The initialization done is same as in the docs. The implementation simply uses the kaiming_uniform_  function (torch.nn.init — PyTorch 1.7.0 documentation 2) and passes the right parameter to get a uniform distribution in (-1/sqrt(in_features),1/sqrt(in_features)) . In Kaiming uniform initialization, there is an extra sqrt(3). So they’ve made the gain value 1/sqrt(3) using
gain = torch.nn.init.calculate_gain(nonlinearity='leaky_relu', param=math.sqrt(5))

Check pytorch/init.py at 4ff1823fac8833d4bdfe333c49fd486143175395 · pytorch/pytorch · GitHub 1.
Seems like a workaround to avoid writing another function that might duplicate code in kaiming_uniform_