Image segmentation model quantization method and apparatus, computer device, and storage medium

An image segmentation model quantization apparatus comprising:

• a memory storing a plurality of instructions;
• and
• a processor configured to execute the plurality of instructions, and upon execution of the plurality of instructions, the processor is configured to:
• acquire a first image segmentation model, the first image segmentation model comprising a plurality of first operators, a concatenation layer, and a second operator, wherein outputs of the first operators are inputs of the concatenation layer, each first operator of the plurality of first operators comprises a first quantization operator and a first dequantization operator, the second operator comprises a second quantization operator and a second dequantization operator, and an output of the concatenation layer is an input of the second operator;
• determine an input range of each of the plurality of first operators and the second operator, and continue iteratively updating a quantization parameter of each operator based on the input range of each operator and a target output range, until the quantization parameter of each operator converges to a quantization parameter corresponding to the target output range, the quantization parameter corresponding to the target output range being used for quantizing any data into the target output range;
• quantize a network parameter of the concatenation layer based on the quantization parameter corresponding to the target output range, to obtain a quantized image segmentation model;
• delete the first dequantization operator from each first operator, and delete the second quantization operator from the second operator;
• and
• call the quantized image segmentation model to perform an image segmentation task.

A non-transitory computer-readable storage medium storing a plurality of instructions executable by a processor, wherein upon execution by the processor, the plurality of instructions is configured to cause the processor to:

• acquire a first image segmentation model, the first image segmentation model comprising a plurality of first operators, a concatenation layer, and a second operator, wherein outputs of the first operators are inputs of the concatenation layer, each first operator of the plurality of first operators comprises a first quantization operator and a first dequantization operator, the second operator comprises a second quantization operator and a second dequantization operator, and an output of the concatenation layer is an input of the second operator;
• determine an input range of each of the plurality of first operators and the second operator, and continue iteratively updating a quantization parameter of each operator based on the input range of each operator and a target output range, until the quantization parameter of each operator converges to a quantization parameter corresponding to the target output range, the quantization parameter corresponding to the target output range being used for quantizing any data into the target output range;
• quantize a network parameter of the concatenation layer based on the quantization parameter corresponding to the target output range, to obtain a quantized image segmentation model;
• delete the first dequantization operator from each first operator, and delete the second quantization operator from the second operator;
• and
• call the quantized image segmentation model to perform an image segmentation task.