alantian

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

alantian

#!/usr/bin/perl -w

# act as a KSysGuard sensor
# provides NVIDIA GPU temperature via `nvidia-settings`

# Usage
# 1. save this file, make sure it has a exec permission
# 2. in KSysGuard's menu, open `File` -> `Monitor Remote Machine`
# 3.1 in new dialog, type `Host` whatever you want
# 3.2 set `Connection Type` to `Custom command`

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#!/usr/bin/env python3

# KSysGard sensor for NVIDIA GPU temperature. Supports multiple GPUs.
# Needs: Python 3 and nvidia-smi

import subprocess
import xml.etree.ElementTree as ET

def get_xml_tree():
    return ET.fromstring(subprocess.check_output(['nvidia-smi', '-q', '-x']))

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import os
import re

from joblib import Parallel, delayed

def go_lines(lines):
    
    flow = []
    names = []
    

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#!/usr/bin/env python3

import argparse
import os
import sys
from os.path import basename
import cv2
import lmdb
import base64
import glob

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import pickle
import pandas
import json
from collections import Counter
import os
from os.path import join
import shutil

games = pickle.load(open('../../data/game_face_170701/games.pickle', 'rb'), encoding='latin1')
tags = pickle.load(open('../../data/game_face_170701/tags.pickle', 'rb'), encoding='latin1')

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#!/usr/bin/env python2

import os
import numpy as np
import h5py
import threading
import Queue
from PIL import Image
from tqdm import tqdm
from joblib import Parallel, delayed

alantian

FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04

#-------------------------------------------------------------------------------
### Enable UTF8 in docker instance
#-------------------------------------------------------------------------------
RUN apt-get update -y && \
    apt-get install -y locales && \
    rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
RUN locale-gen en_US.UTF-8
ENV LANG='en_US.UTF-8' LANGUAGE='en_US:en' LC_ALL='en_US.UTF-8'

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import os
import sys

from chainer.training import extension
from chainer.training.extensions import log_report as log_report_module
from chainer.training.extensions import util

import tensorflow as tf