This also failed :
import theano.tensor as T
def weighted_crossentropy(predictions, targets):
weights_per_label = theano.shared(lasagne.utils.floatX([0.2, 0.4]))
weights = weights_per_label[targets] # returns a targets-shaped weight
matrix
loss =
lasagne.objectives.aggregate(T.nnet.categorical_crossentropy(predictions,
targets), weights=weights)
return loss
loss_or_grads = weighted_crossentropy(prediction, self.target_var)
//
TypeError: index must be integers
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