copying files to /scratch...
starting benchmark...
/scratch/knn/venv/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
running only annoy
order: [Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 100]), 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, 200000]), 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, 400000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 100]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 2000]), 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, 1000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 4000]), 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', 200, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 40000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 2000]), 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, 10000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 200]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 200, 1000]), 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', 200, 200000]), 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', 100, 100000]), 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, 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', 400, 20000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 400]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 2000]), Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 100, 40000]), 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, 400000])]
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 41.04
Index size:  395976.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0129079370, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1221.36 < 1242.69
  -> Decision False in time 0.0400000000, query time of that 0.0346944490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1703.19 < 1709.61
  -> Decision False in time 0.1000000000, query time of that 0.0988944250, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1682.44 < 1777.38
  -> Decision False in time 0.0100000000, query time of that 0.0098781480, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1744.4 < 1816.88
  -> Decision False in time 0.0300000000, query time of that 0.0201721450, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1717.28 < 1730.26
  -> Decision False in time 0.0300000000, query time of that 0.0251600700, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1427.79 < 1753.91
  -> Decision False in time 0.0100000000, query time of that 0.0119505760, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1700.79 < 1706.96
  -> Decision False in time 0.0100000000, query time of that 0.0105537770, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1505.6 < 1581.18
  -> Decision False in time 0.0200000000, query time of that 0.0136453620, 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 34.349999999999994
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0083783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0296702590, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2807056170, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1492.81 < 1533.15
  -> Decision False in time 1.5100000000, query time of that 1.4855740320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0291307880, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.3110614020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1449.81 < 1550.02
  -> Decision False in time 0.6600000000, query time of that 0.6388415090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1513.69 < 1665.31
  -> Decision False in time 0.0400000000, query time of that 0.0318766850, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1832.12 < 1849.98
  -> Decision False in time 0.3400000000, query time of that 0.1596075270, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1382.96 < 1408.02
  -> Decision False in time 0.0300000000, query time of that 0.0321027020, 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 18.420000000000016
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.4567079100, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 4.2300000000, query time of that 4.2172353290, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 42.6300000000, query time of that 42.5259208210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.4400000000, query time of that 0.4313757000, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 4.2300000000, query time of that 4.2085125640, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 42.8000000000, query time of that 42.6767663440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.5300000000, query time of that 0.4499373560, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 4.4600000000, query time of that 4.2977815960, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 43.4400000000, query time of that 43.1153044990, 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 66.47000000000003
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0939833333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0167570290, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
981.344 < 984.304
  -> Decision False in time 0.0500000000, query time of that 0.0438073240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1737.42 < 1815.32
  -> Decision False in time 0.0300000000, query time of that 0.0284776820, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1499.42 < 1509.51
  -> Decision False in time 0.0200000000, query time of that 0.0144739600, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1943.49 < 1984.45
  -> Decision False in time 0.0500000000, query time of that 0.0523436470, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1382.76 < 1393.95
  -> Decision False in time 0.0200000000, query time of that 0.0151290090, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1980.44 < 2013.72
  -> Decision False in time 0.0200000000, query time of that 0.0160151930, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1616.71 < 1794.23
  -> Decision False in time 0.0200000000, query time of that 0.0177325140, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1364.71 < 1367.26
  -> Decision False in time 0.0200000000, query time of that 0.0178534890, 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 34.419999999999845
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.7206068530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.9200000000, query time of that 6.9009378280, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 69.3600000000, query time of that 69.2471465180, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7201629210, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.8500000000, query time of that 6.8334669760, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 68.6400000000, query time of that 68.5043214100, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.6959800240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.1500000000, query time of that 7.0311045160, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 70.0000000000, query time of that 69.5439896010, 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 18.039999999999964
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0104819790, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
2053.58 < 2128.31
