The reason why deep neural networks in deep learning generally do not use BP algorithm is:()

A. During feedback adjustment, the gradient becomes more and more sparse, and the error correction signal becomes smaller and smaller from the top layer
B. Convergence is easy to the local minimum, because it is initialized with random values, it is easy to cause this situation when the initial value is far from the optimal area
C. The BP algorithm requires labeled data to train, but most of the data is unlabeled
D. Multi-layer network, only the nodes between adjacent layers are connected and cannot be corrected