burnbrian

#!/usr/bin/env bash
# https://pve.proxmox.com/wiki/Package_Repositories
# Tested on Proxmox 8.1.3
# https://gist.github.com/ngadmini/7f9df377999cc78c1b58e361d5425ac4
# Disable commercial and ceph
sed -i "s/^deb/\#deb/" /etc/apt/sources.list.d/pve-enterprise.list
sed -i "s/^deb/\#deb/" /etc/apt/sources.list.d/ceph.list
# Enable community
echo "deb http://download.proxmox.com/debian/pve $(grep "VERSION=" /etc/os-release | sed -n 's/.*(\(.*\)).*/\1/p') pve-no-subscription" > /etc/apt/sources.list.d/pve-no-enterprise.list
# Update and upgrade

lukaseder

with recursive
  dims (r1, r2, i1, i2, s, it, p) as (values (-2::float, 1::float, -1.5::float, 1.5::float, 0.01::float, 100, 256.0::float)),
  sprites (s) as (values (st_makepolygon(st_geomfromtext('linestring (0 0, 0 1, 1 1, 1 0, 0 0)')))),
  n1 (r, i) as (select r, i from dims, generate_series((r1 / s)::int, (r2 / s)::int) r, generate_series((i1 / s)::int, (i2 / s)::int) i),
  n2 (r, i) as (select r::float * s::float, i::float * s::float from dims, n1),
  l (cr, ci, zr, zi, g, it, p) as (
    select r, i, 0::float, 0::float, 0, it, p from n2, dims
    union all
    select cr, ci, zr*zr - zi*zi + cr, 2 * zr * zi + ci, g + 1, it, p from l where g < it and zr*zr + zi*zi < p
  ),

majek

rm .config
make tinyconfig
make kvm_guest.config
make kvmconfig
./scripts/config \
        -e EARLY_PRINTK \
        -e 64BIT \
        -e BPF -d EMBEDDED -d EXPERT \
        -e INOTIFY_USER 

stephencookdev

import React from "react";
import { animateSwitch } from "./animateSwitch";
import { SlideOut } from "./SlideOut";

const SwitchWithSlide = animateSwitch(Switch, SlideOut);

export default () => (
  <SwitchWithSlide>
    <Route path="/a" component={PageA} />
    <Route path="/b" component={PageB} />

ubergesundheit

systemd Service Unit for Traefik

Adapted from caddy systemd Service Unit

The provided file should work with systemd version 219 or later. It might work with earlier versions. The easiest way to check your systemd version is to run systemctl --version.

Instructions

We will assume the following:

jumpingfella

import org.deeplearning4j.nn.conf.GradientNormalization;
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
import org.deeplearning4j.nn.conf.layers.GravesLSTM;
import org.deeplearning4j.nn.conf.layers.RnnOutputLayer;
import org.deeplearning4j.nn.api.OptimizationAlgorithm;
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.nn.weights.WeightInit;
import org.nd4j.linalg.activations.Activation;
import org.nd4j.linalg.api.ndarray.INDArray;

avnerbarr

// Simple function to generate 64 bit hashes using the builtin Murmur hash functionaliy which only outputs 32bits
// we had cases when hashing 15M+ items where we got around 0.08% conflicts
// using this method we were able to hash 15M items with 0 conflicts
object ExtendedMurmurHash {
  val seed = 0xf7ca7fd2

  def hash(u: String): Long = {
    val a = scala.util.hashing.MurmurHash3.stringHash(u, seed)
    val b = scala.util.hashing.MurmurHash3.stringHash(u.reverse.toString, seed)
    // shift a 32 bits to the left, leaving 32 lower bits zeroed

chrisdone

Common

export OPT=/opt
export BUILDS=/some/where/mini_linux
mkdir -p $BUILDS

Linux kernel

patoorio

*.pyc

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