@wraps(Cost.expr)
    def expr(self, model, data, **kwargs):
        X = data
        p = self.p
        p_hat = tensor.abs_(model.encode(X)).mean(axis=0)
        kl = p * tensor.log(p / p_hat) + (1 - p) * \
            tensor.log((1 - p) / (1 - p_hat))
        penalty = self.coeff - kl.sum()
        penalty.name = 'sparse_activation_penalty'
        return penalty
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/costs/autoencoder.py/SparseActivation.expr/operator `*` -> `-`