Abstract: A neural network architecture search method includes: receiving an optimization request, where the optimization request includes a model file and an optimization requirement of a to-be-optimized model, and the optimization requirement includes a performance requirement and a hardware requirement; performing neural architecture search processing in search space based on the model file, to obtain a neural network architecture that meets the optimization requirement; and returning the neural network architecture.

Abstract: A model weight obtaining method includes obtaining structure information of a first neural network model; searching, based on the structure information of the first neural network model, a weight library that stores a plurality of groups of historical weights to obtain a reference weight, where the reference weight is a weight of a second neural network model having a structure similar to that of the first neural network model in the plurality of groups of historical weights; and converting the reference weight to obtain a weight of the first neural network model. In the method, a weight of a neural network model having a structure similar to that of a to-be-trained neural network model is searched for in a weight library, and the weight is converted, to obtain a weight that can be used by the to-be-trained neural network model.