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Move Away from Assumption of just One Output Layer #158

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cancan101 opened this issue Sep 23, 2015 · 0 comments

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cancan101 commented Sep 23, 2015

Right now there are a number of places that assume one output layer:

nolearn/nolearn/lasagne/base.py

Line 395 in b4a4cb6

output_layer = layers[-1]
nolearn/nolearn/lasagne/base.py

Line 390 in b4a4cb6

return layer
Cleanup initialize and how it calls initialize_layers #157
nolearn/nolearn/lasagne/base.py

Line 143 in 409c5f5

output_layer = layers[-1]

It would be nice to break this assumption and leave it up to the writer of the loss / objective to deal with more than one output layer.

cancan101 mentioned this issue

Multiple network outputs #202

Closed

cancan101 mentioned this issue

Added visualization code using saliency maps #223

Merged

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