  -> Decision False in time 0.0800000000, query time of that 0.0676694520, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1948.65 < 1978.08
  -> Decision False in time 0.0900000000, query time of that 0.0857711400, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0099966330, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1183.11 < 1288.91
  -> Decision False in time 0.0200000000, query time of that 0.0152873120, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1398.78 < 1430.59
  -> Decision False in time 0.0200000000, query time of that 0.0226473590, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1682.27 < 1981.01
  -> Decision False in time 0.0100000000, query time of that 0.0103104620, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1924.94 < 1997.95
  -> Decision False in time 0.0200000000, query time of that 0.0108409560, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1898.25 < 1939.14
  -> Decision False in time 0.0100000000, query time of that 0.0098074450, 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 18.01000000000022
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0512416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0143004320, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1664.06 < 1669.56
  -> Decision False in time 0.0600000000, query time of that 0.0619188400, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1945.62 < 1960.92
  -> Decision False in time 0.0500000000, query time of that 0.0494560330, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0153320360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2085.19 < 2085.74
  -> Decision False in time 0.0700000000, query time of that 0.0686230480, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1330.59 < 1491.17
  -> Decision False in time 0.0200000000, query time of that 0.0138428830, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1419.69 < 1469.06
  -> Decision False in time 0.0200000000, query time of that 0.0156536700, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1871.54 < 2020.12
  -> Decision False in time 0.0200000000, query time of that 0.0165679670, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1353.05 < 1439.27
  -> Decision False in time 0.0200000000, query time of that 0.0156904970, 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 18.030000000000655
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1233016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0107646420, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1648.71 < 1656.77
  -> Decision False in time 0.0400000000, query time of that 0.0363997100, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1376.09 < 1469.01
  -> Decision False in time 0.0500000000, query time of that 0.0492420480, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1488.09 < 1567.07
  -> Decision False in time 0.0100000000, query time of that 0.0098192470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1887.41 < 1963.89
  -> Decision False in time 0.0200000000, query time of that 0.0146540210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1944.37 < 2023.97
  -> Decision False in time 0.0100000000, query time of that 0.0099753230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1274.38 < 1381.81
  -> Decision False in time 0.0200000000, query time of that 0.0102961970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1354.89 < 1373.69
  -> Decision False in time 0.0100000000, query time of that 0.0114454900, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1582.73 < 1622.27
  -> Decision False in time 0.0100000000, query time of that 0.0101274840, 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 33.67000000000007
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0195666667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0221426180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2044488240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1444.85 < 1448.75
  -> Decision False in time 0.2900000000, query time of that 0.2855112150, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0229499070, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1399.47 < 1492.69
  -> Decision False in time 0.0400000000, query time of that 0.0433517630, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1597.86 < 1678.87
  -> Decision False in time 0.1100000000, query time of that 0.1021525260, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1382.96 < 1408.02
  -> Decision False in time 0.0200000000, query time of that 0.0223140260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1815.86 < 1847.74
  -> Decision False in time 0.0300000000, query time of that 0.0242322000, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1665.17 < 1680.94
  -> Decision False in time 0.0300000000, query time of that 0.0262761220, with c1=5.0000000000, c2=0.1000000000
Definition(algorithm='annoy', constructor='Annoy', module='ann_benchmarks.algorithms.annoy', docker_tag='ann-benchmarks-annoy', arguments=['euclidean', 400, 100]) ...
Trying to instantiate ann_benchmarks.algorithms.annoy.Annoy(['euclidean', 400, 100])
Got a train set of size (60000 * 784)
Built index in 64.92000000000007
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0170620850, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1474.01 < 1569.83
  -> Decision False in time 0.0400000000, query time of that 0.0341091060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1419.67 < 1517.85
  -> Decision False in time 0.1100000000, query time of that 0.1093230470, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1301.05 < 1421.16
  -> Decision False in time 0.0200000000, query time of that 0.0153573090, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2151.2 < 2195.16
  -> Decision False in time 0.0500000000, query time of that 0.0417306260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1517.75 < 1661.25
  -> Decision False in time 0.0100000000, query time of that 0.0157648420, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1432.88 < 1460.69
  -> Decision False in time 0.0200000000, query time of that 0.0168343510, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1146.49 < 1235.74
  -> Decision False in time 0.0200000000, query time of that 0.0156127820, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1398.78 < 1430.24
  -> Decision False in time 0.0100000000, query time of that 0.0152518920, 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 18.100000000000364
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0028783333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0446547430, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.4400686470, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.3700000000, query time of that 4.3143527420, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0475811580, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.4900000000, query time of that 0.4596705690, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1773.3 < 1840.89
  -> Decision False in time 2.0800000000, query time of that 2.0610143830, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0523099430, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.0800000000, query time of that 0.5756006050, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1685.24 < 1702.05
