rumansaleem

Contents

• Clean pkg cache
• Remove unused packages (orphans)
• Clean cache in /home
• remove old config files
• Find and Remove
  • duplicates
  • empty files
  • empty directories
• broken symlinks

JoeyBurzynski

58 bytes of CSS to look great nearly everywhere

When making this website, i wanted a simple, reasonable way to make it look good on most displays. Not counting any minimization techniques, the following 58 bytes worked well for me:

main {
  max-width: 38rem;
  padding: 2rem;
  margin: auto;
}

dreikanter

Symmetic encryption

For symmetic encryption, you can use the following:

To encrypt:

openssl aes-256-cbc -salt -a -e -in plaintext.txt -out encrypted.txt

To decrypt:

mikoim

Parameters

Container: MP4

Parameter	YouTube recommends setting
-movflags faststart	moov atom at the front of the file (Fast Start)

Video codec: H.264

Misairu-G

Reddit post (Archived)

Table of Content

• What to expect?
  • Some TLDR about the idea behind
• Prerequisites
  • Hardware
  • System & Software
• Update: Attention for MUXless laptop

lolo32

CLang optimizations on Mac OSX

Version:

Apple LLVM version 6.0 (clang-600.0.57) (based on LLVM 3.5svn)
Target: x86_64-apple-darwin14.1.0
Thread model: posix

This was made with commands:

oldcai

import time
import requests
import zlib
#!pip install lz4 pylzma zstd
import lz4.block
import pylzma as lzma
import zstd

def measure_time_and_compress_decompress(compress_func, decompress_func, data, *args):
    # Measure compression time

xerpi

Step 1: Compiling or Downloading the toolchain

Step 1.a: If you choose to download a pre-compiled toolchain (only for Linux x86-64)

• Go to https://toolchains.bootlin.com
• Select arch: armv6-eabihf
• Select libc: glibc
• Download bleeding-edge
• Uncompress it (for example to /opt)
• Add the bin/directory of the toolchain to $PATH
• In my case: export PATH=$PATH:/opt/armv6-eabihf--glibc--bleeding-edge-2020.08-1

csuft

import QtQuick 2.7
import QtQuick.Controls 2.0
import QtQuick.Layouts 1.0


ApplicationWindow {
    id: root
    width: 780
    height: 150
    visible: true

kmhofmann

Building TensorFlow from source (TF 2.3.0, Ubuntu 20.04)

Why build from source?

The official instructions on installing TensorFlow are here: https://www.tensorflow.org/install. If you want to install TensorFlow just using pip, you are running a supported Ubuntu LTS distribution, and you're happy to install the respective tested CUDA versions (which often are outdated), by all means go ahead. A good alternative may be to run a Docker image.

I am usually unhappy with installing what in effect are pre-built binaries. These binaries are often not compatible with the Ubuntu version I am running, the CUDA version that I have installed, and so on. Furthermore, they may be slower than binaries optimized for the target architecture, since certain instructions are not being used (e.g. AVX2, FMA).

So installing TensorFlow from source becomes a necessity. The official instructions on building TensorFlow from source are here: ht