Plt update 006 (#2914)

* add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * add plt export, test=model * fix plt start, test=model * fix plt start, test=model * fix plt start, test=model * fix plt start, test=model * fix plt perf, test=model * add plt bm ignore, test=model * update plt start.sh, test=model
PaddlePaddle · Aug 5, 2024 · eaad66b · eaad66b
1 parent 8245844
commit eaad66b
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diff --git a/framework/e2e/PaddleLT_new/start.sh b/framework/e2e/PaddleLT_new/start.sh
@@ -1,11 +1,12 @@
 #!/usr/bin/env bash
 
-# 最外层执行脚本
+# 最外层执行脚本, 不可用于CI
 test_scene=$1
 source ./PTSTools/tools/set_env/set_env.sh ${PTS_ENV_VARS}  # 设定PTS环境变量
 source ./set_docker_env.sh # 设定docker环境相关参数
 
-docker_name="PaddleLayerTest_${AGILE_PIPELINE_BUILD_NUMBER}"
+export docker_name=${DOCKER_NAME:-PaddleLayerTest_${AGILE_PIPELINE_BUILD_NUMBER}}
+docker container ls -a --filter "name=${docker_name}" --format "{{.ID}}" | xargs -r docker rm -f
 
 nvidia-docker run --rm -i --name ${docker_name} --privileged --shm-size=128g --net=host \
   -w /workspace \

diff --git a/framework/e2e/PaddleLT_new/start_perf_a100.sh b/framework/e2e/PaddleLT_new/start_perf_a100.sh
@@ -5,12 +5,14 @@ test_scene=$1
 source ./PTSTools/tools/set_env/set_env.sh ${PTS_ENV_VARS}  # 设定PTS环境变量
 source ./set_docker_env.sh # 设定docker环境相关参数
 
-docker_name="PaddleLayerTest_perf_${AGILE_PIPELINE_BUILD_NUMBER}"
 export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
 export DEVICES="$(\ls -d /dev/nvidia* | xargs -I{} echo '-v {}:{}') $(\ls /dev/nvidia-caps/* | xargs -I{} echo '-v {}:{}')"
 RUN_IMAGE_NAME=iregistry.baidu-int.com/paddlecloud/base-images:paddlecloud-ubuntu18.04-gcc8.2-cuda11.8-cudnn8.6-nccl2.15.5
 
 if [ $PLT_PERF_CONTENT == "layer" ];then
+export docker_name=${DOCKER_NAME:-PaddleLayerTest_perf_${AGILE_PIPELINE_BUILD_NUMBER}}
+docker container ls -a --filter "name=${docker_name}" --format "{{.ID}}" | xargs -r docker rm -f
+
 docker run --rm -i --name=${docker_name} --network=host --privileged -v /usr/bin/nvidia-smi:/usr/bin/nvidia-smi \
 ${DEVICES} ${CUDA_SO} -v ${PWD}:/workspace \
   -w /workspace \
@@ -41,6 +43,8 @@ ${python_ver} run.py
 "
 
 elif [ $PLT_PERF_CONTENT == "kernel" ];then
+export docker_name=${DOCKER_NAME:-PaddleLayerTest_perf_${AGILE_PIPELINE_BUILD_NUMBER}}
+docker container ls -a --filter "name=${docker_name}" --format "{{.ID}}" | xargs -r docker rm -f
 
 docker exec -e "PLT_DEVICE_ID=${PLT_DEVICE_ID}" \
   -e "AK=${AK}" -e "SK=${SK}" \
@@ -51,7 +55,7 @@ docker exec -e "PLT_DEVICE_ID=${PLT_DEVICE_ID}" \
   -e "python_ver=${python_ver}" \
   -e "wheel_url=${wheel_url}" \
   -e "AGILE_PIPELINE_BUILD_ID=${AGILE_PIPELINE_BUILD_ID}" \
-  ${PLT_PERF_DOCKER_NAME} \
+  ${docker_name} \
   /bin/bash -c "
 ldconfig;
 ps aux | grep python | awk '{print $2}' | xargs kill -9