  -> Decision False in time 0.4800000000, query time of that 0.2962388990, 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 65.36999999999989
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0379633333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0211026360, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2000000000, query time of that 0.1951840660, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1276.61 < 1357.25
  -> Decision False in time 1.0000000000, query time of that 0.9817384580, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0206550510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1567.69 < 1705.18
  -> Decision False in time 0.0400000000, query time of that 0.0357202930, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1248.8 < 1286.58
  -> Decision False in time 0.0300000000, query time of that 0.0358383950, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1451.01 < 1464.98
  -> Decision False in time 0.0300000000, query time of that 0.0219990150, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1656.82 < 1683.6
  -> Decision False in time 0.0400000000, query time of that 0.0219828190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1504.55 < 1521.28
  -> Decision False in time 0.0200000000, query time of that 0.0200115210, 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 65.39000000000033
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0966950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0170871540, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1396.64 < 1563.97
  -> Decision False in time 0.0400000000, query time of that 0.0396529240, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1656.35 < 1662.4
  -> Decision False in time 0.0400000000, query time of that 0.0407445610, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1390.71 < 1396.32
  -> Decision False in time 0.0200000000, query time of that 0.0164375530, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1613.62 < 1775.61
  -> Decision False in time 0.0100000000, query time of that 0.0164449210, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1565.65 < 1591.9
  -> Decision False in time 0.0200000000, query time of that 0.0165128800, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1547.15 < 1594.97
  -> Decision False in time 0.0200000000, query time of that 0.0166445300, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1617.33 < 1630.6
  -> Decision False in time 0.0200000000, query time of that 0.0187433050, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1408.08 < 1441.27
  -> Decision False in time 0.0200000000, query time of that 0.0180737050, 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 65.34000000000015
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0074250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0339921550, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1798.76 < 1811.65
  -> Decision False in time 0.1800000000, query time of that 0.1746421060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1810.65 < 1814.93
  -> Decision False in time 0.9000000000, query time of that 0.8863292710, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0352123490, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1570.93 < 1678.24
  -> Decision False in time 0.1600000000, query time of that 0.1514100320, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1344.66 < 1467.82
  -> Decision False in time 0.4200000000, query time of that 0.4175412640, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1434.28 < 1451.03
  -> Decision False in time 0.0400000000, query time of that 0.0327122450, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1730.11 < 1733.83
  -> Decision False in time 0.2600000000, query time of that 0.1433893730, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1606.42 < 1632.08
  -> Decision False in time 0.1200000000, query time of that 0.0720848910, 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 65.3100000000004
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0023250000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0557519170, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4995590800, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.9300000000, query time of that 4.8668979320, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0550302540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1379.68 < 1387.4
  -> Decision False in time 0.1100000000, query time of that 0.1126909360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1745.06 < 1968.29
  -> Decision False in time 2.7200000000, query time of that 2.6881792230, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.0601223680, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
983.608 < 1037.53
  -> Decision False in time 0.5900000000, query time of that 0.4316979250, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1533.56 < 1542.56
  -> Decision False in time 0.5600000000, query time of that 0.4174218080, 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 33.789999999999964
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000366667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2116555150, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0300000000, query time of that 2.0239503710, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 20.5600000000, query time of that 20.4743239920, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2055091200, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0700000000, query time of that 2.0557540020, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 20.5900000000, query time of that 20.4935928400, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2900000000, query time of that 0.2069302920, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.3200000000, query time of that 2.1251423530, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.4100000000, query time of that 20.9242181380, 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 33.720000000000255
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0002966667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1129049970, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0600000000, query time of that 1.0509574460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.4600000000, query time of that 10.3885347490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1120746540, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1300000000, query time of that 1.1137405040, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 10.8800000000, query time of that 10.7643975780, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1300824820, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1615.74 < 1618.45
  -> Decision False in time 0.9500000000, query time of that 0.9399227960, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1475.18 < 1481.89
  -> Decision False in time 3.8800000000, query time of that 3.8450326030, 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 18.109999999999673
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0229533333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0209522870, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1612.71 < 1756.34
  -> Decision False in time 0.1100000000, query time of that 0.1089459220, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1919.75 < 2032.92
