QUANTIZATION METHOD FOR NEURAL NETWORK MODEL AND DEEP LEARNING ACCELERATOR
Abstract:
A quantization method for neural network model includes following steps: initializing a weight array of a neural network model, wherein the weight array includes a plurality of initial weights; performing a quantization procedure to generate a quantized weight array according to the weight array, wherein the quantized weight array includes a plurality of quantized weights within a fixed range; performing a training procedure of the neural network model according to the quantized weight array; and determining whether a loss function is convergent in the training procedure and outputting a post-trained quantized weight array when the loss function is convergent.
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