54691f9be052e5564ca0e5c6a503e641ea3142e1,keras/layers/normalization.py,BatchNormalization,output,#BatchNormalization#Any#,23

Before Change

    def output(self, train):
        X = self.get_input(train)
        X_normed = (X - X.mean(keepdims=True)) / (X.std(keepdims=True) + self.epsilon)
        out = self.gamma * X_normed + self.beta
        return out

After Change

        X = self.get_input(train)

        if self.mode == 0:
            m = X.mean(axis=0)
            // manual computation of std to prevent NaNs
            std = T.mean((X-m)**2 + self.epsilon, axis=0) ** 0.5
            X_normed = (X - m) / (std + self.epsilon)

        elif self.mode == 1:
            m = X.mean(axis=-1, keepdims=True)
            std = X.std(axis=-1, keepdims=True)

Instances