class TUM(chainer.Chain):
def __init__(self, inplanes, scales=6, mingrid=1):
super(TUM, self).__init__()
self.scales = scales
with self.init_scope():
ecs = []
for s in range(scales - 1):
if s == 0:
conv = Conv2DBNActiv(inplanes,
256,
3,
2,
pad=1,
nobias=True)
elif s == scales - 2 and mingrid == 1:
conv = Conv2DBNActiv(256, 256, 3, 2, nobias=True)
else:
conv = Conv2DBNActiv(256, 256, 3, 2, pad=1, nobias=True)
ecs.append(conv)
self.ecs = ChainList(*ecs)
dcs = []
for s in range(scales):
if s == scales - 1:
conv = Conv2DBNActiv(inplanes, 256, 3, pad=1, nobias=True)
else:
conv = Conv2DBNActiv(256, 256, 3, pad=1, nobias=True)
dcs.append(conv)
self.dcs = ChainList(*dcs)
self.scs = ChainList(*[
Conv2DBNActiv(256, 128, 1, nobias=True) for _ in range(scales)
])
def __call__(self, x):
e = x
es = [e]
for conv in self.ecs.children():
e = conv(e)
es.append(e)
d = es[-1]
ds = [d]
for s in range(self.scales - 2):
d = F.resize_images(
self.dcs[s](d),
(es[-(s + 2)].shape[2], es[-(s + 2)].shape[3])) + es[-(s + 2)]
ds.append(d)
d = F.resize_images(
self.dcs[self.scales - 2](d),
(x.shape[2], x.shape[3])) + self.dcs[self.scales - 1](x)
ds.append(d)
ys = []
for s in range(self.scales):
ys.append(self.scs[s](ds[s]))
return ys[::-1]
def __call__(self, X):
Y = X
for layer in ChainList.children(self):
Y = layer(Y)
return Y
