Understanding Layer Normalization In PyTorch
Layer Normalization explained: LayerNorm() computes mean & variance for each feature dimension, normalizing inputs to have 0 mean & unit variance.
Buy Me a Coffee☕ *Memos: My post explains Layer Normalization. My post explains BatchNorm1d(). My post explains BatchNorm2d(). My post explains BatchNorm3d(). My post explains requires_grad. LayerNorm() can get the 1D or more D tensor of the zero or more elements computed by Layer Normalization from the 1D or more D tensor of zero or more elements as shown below: *Memos: The 1st argument for initialization is normalized_shape(Required-Type:int, tuple or list of int or torch.Size). *It must be 0 <= x. The 2nd argument for initialization is eps(Optional-Default:1e-05-Type:float). The 3rd arg...