Method and device for model compression

A device comprising:

• at least one processor;
• and
• a storage medium storing computer-readable instructions,
• wherein the instructions are executed by the at least one processor to cause the at least one processor to:
• receive a deep learning model loaded on a target device and a computation list supported by a model converter for the target device,
• determine whether a computation for each layer of the deep learning model is able to be accelerated on the target device based at least in part on the computation list,
• acquire a compressed model by maintaining a computation corresponding to one layer as it is, and applying a compression technique to the deep learning model when the one layer of the deep learning model is determined to include a computation unable to be accelerated on the target device,
• acquire the compressed model by changing the computation corresponding to the one layer to another computation, and then applying the compression technique to the deep learning model when the one layer is determined to include the computation able to be accelerated on the target device, and
• add a model component of the compressed model to a compressed model component database.