'Apply one linear transformation that captures normalization, gamma scaling and beta shift.'

def _fprop_inference(self, inputs, beta=0.0):

    xhat = ((inputs - self.gmean) / self.be.sqrt((self.gvar + self.eps)))
    self.y[:] = (((self.y * beta) + (xhat * self.gamma)) + self.beta)
    return self.outputs
