forked from PulseFocusPlatform/PulseFocusPlatform
37 lines
1.0 KiB
Bash
37 lines
1.0 KiB
Bash
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# All rights `PaddleDetection` reserved
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#!/bin/bash
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model_dir=$1
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model_name=$2
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export img_dir="demo"
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export log_path="output_pipeline"
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echo "model_dir : ${model_dir}"
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echo "img_dir: ${img_dir}"
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# TODO: support batch size>1
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for use_mkldnn in "True" "False"; do
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for threads in "1" "6"; do
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echo "${model_name} ${model_dir}, use_mkldnn: ${use_mkldnn} threads: ${threads}"
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python deploy/python/infer.py \
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--model_dir=${model_dir} \
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--run_benchmark True \
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--enable_mkldnn=${use_mkldnn} \
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--use_gpu=False \
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--cpu_threads=${threads} \
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--image_dir=${img_dir} 2>&1 | tee ${log_path}/${model_name}_cpu_usemkldnn_${use_mkldnn}_cputhreads_${threads}_bs1_infer.log
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done
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done
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for run_mode in "fluid" "trt_fp32" "trt_fp16"; do
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echo "${model_name} ${model_dir}, run_mode: ${run_mode}"
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python deploy/python/infer.py \
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--model_dir=${model_dir} \
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--run_benchmark=True \
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--use_gpu=True \
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--run_mode=${run_mode} \
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--image_dir=${img_dir} 2>&1 | tee ${log_path}/${model_name}_gpu_runmode_${run_mode}_bs1_infer.log
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done
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