megengine.module.init.xavier_normal_#
- xavier_normal_(tensor, gain=1.0)[source]#
Fills tensor with random values sampled from \(\mathcal{N}(0, \text{std}^2)\) where
\[\text{std} = \text{gain} \times \sqrt{\frac{2}{\text{fan_in} + \text{fan_out}}}\]Also known as Glorot initialization. Detailed information can be retrieved from Understanding the difficulty of training deep feedforward neural networks - Glorot, X. & Bengio, Y. (2010).