def run():
dims = 20
negrate = 1
batsize = 100
epochs = 3000
path = "../../data/Family/SN-"
traind, valid, test = family.getdata(path)
lemb = VectorEmbed.indim(traind.numsubjs+2).outdim(dims).Wreg(l2reg(0.000001))()
remb = VectorEmbed.indim(traind.numsubjs+2).outdim(dims).Wreg(l2reg(0.000001))()
inp = Input(T.imatrix())
out = ((inp[:, 0] >> lemb) & (inp[:, 2] >> remb)) >> DotProduct() >> Sigmoid()
outtest = Output(T.fvector())
loss = (out & outtest) >> MSELoss()
trainer = Trainer\
.batsize(batsize)\
.epochs(epochs)\
.onrun(getonrun())\
.offrun(offrun)\
.offepoch(getoffepoch(out))\
.onbatch(getonbatch(negrate))\
.optimizer(sgd(lr=1.))\
.batchtransformer(transbat)
trainer\
.loss(loss)\
trainer.train(traind, valid)\
.test(test)
def run():
dims = 60
negrate = 1
batsize = 100
epochs = 800
path = "../../data/Family/SN-"
traind, valid, test = family.getdata(path)
semb = VectorEmbed.indim(traind.numsubjs+2).outdim(dims).Wreg(l2reg(0.000000001))()
oemb = VectorEmbed.indim(traind.numsubjs+2).outdim(dims).Wreg(l2reg(0.000000001))()
remb = MatrixEmbed.indim(traind.numrels).outdim(dims).idxoffset(traind.numsubjs+2).Wreg(l2reg(0.000000001))()
inp = Input(T.imatrix())
sembvec = (inp[:, 0] >> semb)
sremb = (inp[:, 1] & sembvec) >> remb
out = (sremb & (inp[:, 2] >> oemb)) >> DotProduct() >> Sigmoid()
print out(np.asarray([[1, 720, 6]], dtype="int32"))
outtest = Output(T.fvector())
loss = (out & outtest) >> MSELoss()
trainer = Trainer\
.batsize(batsize)\
.epochs(epochs)\
.onrun(getonrun())\
.offrun(offrun)\
.offepoch(getoffepoch(out))\
.onbatch(getonbatch(negrate))\
.optimizer(sgd(lr=1.))\
.batchtransformer(transbat)
trainer\
.loss(loss)\
trainer.train(traind, valid)\
.test(test)
