From 8525e7ed3fb098537d89e696c26393f3cfc2c859 Mon Sep 17 00:00:00 2001
From: lubin10 <lubin10@baidu.com>
Date: Fri, 21 Jan 2022 06:31:58 +0000
Subject: [PATCH] add insatll nvidia_dali in prepare.sh

---
 .../ResNet/ResNet50_vd_train_use_dali.txt     | 22 +++++++++++++++++++
 test_tipc/prepare.sh                          |  5 +++++
 2 files changed, 27 insertions(+)
 create mode 100644 test_tipc/config/ResNet/ResNet50_vd_train_use_dali.txt

diff --git a/test_tipc/config/ResNet/ResNet50_vd_train_use_dali.txt b/test_tipc/config/ResNet/ResNet50_vd_train_use_dali.txt
new file mode 100644
index 00000000..9d4bf7f3
--- /dev/null
+++ b/test_tipc/config/ResNet/ResNet50_vd_train_use_dali.txt
@@ -0,0 +1,22 @@
+===========================train_params===========================
+model_name:ResNet50_vd
+python:python3.7
+gpu_list:0|0,1
+-o Global.device:gpu
+-o Global.auto_cast:null|amp
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
+-o Global.output_dir:./output/
+-o DataLoader.Train.sampler.batch_size:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:norm_train
+norm_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Global.use_dali=True
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
diff --git a/test_tipc/prepare.sh b/test_tipc/prepare.sh
index 646e7f4d..18892fb4 100644
--- a/test_tipc/prepare.sh
+++ b/test_tipc/prepare.sh
@@ -108,6 +108,11 @@ if [[ $FILENAME == *GeneralRecognition* ]];then
    exit 0
 fi
 
+if [[ $FILENAME == *use_dali* ]];then
+    python_name=$(func_parser_value "${lines[2]}")
+    ${python_name} -m pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/nightly --upgrade nvidia-dali-nightly-cuda102
+fi
+
 if [ ${MODE} = "lite_train_lite_infer" ] || [ ${MODE} = "lite_train_whole_infer" ];then
     # pretrain lite train data
     cd dataset
-- 
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