  -> Decision False in time 0.1400000000, query time of that 0.1375530380, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0203511650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1469.06 < 1487.42
  -> Decision False in time 0.0800000000, query time of that 0.0809435320, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1225.16 < 1301.25
  -> Decision False in time 0.0600000000, query time of that 0.0603053290, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1622.03 < 1677.1
  -> Decision False in time 0.0200000000, query time of that 0.0203346550, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1301.24 < 1341.5
  -> Decision False in time 0.1400000000, query time of that 0.0458866190, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1460.38 < 1486.71
  -> Decision False in time 0.1000000000, query time of that 0.0330451970, 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 33.75999999999931
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0008883333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0691901180, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6600000000, query time of that 0.6561788200, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7100000000, query time of that 6.6427133210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0676493470, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7000000000, query time of that 0.6894006590, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1836.96 < 1843.71
  -> Decision False in time 6.9500000000, query time of that 6.8808327410, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0755450330, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1600000000, query time of that 0.8478490800, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1242.2 < 1309.98
  -> Decision False in time 4.2600000000, query time of that 3.7818200530, 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 33.77000000000044
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0024733333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0500000000, query time of that 0.0492097200, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.4600000000, query time of that 0.4487422060, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 4.4500000000, query time of that 4.3955743760, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0600000000, query time of that 0.0471163570, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.5100000000, query time of that 0.4758709780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1731.31 < 1869.76
  -> Decision False in time 2.5600000000, query time of that 2.5289682900, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0553473210, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1428.51 < 1450.8
  -> Decision False in time 0.2500000000, query time of that 0.1756867710, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1806.32 < 1854.81
  -> Decision False in time 0.2400000000, query time of that 0.1631864810, 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 33.94999999999982
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1084833333
  Testing...
|S| = 20
|T| = 283
Reject!
1673.74 < 1704.02
  -> Decision False in time 0.0100000000, query time of that 0.0125449470, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1490.5 < 1531.74
  -> Decision False in time 0.0300000000, query time of that 0.0241630460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1439.17 < 1516.37
  -> Decision False in time 0.1600000000, query time of that 0.1528342820, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0127571640, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1619.69 < 1645.47
  -> Decision False in time 0.0200000000, query time of that 0.0232211130, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1513.58 < 1545.56
  -> Decision False in time 0.0200000000, query time of that 0.0122028490, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1490.35 < 1544.4
  -> Decision False in time 0.0200000000, query time of that 0.0137424530, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
2128.72 < 2152.95
  -> Decision False in time 0.0200000000, query time of that 0.0132716660, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1470.28 < 1482.22
  -> Decision False in time 0.0100000000, query time of that 0.0134055240, 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 33.86000000000058
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0438100000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0171769220, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.1500000000, query time of that 0.1529830260, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1887.11 < 1904.78
  -> Decision False in time 0.0800000000, query time of that 0.0715333990, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0200000000, query time of that 0.0183088360, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1568.93 < 1576.62
  -> Decision False in time 0.0500000000, query time of that 0.0435656800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1222.52 < 1277.39
  -> Decision False in time 0.0200000000, query time of that 0.0158334750, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1504.12 < 1551.78
  -> Decision False in time 0.0100000000, query time of that 0.0173604900, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1327.8 < 1347.49
  -> Decision False in time 0.0200000000, query time of that 0.0178938600, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1977.89 < 2020.17
  -> Decision False in time 0.0200000000, query time of that 0.0177763790, 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 65.40000000000055
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000016667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.6600000000, query time of that 0.6602329390, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 6.2500000000, query time of that 6.2304185420, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 61.7700000000, query time of that 61.6602815190, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.6400000000, query time of that 0.6318455840, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 6.1600000000, query time of that 6.1378938720, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 62.4900000000, query time of that 62.3720687580, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.7200000000, query time of that 0.6434550400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 6.3400000000, query time of that 6.2476610640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 62.7600000000, query time of that 62.5599191220, 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 33.86999999999898
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000033333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3761842600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.7100000000, query time of that 3.7007128600, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 36.8100000000, query time of that 36.7136935490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3712345610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.6600000000, query time of that 3.6429970000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 37.2500000000, query time of that 37.1375288810, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.3715402240, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.9400000000, query time of that 3.7777735950, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 38.0100000000, query time of that 37.4969505200, 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 65.53999999999905
