AI开发平台MODELARTS-设置训练故障优雅退出:特性使用操作

时间：2024-11-21 19:46:06

AI开发平台MODELARTS

特性使用操作

安装优雅退出二进制包

通过ma_pre_start.sh安装whl包。

echo "[ma-pre-start] Enter the input directory"
cd/home/ma-user/modelarts/inputs/data_url_0/
echo "[ma-pre-start] Start to install mindx-elastic 0.0.1版本"
export PATH=/home/ma-user/anaconda/bin:$PATH
pip install ./mindx_elastic-0.0.1-py3-none-any.whl
echo "[ma-pre-start] Clean run package"
sudo rm -rf ./script ./*.run ./run_package *.whl
echo "[ma-pre-start] Set ENV"
export G LOG _v=1    # 当前使用诊断模式需要用户手动设置成INFO日志级别
echo "[ma-pre-start] End"

创建训练任务

约束：MindSpore版本要求1.6.0及以上。

修改样例代码，增加如下内容：

# 载入依赖接口
from mindx_elastic.terminating_message import ExceptionCheckpoint
...

if args_opt.do_train:
dataset = create_dataset()
loss_cb = LossMonitor()
cb = [loss_cb]
if int(os.getenv('RANK_ID')) == 0:
batch_num = dataset.get_dataset_size()
# 开启优雅退出保存
config_ck = CheckpointConfig(save_checkpoint_steps=batch_num,
keep_checkpoint_max=35,
async_save=True,
append_info=[{"epoch_num": cur_epoch_num}],
exception_save=True)

ckpoint_cb = ModelCheckpoint(prefix="train_resnet_cifar10",
directory=args_opt.train_url,
config=config_ck)
# 定义优雅退出ckpt保存callback
ckpoint_exp = ExceptionCheckpoint(
prefix="train_resnet_cifar10",
directory=args_opt.train_url,
config=config_ck)
# 添加优雅退出ckpt保存callback
cb += [ckpoint_cb, ckpoint_exp]

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