Add 1D support to TF u_net
@@ -57,7 +57,7 @@ Restrictions:
else:
raise NotImplementedError()
y = y + res_in
- y = y.padded([[0, 1], [0, 1]])
+ y = y.padded([[0, 1]] * y.rank)
if resolutions:
level_filters = filters if isinstance(filters, int) else reversed(filters)[level]
y = conv_layer(y, level_filters, kernel_size=2, activation=tf.nn.relu, padding='valid', name='up_convolution_%d' % level, trainable=trainable, reuse=reuse)
