Method and apparatus for training a model

An apparatus for model training, comprising:

• a first training unit configured to train a first model to obtain a parameter set of the trained first model, wherein a plurality of first layers in the first model share same weight parameters;
• a parameter copying unit configured to copy the parameter set for a plurality of times as weight parameters of a plurality of second layers of a second model;
• and
• a second training unit configured to train the second model to realize model convergence,
• wherein the first model and the second model have a same computation graph, and the number of the plurality of second layers is equal to or greater than the number of the plurality of first layers.

A server, comprising:

• one or more processors, and
• a plurality of model acceleration units, wherein the one or more processors and the plurality of model acceleration units are configured to execute a set of instructions to cause the server to perform:
• training a first model to obtain a parameter set of the trained first model, wherein a plurality of first layers in the first model share same weight parameters;
• copying the parameter set for a plurality of times as weight parameters of a plurality of second layers of a second model;
• and
• training the second model to realize model convergence,
• wherein the first model and the second model have a same computation graph, and the number of the plurality of second layers is equal to or greater than the number of the plurality of first layers.