809d0e5b52561fefd3b0d98c08d3cbb175d7e706,onmt/modules/Util.py,LayerNorm,forward,#LayerNorm#Any#,35

Before Change

    def forward(self, z):
        if z.size(1) == 1:
            return z
        mu = torch.mean(z, dim=1).unsqueeze(1)
        sigma = torch.std(z, dim=1).unsqueeze(1)
        ln_out = (z - mu.expand_as(z)) / (sigma.expand_as(z) + self.eps)
        ln_out = ln_out * self.a_2.expand_as(ln_out) \
            + self.b_2.expand_as(ln_out)

After Change

        mu = torch.mean(z, dim=1)
        sigma = torch.std(z, dim=1)
        // HACK. PyTorch is changing behavior 
        if mu.dim() == 1:
            mu = mu.unsqueeze(1)
            sigma = sigma.unsqueeze(1)
        ln_out = (z - mu.expand_as(z)) / (sigma.expand_as(z) + self.eps)
        ln_out = ln_out.mul(self.a_2.expand_as(ln_out)) \
            + self.b_2.expand_as(ln_out)
        return ln_out

Instances