小编emo*_*ain的帖子

我想使用 PyTorch 实现非负矩阵分解。这是我最初的实现：

def nmf(X, k, lr, epochs):
    # X: input matrix of size (m, n)
    # k: number of latent factors
    # lr: learning rate
    # epochs: number of training epochs
    m, n = X.shape
    W = torch.rand(m, k, requires_grad=True)  # initialize W randomly
    H = torch.rand(k, n, requires_grad=True)  # initialize H randomly
    # training loop
    for i in range(epochs):
        # compute reconstruction error
        loss = torch.norm(X - torch.matmul(W, H), p='fro')
        # compute gradients
        loss.backward()
        # update parameters using …