def build(inp, encoder, nc, valid_shapes):
side = conv_block_side(inp)
x = Lambda(
interp,
arguments={'shape': valid_shapes[3]},
name='sub24_sum_interp')(encoder)
main = ConvBN(
filters=128,
kernel_size=3,
dilation_rate=2,
padding='same',
name='conv_sub2')(x)
x = Add(name='sub12_sum')([main, side])
x = Activation('relu')(x)
x = Lambda(
interp,
arguments={'shape': valid_shapes[2]},
name='sub12_sum_interp')(x)
x = Conv2D(
filters=nc,
kernel_size=1,
name='conv6_cls')(x)
out = Lambda(
interp,
arguments={'shape': valid_shapes[0]},
name='conv6_interp')(x)
return out
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