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typo fixed in adaptive reg
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neuralpredictors/layers/readouts/gaussian.py

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@@ -399,7 +399,7 @@ def adaptive_feature_l1_lognorm(self, reduction="sum", average=None):
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)
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# adaptive_neuron_reg_coefs (betas) are supposted to be from lognorm distribution
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coef_prior = 1 / (self.gamma_sigma**2) * ((torch.log(self.adaptive_neuron_reg_coefs.abs()) ** 2).sum())
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return regularization_loss + coef_prior
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return features_regularization + coef_prior
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else:
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return 0
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