D&A loss & acc fixed and dead,why?
taichu012 opened this issue · 3 comments
I just run this python program of DCGAN with keras, it seems work and after 20 mins, all outputs and numbers are fixed and NEVER changed again, it seems dead, but WHY? output is copied below:
48: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
49: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
50: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
51: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
52: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
53: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
54: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
55: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
56: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
57: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
58: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
59: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
60: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
61: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
62: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
63: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
64: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
65: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
66: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
67: [D loss: 7.971192, acc: 0.500000] [A loss: 0.000000, acc: 1.000000]
I adjusted the learning rate of RMSProp. Pls try again. The output near the end of 10k iteration should appear something like this:
9985: [D loss: 0.697829, acc: 0.535156] [A loss: 0.771172, acc: 0.343750]
9986: [D loss: 0.699841, acc: 0.513672] [A loss: 0.792130, acc: 0.296875]
9987: [D loss: 0.711574, acc: 0.507812] [A loss: 0.842314, acc: 0.199219]
9988: [D loss: 0.697459, acc: 0.521484] [A loss: 0.801781, acc: 0.253906]
9989: [D loss: 0.691388, acc: 0.521484] [A loss: 0.810089, acc: 0.269531]
9990: [D loss: 0.713812, acc: 0.490234] [A loss: 0.838145, acc: 0.210938]
9991: [D loss: 0.703769, acc: 0.478516] [A loss: 0.783158, acc: 0.335938]
9992: [D loss: 0.694213, acc: 0.531250] [A loss: 0.812030, acc: 0.246094]
9993: [D loss: 0.707447, acc: 0.503906] [A loss: 0.876013, acc: 0.156250]
9994: [D loss: 0.689719, acc: 0.556641] [A loss: 0.780946, acc: 0.281250]
9995: [D loss: 0.707479, acc: 0.521484] [A loss: 0.905610, acc: 0.101562]
9996: [D loss: 0.692887, acc: 0.529297] [A loss: 0.709554, acc: 0.511719]
9997: [D loss: 0.702180, acc: 0.523438] [A loss: 0.932314, acc: 0.101562]
9998: [D loss: 0.698255, acc: 0.519531] [A loss: 0.685984, acc: 0.542969]
9999: [D loss: 0.711334, acc: 0.515625] [A loss: 0.925216, acc: 0.085938]
How long does it take to run 10K iterations on a 2.7 GHZ intel Core i5 processor Mac book?
I was at 150 iterations after so many hours? Is there a problem with code, system or I need a GPU?