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.3600000000, query time of that 0.3578293260, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 3.4800000000, query time of that 3.4678595070, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 33.8100000000, query time of that 33.7226466210, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.3800000000, query time of that 0.3653484740, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 3.4400000000, query time of that 3.4261355570, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 33.7700000000, query time of that 33.6661177480, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.4500000000, query time of that 0.3624547400, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 3.5900000000, query time of that 3.4586818340, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 34.8500000000, query time of that 34.5980473780, 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:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000300000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2300000000, query time of that 0.2281765010, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.3200000000, query time of that 2.3138304460, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 22.9900000000, query time of that 22.9029058500, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2700000000, query time of that 0.2529844990, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.2600000000, query time of that 2.2419064360, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 23.1300000000, query time of that 23.0281714790, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3300000000, query time of that 0.2521601000, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.5200000000, query time of that 2.3975422180, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 24.0800000000, query time of that 23.6746995250, 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 18.320000000001528
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0098416667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0259464530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2600000000, query time of that 0.2566787750, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1769.62 < 1934.22
  -> Decision False in time 2.0200000000, query time of that 1.9860328080, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1542.4 < 1630.41
  -> Decision False in time 0.0300000000, query time of that 0.0280285370, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1321.2 < 1384.2
  -> Decision False in time 0.2700000000, query time of that 0.2610836980, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1262.4 < 1270.5
  -> Decision False in time 0.5000000000, query time of that 0.4853315550, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1742.31 < 1764.48
  -> Decision False in time 0.0300000000, query time of that 0.0309930490, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1398.02 < 1430.22
  -> Decision False in time 0.1600000000, query time of that 0.0674032400, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1569.54 < 1650.16
  -> Decision False in time 0.0200000000, query time of that 0.0273503520, 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 18.270000000000437
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009950000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0711117650, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.6700000000, query time of that 0.6702274520, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 6.7900000000, query time of that 6.7208617940, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0663738970, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1657.97 < 1689.89
  -> Decision False in time 0.6800000000, query time of that 0.6777863000, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1910.73 < 1925.36
  -> Decision False in time 3.6700000000, query time of that 3.6295559740, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.1600000000, query time of that 0.0835249020, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1100000000, query time of that 0.8761789920, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1720.41 < 1777.36
  -> Decision False in time 2.1400000000, query time of that 1.9566517460, 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 65.17999999999847
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003083333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1100521530, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.0700000000, query time of that 1.0616294660, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 10.7100000000, query time of that 10.6367339340, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1094799650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1661.85 < 1662.65
  -> Decision False in time 0.3400000000, query time of that 0.3355405260, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.0300000000, query time of that 10.9188107460, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1268379600, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.3700000000, query time of that 1.2197640910, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1941.61 < 1969.82
  -> Decision False in time 5.2600000000, query time of that 5.2104888480, 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 66.0
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0009050000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0700000000, query time of that 0.0733940680, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.7300000000, query time of that 0.7167044300, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1676.29 < 1694.88
  -> Decision False in time 4.5600000000, query time of that 4.5221148590, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0800000000, query time of that 0.0728796960, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 0.7700000000, query time of that 0.7453114800, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1717.03 < 1726.41
  -> Decision False in time 1.4100000000, query time of that 1.3912830440, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1737.11 < 1755.85
  -> Decision False in time 0.1100000000, query time of that 0.0783981320, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.1200000000, query time of that 0.9316648570, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1751.91 < 1846.19
  -> Decision False in time 1.8500000000, query time of that 1.7629801760, 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 18.420000000000073
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1197816667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0100328640, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1243.93 < 1417.59
  -> Decision False in time 0.0300000000, query time of that 0.0300836270, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1974.89 < 1988.2
