Parameter checking in DeconvolutionalLayer for case where with_bn==True and is_training is not passed in.
@@ -189,6 +189,8 @@ class DeconvolutionalLayer(TrainableLayer):
output_tensor = deconv_layer(input_tensor)
if self.with_bn:
+ if is_training is None:
+ raise ValueError('is_training argument should be True or False unless with_bn is False')
bn_layer = BNLayer(
regularizer=self.regularizers['w'],
moving_decay=self.moving_decay,
