12/06/2019

using specific gpu device for TensorFlow

setting first or second gpu machine
CUDA_VISIBLE_DEVICES=0 python script_one.py
CUDA_VISIBLE_DEVICES=1 python script_two.py
another way
use first (it didn't work for me)
export CUDA_VISIBLE_DEVICE=0
./train.py
use second (it didn't work for me)
export CUDA_VISIBLE_DEVICE=1
./train.py
use both (it didn't work for me)
export CUDA_VISIBLE_DEVICE=0,1
./train.py

refer to here:
https://stackoverflow.com/questions/44135538/tensorflow-using-2-gpu-at-the-same-time

12/05/2019

monitoring gpu status in command (terminal)



pip install gpustat
>gpustat -cp




monitoring continuously
>watch -n 0.5 -c gpustat -cp --color


12/03/2019

find pdf file (or some exe file) in directories and copy it to another directory, python sample code


import os
import glob
from shutil import copyfile


files = []
start_dir = '/Volumes/input/'
output_path = '/Volumes/output/'
pattern = "*.pdf"

total = 0
for dir,_,_ in os.walk(start_dir):
files.extend(glob.glob(os.path.join(dir,pattern)))
for i,v in enumerate(files):
#found pdf files
print(total,i,v)
#extract filename only
filename = v.split('/')[-1]
#make new filename and output path
output_filename = output_path + str(total) + '_' + filename
#if file exist? then no copy
exist = glob.glob(output_filename)
#if not copy
if len(exist) == 0:
copyfile(v, output_filename)
#print out copied filename
print('copy! : ', output_filename)
#increase global count
total += 1