cannot reproduce the result you reported

[Kai Li]

By running the code, first training and then test, without changing anything. I got the results below, which are far from being comparable with what you have reported. I use pytorch 0.2.0.4. Any idea on how this happens. Thanks.

test cub***knnsoftmax-model.pkl
[0.48176907 0.61428089 0.74257259 0.84689399]
test cub***knnsoftmax-50_model.pkl
[0.48041864 0.62187711 0.74206617 0.84351789]
test cub***knnsoftmax-100_model.pkl
[0.5035449  0.63740716 0.763842   0.85651587]
test cub***knnsoftmax-200_model.pkl
[0.50303849 0.63723835 0.76164754 0.86090479]
test cub***knnsoftmax-300_model.pkl
[0.50607698 0.6424713  0.76991897 0.86326806]
test cub***knnsoftmax-350_model.pkl
[0.51147873 0.65124916 0.76890614 0.86613774]
  train cub***knnsoftmax-350_model.pkl
[0.58202592 0.696794   0.7941678  0.86834925]
test cub***knnsoftmax-400_model.pkl
[0.5140108  0.64804186 0.77211344 0.86664416]
test cub***knnsoftmax-450_model.pkl
[0.51367319 0.65563808 0.77211344 0.86647535]
test cub***knnsoftmax-500_model.pkl
[0.51536124 0.6492235  0.77599595 0.86866982]
test cub***knnsoftmax-550_model.pkl
[0.51958136 0.65563808 0.7744767  0.86293045]
test cub***knnsoftmax-600_model.pkl
[0.52160702 0.65698852 0.77970966 0.87002026]
  train cub***knnsoftmax-600_model.pkl
[0.62772851 0.73328786 0.82213506 0.88847203]