1004.52
  -> Decision False in time 0.0100000000, query time of that 0.0125640000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1669.36 < 1768.82
  -> Decision False in time 0.0200000000, query time of that 0.0115092150, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1195.48 < 1219.03
  -> Decision False in time 0.0100000000, query time of that 0.0131544720, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1596.86 < 1631.38
  -> Decision False in time 0.0200000000, query time of that 0.0121953260, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1501.69 < 1565.25
  -> Decision False in time 0.0100000000, query time of that 0.0116922220, 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 65.64999999999782
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0343257440, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3218381040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1581.43 < 1658.6
  -> Decision False in time 2.4500000000, query time of that 2.4233832450, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0352592120, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3596015580, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1516.2 < 1547.21
  -> Decision False in time 0.4100000000, query time of that 0.3991168830, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.0414403070, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1429.63 < 1571.26
  -> Decision False in time 0.0400000000, query time of that 0.0393912290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1526.27 < 1578.1
  -> Decision False in time 0.2700000000, query time of that 0.1466982880, 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 65.34000000000015
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0174632730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1440.55 < 1529.3
  -> Decision False in time 0.1000000000, query time of that 0.0955496410, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2138.66 < 2164.31
  -> Decision False in time 0.1000000000, query time of that 0.0942491320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1623.15 < 1653.98
  -> Decision False in time 0.0100000000, query time of that 0.0145443510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1838.62 < 1910.75
  -> Decision False in time 0.0400000000, query time of that 0.0375301410, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1440.25 < 1450.13
  -> Decision False in time 0.0400000000, query time of that 0.0345609400, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1767.65 < 1797.21
  -> Decision False in time 0.0100000000, query time of that 0.0157158800, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1065.91 < 1106.34
  -> Decision False in time 0.0200000000, query time of that 0.0162901290, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1726.9 < 1747.11
  -> Decision False in time 0.0300000000, query time of that 0.0181517360, 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 33.93000000000029
Index size:  395848.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Reject!
1648.59 < 1855.79
  -> Decision False in time 0.0100000000, query time of that 0.0127414190, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1672.88 < 1711.86
  -> Decision False in time 0.0400000000, query time of that 0.0365139760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
2134.85 < 2155.07
  -> Decision False in time 0.0300000000, query time of that 0.0283849920, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1589.54 < 1741.26
  -> Decision False in time 0.0100000000, query time of that 0.0118574470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1480 < 1501.02
  -> Decision False in time 0.0200000000, query time of that 0.0194537490, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1678.6 < 1759.86
  -> Decision False in time 0.0200000000, query time of that 0.0123483590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1139.27 < 1144.08
  -> Decision False in time 0.0200000000, query time of that 0.0134494650, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1447.19 < 1546.83
  -> Decision False in time 0.0200000000, query time of that 0.0127474620, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1745.46 < 1752.15
  -> Decision False in time 0.0100000000, query time of that 0.0124441300, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 100, 200])
Got a train set of size (60000 * 784)
Built index in 18.139999999999418
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 0.0092846470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1587.76 < 1596.73
  -> Decision False in time 0.0200000000, query time of that 0.0219392470, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1399.44 < 1476.52
  -> Decision False in time 0.0300000000, query time of that 0.0207938810, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1072.54 < 1083.51
  -> Decision False in time 0.0100000000, query time of that 0.0095608460, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1447.67 < 1538.95
  -> Decision False in time 0.0100000000, query time of that 0.0150947890, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1178.65 < 1193.54
  -> Decision False in time 0.0200000000, query time of that 0.0177503910, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1551.98 < 1650.31
  -> Decision False in time 0.0300000000, query time of that 0.0104230830, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
869.771 < 912.602
  -> Decision False in time 0.0100000000, query time of that 0.0101627420, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1423.48 < 1424.15
  -> Decision False in time 0.0200000000, query time of that 0.0100317980, 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 65.64000000000306
Index size:  514384.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0160409730, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1752.15 < 1829.48
  -> Decision False in time 0.0700000000, query time of that 0.0637745860, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1422.96 < 1532.68
  -> Decision False in time 0.1700000000, query time of that 0.1702357900, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1176.72 < 1282.71
  -> Decision False in time 0.0200000000, query time of that 0.0152579520, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1308.39 < 1526.42
  -> Decision False in time 0.0500000000, query time of that 0.0442196370, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1647.04 < 1691.63
  -> Decision False in time 0.0300000000, query time of that 0.0282541860, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1444.72 < 1462.74
  -> Decision False in time 0.0100000000, query time of that 0.0154146960, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1493.52 < 1749.46
  -> Decision False in time 0.0200000000, query time of that 0.0201845270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1676 < 1681.4
  -> Decision False in time 0.0200000000, query time of that 0.0163778250, with c1=5.0000000000, c2=0.1000000000
