Hardware environment-based data quantization method and apparatus, and readable storage medium

A hardware environment-based data quantization apparatus, comprising a processor configured to execute a computer program stored in a memory to implement any steps of:

• performing parsing according to a model file under a current deep learning framework to obtain intermediate computational graph data and weight data that are independent of a hardware environment;
• performing, based on the intermediate computational graph data and the weight data, calculation on image data in an input data set through a process indicated by an intermediate computational graph to obtain feature map data;
• separately performing uniform quantization on the weight data and the feature map data of each layer according to a preset linear quantization method, and calculating a weight quantization factor and a feature map quantization factor;
• combining the weight quantization factor and the feature map quantization factor to obtain a quantization parameter, wherein the quantization parameter is a parameter that makes hardware use shift instead of division;
• and
• writing the quantization parameter and quantized weight data to a bin file according to a hardware requirement so as to generate quantized file data.

A computer readable storage medium configured to store a hardware environment-based data quantization program that is executed by a processor to implement any steps of:

• performing parsing according to a model file under a current deep learning framework to obtain intermediate computational graph data and weight data that are independent of a hardware environment;
• performing, based on the intermediate computational graph data and the weight data, calculation on image data in an input data set through a process indicated by an intermediate computational graph to obtain feature map data;
• separately performing uniform quantization on the weight data and the feature map data of each layer according to a preset linear quantization method, and calculating a weight quantization factor and a feature map quantization factor;
• combining the weight quantization factor and the feature map quantization factor to obtain a quantization parameter, wherein the quantization parameter is a parameter that makes hardware use shift instead of division;
• and
• writing the quantization parameter and quantized weight data to a bin file according to a hardware requirement so as to generate quantized file data.