export CUDA_VISIBLE_DEVICES=0 root_url="https://paddle-inference-dist.bj.bcebos.com/int8" mobilenetv1="mobilenetv1_fp32_model" samples="samples_100" if [ ! -d ${mobilenetv1} ]; then wget ${root_url}/${mobilenetv1}.tgz tar zxf ${mobilenetv1}.tgz fi if [ ! -d ${samples} ]; then wget ${root_url}/${samples}.tgz tar zxf ${samples}.tgz fi python post_training_quantization.py \ --model_dir=${mobilenetv1} \ --data_path=${samples} \ --save_model_path="mobilenetv1_int8_model" \ --algo="KL" \ --is_full_quantize=True \ --batch_size=10 \ --batch_nums=10 \ --use_gpu=True \
