Get output from Lasagne (python deep neural network framework)

Question

I loaded the mnist_conv.py example from official github of Lasagne.

At the and, I would like to predict my own example. I saw that \"lasagne.layers.get_output()\" should

Answer 1

First you try pass a single "image" into your network, which so it has the dimension (256,256).

But it need a list of 3 dimensional data i.e. images, which in theano is implemented as 4D tensor.

I don't see your full code, how you intended to use lasagne's interface, but if your code is written properly, from what I saw so far, I think you should convert your (256,256) data first to a one single channel image like (1,256,256), then make a list from either use more (1,256,256) data passed in a list e.g. [(1,256,256), (1,256,256), (1,256,256)], or make a list from this single example like [(1,256,256)]. Former you get and then pass a (3,1,256,256), latter a (1,1,256,256) 4D tensor, which will be accepted by lasagne interface.