meta_cal/pido_test.sh

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#!/bin/bash
#SBATCH --job-name=run_node05 # 作业名称
#SBATCH --output=pidn_output_%j # 标准输出文件(%j 会被替换为作业 ID
#SBATCH --error=pidn_error_%j.txt # 标准错误文件(%j 会被替换为作业 ID
#SBATCH --time=100:00:00 # 运行时间限制
#SBATCH --partition=gpu # 请求 GPU 分区
#SBATCH --cpus-per-task=10 # 节点请求的cpu核心数
#SBATCH --mem=128G # 请求内存大小
#SBATCH --gres=gpu:7 # 请求 4 个 GPU 资源
#SBATCH --nodelist=node06 # 指定使用 node06 节点
# 激活虚拟环境
eval "$(/public/apps/miniconda3/bin/conda shell.bash hook)"
conda activate deepnet
# 切换到存放 Python 脚本的目录
cd /public/home/cw/meta_cal/20260304_FNO_512
# 执行 Python 脚本
torchrun --nproc_per_node=7 PI_code_test_FNO.py