def _select_update(self, y, train_ref, is_train):
if train_ref is not None and is_train:
# Training
wt = train_ref
else:
# Testing
wt = Variable(self._xp.array(UF.argmax(y.data), dtype=np.int32))
return wt
def collect_output(src_col, output, alignment, out):
y = UF.argmax(out.y.data)
for i in range(len(y)):
output[i][src_col] = y[i]
a = out.a
if a is not None:
for i, x in enumerate(a.data):
for j, x_a in enumerate(x):
alignment[i][src_col][j] = float(x_a)