Yixin Liu commited on
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1 Parent(s): 23b9bfb

update readme

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Files changed (4) hide show
  1. Procfile +1 -0
  2. main.py +126 -0
  3. requirements.txt +3 -0
  4. setup.sh +13 -0
Procfile ADDED
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+ web: sh setup.sh && streamlit run main.py
main.py ADDED
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+ # import imp
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+ import streamlit as st
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+ import pandas as pd
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+ import numpy as np
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+ import time
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+ # import matplotlib.pyplot as plt
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+ # import seaborn as sns
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+ # import plotly.figure_factory as ff
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+ # import altair as alt
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+ # from PIL import Image
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+ # import base64
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+ # import tarfile
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+ # import os
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+ # import requests
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+
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+
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+
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+ # title
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+ st.title("Exp Command Generator")
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+
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+ ## 检查框
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+ debug = st.checkbox("Debug:选择则会串行地执行命令", value=True)
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+ # st.write(f"checkbox的值是{res}")
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+
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+ setup = st.text_area("Some setup of env at beginning.", """cd $(dirname $(dirname $0))
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+ source activate xai
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+ export PYTHONPATH=${PYTHONPATH}:/Users/apple/Desktop/workspace/research_project/attention:/mnt/yixin/:/home/yila22/prj""")
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+
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+ exp_hyper = st.text_area("Hyperparameters", """exp_name="debug-adv-training-emotion"
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+ dataset=emotion
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+ n_epoch=3
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+ K=3
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+ encoder=bert
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+ lambda_1=1
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+ lambda_2=1
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+ x_pgd_radius=0.01
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+ pgd_radius=0.001
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+ seed=2
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+ bsize=8
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+ lr=5e-5""")
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+
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+ ## gpu 相关参数
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+ gpu_list = st.multiselect("multi select", range(10), [1, 2, 3, 4, 5, 6, 7, 8, 9])
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+ print(gpu_list)
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+ allow_gpu_memory_threshold = st.number_input("最小单卡剩余容量", value=5000, min_value=0, max_value=30000, step=1000)
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+ gpu_threshold = st.number_input("最大单卡利用率", value=70, min_value=0, max_value=100, step=10)
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+ sleep_time_after_loading_task= st.number_input("加载任务后等待秒数", value=20, min_value=0,step=5)
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+ all_full_sleep_time = st.number_input("全满之后等待秒数", value=20, min_value=0,step=5)
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+
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+ gpu_list_str = ' '.join([str(i) for i in gpu_list])
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+ gpu_hyper = f"gpu=({gpu_list_str})\n"
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+ gpu_hyper+=f"allow_gpu_memory_threshold={allow_gpu_memory_threshold}\n"
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+ gpu_hyper+=f"gpu_threshold={gpu_threshold}\n"
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+ gpu_hyper+=f"sleep_time_after_loading_task={sleep_time_after_loading_task}s\n"
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+ gpu_hyper+=f"all_full_sleep_time={all_full_sleep_time}s\n"
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+ gpu_hyper+=f"gpunum={len(gpu_list)}\n"
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+
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+ main_loop = st.text_area("Main loop", """for lambda_1 in 1 3;do
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+ for lambda_2 in 1 10;do
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+ for n_epoch in 3;do
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+ for x_pgd_radius in 0.005 0.01;do
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+ for pgd_radius in 0.0005 0.001 0.002;do
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+ python train.py --dataset $dataset --data_dir . --output_dir ./outputs/ --attention tanh \
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+ --encoder $encoder \
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+ --exp_name $exp_name --lambda_1 $lambda_1 --lambda_2 $lambda_2 --pgd_radius $pgd_radius --x_pgd_radius $x_pgd_radius \
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+ --K $K --seed $seed --train_mode adv_train --bsize $bsize --n_epoch $n_epoch --lr $lr \
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+ --eval_baseline
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+ done;done;done;done;done;""")
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+
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+ hyper_loop = main_loop.split("python")[0]
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+ print(hyper_loop)
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+ python_cmd = main_loop.split(";do\n")[-1].split('done;')[0]
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+ print(python_cmd)
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+ end_loop = "done;"*hyper_loop.count("\n")
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+ print(end_loop)
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+
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+
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+ g = st.button("Generate")
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+ if g:
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+ s = ""
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+ s += setup + "\n\n"
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+ s += exp_hyper + "\n\n"
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+ s += gpu_hyper + "\n\n"
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+ s += hyper_loop + "\n\n"
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+ s += """
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+ i=0 # we search from the first gpu
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+ while true; do
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+ gpu_id=${gpu[$i]}
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+ # nvidia-smi --query-gpu=utilization.gpu --format=csv -i 2 | grep -Eo "[0-9]+"
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+ gpu_u=$(nvidia-smi --query-gpu=utilization.gpu --format=csv -i $gpu_id | grep -Eo "[0-9]+")
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+ free_mem=$(nvidia-smi --query-gpu=memory.free --format=csv -i $gpu_id | grep -Eo "[0-9]+")
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+ if [[ $free_mem -lt $allow_gpu_memory_threshold || $gpu_u -ge ${gpu_threshold} ]]; then
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+ i=`expr $i + 1`
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+ i=`expr $i % $gpunum`
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+ echo "gpu id ${gpu[$i]} is full loaded, skip"
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+ if [ "$i" == "0" ]; then
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+ sleep ${all_full_sleep_time}
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+ echo "all the gpus are full, sleep 1m"
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+ fi
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+ else
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+ break
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+ fi
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+ done
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+
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+ gpu_id=${gpu[$i]}
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+ free_mem=$(nvidia-smi --query-gpu=memory.free --format=csv -i $gpu_id | grep -Eo "[0-9]+")
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+ gpu_u=$(nvidia-smi --query-gpu=utilization.gpu --format=csv -i $gpu_id | grep -Eo "[0-9]+")
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+ export CUDA_VISIBLE_DEVICES=$gpu_id
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+ echo "use gpu id is ${gpu[$i]}, free memory is $free_mem, it utilization is ${gpu_u}%"
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+ """
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+ s += f"""com="{python_cmd}"\n"""
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+ s += "echo $com\n"
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+ s += "echo ==========================================================================================\n"
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+ if debug:
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+ s += "$com\n"
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+ else:
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+ s += "mkdir -p ./logs/\n"
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+ s += "nohup $com > ./logs/$exp_name-$RANDOM.log 2>&1 &\n"
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+ s += """echo "sleep for $sleep_time_after_loading_task to wait the task loaded"
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+ sleep $sleep_time_after_loading_task\n"""
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+ s += end_loop
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+ st.success("Finished")
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+ st.code(s, language="shell")
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+
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+
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+
requirements.txt ADDED
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+ numpy
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+ streamlit
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+ pandas
setup.sh ADDED
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+ mkdir -p ~/.streamlit/
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+
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+ echo "\
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+ [general]\n\
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+ email = \"yila22@lehigh.edu\"\n\
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+ " > ~/.streamlit/credentials.toml
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+
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+ echo "\
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+ [server]\n\
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+ headless = true\n\
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+ enableCORS=false\n\
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+ port = $PORT\n\
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+ " > ~/.streamlit/config.toml