  -> Decision False in time 0.0300000000, query time of that 0.0306964160, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1053.43 < 1115.82
  -> Decision False in time 0.0100000000, query time of that 0.0095474660, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2065.74 < 2084.44
  -> Decision False in time 0.0200000000, query time of that 0.0115953340, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1356.38 < 1463.89
  -> Decision False in time 0.0100000000, query time of that 0.0101612600, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1157.53 < 1267.71
  -> Decision False in time 0.0100000000, query time of that 0.0096689750, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1541.12 < 1562.79
  -> Decision False in time 0.0100000000, query time of that 0.0097093640, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1576.99 < 1578.41
  -> Decision False in time 0.0100000000, query time of that 0.0091011240, 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 66.26999999999862
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000566667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.2200000000, query time of that 0.2145492600, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 2.0400000000, query time of that 2.0344946180, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 19.8300000000, query time of that 19.7402217390, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.2081670620, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 2.0000000000, query time of that 1.9848742090, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 19.8800000000, query time of that 19.7616858240, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.3000000000, query time of that 0.2199087970, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 2.2300000000, query time of that 2.1125435480, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 21.4000000000, query time of that 20.7406289170, 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 65.34000000000015
Index size:  514600.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0172116667
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0300000000, query time of that 0.0249071300, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 0.2500000000, query time of that 0.2360871040, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1543.47 < 1575.5
  -> Decision False in time 0.5200000000, query time of that 0.5127743490, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.0400000000, query time of that 0.0278290650, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
1774.69 < 1790.17
  -> Decision False in time 0.1000000000, query time of that 0.1038609250, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1779.39 < 1834.79
  -> Decision False in time 0.2300000000, query time of that 0.2204030430, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1832.36 < 1867.94
  -> Decision False in time 0.0700000000, query time of that 0.0319153260, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1264.02 < 1280.42
  -> Decision False in time 0.0400000000, query time of that 0.0286793740, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1817.61 < 1827.03
  -> Decision False in time 0.1100000000, query time of that 0.0604284400, 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 18.350000000000364
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0003183333
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.1100000000, query time of that 0.1104914000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 1.1700000000, query time of that 1.1526953490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 11.0000000000, query time of that 10.9229643040, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.1200000000, query time of that 0.1124586610, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 1.1300000000, query time of that 1.1213388780, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 11.2800000000, query time of that 11.1300594310, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.2100000000, query time of that 0.1365361610, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 1.4500000000, query time of that 1.2712578620, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
1475.18 < 1481.89
  -> Decision False in time 3.8200000000, query time of that 3.7843655240, 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 34.39000000000124
Index size:  395800.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.1053650000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.0100000000, query time of that 0.0133384060, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Reject!
1780.06 < 1817.66
  -> Decision False in time 0.0300000000, query time of that 0.0294797760, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Reject!
1165.97 < 1201.22
  -> Decision False in time 0.0200000000, query time of that 0.0147990290, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Reject!
1461 < 1516.37
  -> Decision False in time 0.0100000000, query time of that 0.0120388510, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Reject!
2040.38 < 2159.5
  -> Decision False in time 0.0200000000, query time of that 0.0190275710, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Reject!
1632.8 < 1649.76
  -> Decision False in time 0.0200000000, query time of that 0.0174254320, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Reject!
1783.27 < 1821.31
  -> Decision False in time 0.0100000000, query time of that 0.0117143930, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Reject!
1310.25 < 1324.73
  -> Decision False in time 0.0100000000, query time of that 0.0117854700, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Reject!
2021.86 < 2024.75
  -> Decision False in time 0.0200000000, query time of that 0.0127983360, 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 18.290000000000873
Index size:  304456.0
Run 1/1...
  Calculating distance...
  -> Distance: 0.0000000000
  Testing...
|S| = 20
|T| = 283
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7853878000, with c1=0.0500000000, c2=0.0010000000
|S| = 196
|T| = 283
Accept!
  -> Decision True in time 7.6600000000, query time of that 7.6508211490, with c1=0.0500000000, c2=0.0100000000
|S| = 1960
|T| = 283
Accept!
  -> Decision True in time 76.2800000000, query time of that 76.1573808540, with c1=0.0500000000, c2=0.1000000000
|S| = 20
|T| = 2821
Accept!
  -> Decision True in time 0.7900000000, query time of that 0.7842975430, with c1=0.5000000000, c2=0.0010000000
|S| = 196
|T| = 2821
Accept!
  -> Decision True in time 7.6900000000, query time of that 7.6693751010, with c1=0.5000000000, c2=0.0100000000
|S| = 1960
|T| = 2821
Accept!
  -> Decision True in time 75.9900000000, query time of that 75.8608656390, with c1=0.5000000000, c2=0.1000000000
|S| = 20
|T| = 28201
Accept!
  -> Decision True in time 0.8600000000, query time of that 0.7814644200, with c1=5.0000000000, c2=0.0010000000
|S| = 196
|T| = 28201
Accept!
  -> Decision True in time 7.8500000000, query time of that 7.7541826470, with c1=5.0000000000, c2=0.0100000000
|S| = 1960
|T| = 28201
Accept!
  -> Decision True in time 77.7300000000, query time of that 77.2370102280, with c1=5.0000000000, c2=0.1000000000
