Understanding BCE Loss In PyTorch
BCELoss() computes binary cross-entropy loss between input and target tensors. It can be initialized with weight and reduction arguments.
Buy Me a Coffee☕ *Memos: My post explains BCE(Binary Cross Entropy) Loss. My post explains BCEWithLogitsLoss(). My post explains CrossEntropyLoss(). BCELoss() can get the 0D or more D tensor of the zero or more values(float) computed by BCE Loss from the 0D or more D tensor of zero or more elements as shown below: *Memos: The 1st argument for initialization is weight(Optional-Default:None-Type:tensor of int, float or bool): *Memos: If it's not given, it's 1. It must be the 0D or more D tensor of zero or more elements. There is reduction argument for initialization(Optional-Default:'mean...