CODEWITHSUNDEEP
c++neural-networktheanolasagne
amanusk
amanusk

Reputation: 242

How can I print the output of a hidden layer in Lasagne

I am trying to use lasgne to train a simple neural network, and to use my own C++ code to do inference. I use the weights generated by lasgne, but I am not able to get good results. Is there a way I can print the output of a hidden layer and/or the calculations themselves? I want to see who it works under the hood, so I can implement it the same way in C++.

Upvotes: 0

Views: 327

Answers (1)

Roxana Istrate
Roxana Istrate

Reputation: 682

I can help with Lasagne + Theano in Python, I am not sure from your question whether you fully work in C++ or you only need the results from Python + Lasagne in your C++ code.

Let's consider you have a simple network like this:

l_in = lasagne.layers.InputLayer(...)
l_in_drop = lasagne.layers.DropoutLayer(l_in, ...)
l_hid1 = lasagne.layers.DenseLayer(l_in_drop, ...)
l_out = lasagne.layers.DenseLayer(l_hid1, ...)

You can get the output of each layer by calling the get_output method on a specific layer:

lasagne.layers.get_output(l_in, deterministic=False) # this will just give you the input tensor
lasagne.layers.get_output(l_in_drop, deterministic=True)
lasagne.layers.get_output(l_hid1, deterministic=True)
lasagne.layers.get_output(l_out, deterministic=True)

When you are dealing with dropout and you are not in the training phase, it's important to remember to call get_output method with the deterministic parameter set to True, to avoid non-deterministic behaviours. This applies to all layers that are preceded by one or more dropout layers.

I hope this answers your question.

Upvotes: 1

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