Method And System Of Compressing Neural Network Models Based On Network Architecture Design

Abstract: A method and system of compressing a neural network model (NNM) is disclosed. The method includes determining filter contribution information and position wise contribution information of each of the plurality of layers based on a total number of the plurality of layers in the NNM, a total number of the plurality of filters in the NNM, and a number of filters in each of the plurality of layers. A layer score is determined based on a type of layer for each of the plurality of layers and a predefined scoring criteria. A pruning control parameter is determined of each of the plurality of layers based on the layer score, the filter contribution information and the position wise contribution information of the corresponding layers. A layer-wise pruning rate is determined of each of the plurality of layers based on the pruning control parameter and the pre-defined pruning ratio. [To be published with FIG. 1]

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