lasagne.layers.Conv2DLayer default adds bias

[mee1o]

So no need to use lasagne.layers.BiasLayer

I found this when I print the shape of arrays in file fft_1024.pkl (iKala dataset)

These are the shapes and bias array (30,) occurs twice for each convolutional layer.

(30, 1, 1, 30) (30,) (30,) (30, 30, 10, 20) (30,) (30,) (13230, 256) (256,) (256, 13230) (13230,) (256, 13230) (13230,) (2,)

I also checked the code of lasagne.layers.Conv2DLayer, it confirms my assumption.

[nkundiushuti]

thanks! I wasn't aware that lasagne adds the bias by default. though I don't think it damages the performance or significantly slows down training

[nkundiushuti]

we will preserve this to be backwards compatible with the model we sent to MIREX in 2016