def visitClassicBatches(nn, data, labels, val_d, val_l, l, test_val, it=1000):
for c in range(it):
for cc in range(len(data)):
nnS.minibatch_fit(nn, data[cc], labels[cc])
if c % 10 == 0:
acc = accuracy(nn, val_d, val_l, thr=0.5)
l[test_val][c / 10] = acc
print acc
def visitClassicBatches(nn,data,labels, val_d, val_l, l, test_val, it=1000):
for c in range(it):
for cc in range(len(data)):
nnS.minibatch_fit(nn, data[cc], labels[cc])
if c %10 == 0:
acc = accuracy(nn, val_d, val_l, thr = 0.5)
l[test_val][c/10] = acc
print acc
def visitClassicBatches(nn,data,labels, it=1000):
for c in range(it):
for cc in range(len(data)):
nnS.minibatch_fit(nn, data[cc], labels[cc])
def visitClassicBatches(nn, data, labels, it=1000):
for c in range(it):
for cc in range(len(data)):
nnS.minibatch_fit(nn, data[cc], labels[cc])