I am experimenting on Deep Belief Nets and the code is available here DBN
Example <http://deeplearning.net/tutorial/code/DBN.py> . There, the trained
model is tested passing it data in batches
test_score_i = theano.function(
[index],
self.errors,
givens={
self.x: test_set_x[
index * batch_size: (index + 1) * batch_size
],
self.y: test_set_y[
index * batch_size: (index + 1) * batch_size
]
}
)
Where the function gives the scores as output. Is there a way that i can
actually get the predicted value?
I tried the follwing code
predict_model = theano.function(
inputs=[test_set_x],
outputs= self.logLayer.y_pred)
But it didn't work. It gave the following error:
theano.compile.function_module.UnusedInputError: theano.function was asked
> to create a function computing outputs given certain inputs, but the
> provided input variable at index 0 is not part of the computational graph
> needed to compute the outputs: Subtensor{:int64:}.0.
>
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