ThoenigAdrian

import tensorflow
tensorflow.Session(config=tensorflow.ConfigProto(log_device_placement=True))

ThoenigAdrian

import socket
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect(("127.0.0.1", 80))
#s.send()
#print(s.recv(1024))

ThoenigAdrian

cat /usr/include/cudnn.h | grep CUDNN_MAJOR -A 2

ThoenigAdrian

[jane@nixos:~/graphviz]$ cat default.nix
let 

pkgs = import <nixpkgs> {}; 
mkDerivation = import ./autotools.nix pkgs;
patchedPkgs = import /home/jane/nixpkgs {} // {binutils-unwrapped="";};
mkDerivation2 = import ./autotools.nix patchedPkgs;
libs = with patchedPkgs; { inherit gd fontconfig bzip2 libjpeg;};

in

ThoenigAdrian

private void TabDefault()
{
    // The idea is as a User I expect the Tab Button to go from left to right and from top to bottom. 
    // Unfortunately this isn't the default behaviour in WinForms hence this method.
    // It will go through all Controls and sort them by their x and y coordinates and set a sane set of Tab Indices
    // This saves Maintainence because now you don't need to adapt Tab Indices when you add/remove a control
    List<Control> tabAbleControls = new List<Control>();
    foreach (Control c in Controls)
    {
        if(c.TabStop)

ThoenigAdrian

with import <nixpkgs> {};

let
  python = python37;
in
pkgs.mkShell {
  name = "pip-env";
  buildInputs = with pkgs; [
    gmp5
    libffi

ThoenigAdrian

sudo nix-channel --add https://nixos.org/channels/nixos-unstable nixos-unstable
sudo nix-channel --update nixos-unstable

ThoenigAdrian

# Import python packages which are installed in the nix store

# Note you NEED this if you install it via environment.systemPackages
# E.g environment.systemPackages = with pkgs; [ python27Packages.tensorflowWithCuda ]

# You DON'T NEED this if you do it like this: 
# python-with-my-packages = pkgs.python27.withPackages (ps: with ps; [ tensorflowWithCuda]);
# environment.systemPackages = [ python-with-my-packages ]

import sys

ThoenigAdrian

# https://stackoverflow.com/a/53374933/5130800
import torch
# setting device on GPU if available, else CPU
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('Using device:', device)
print()

#Additional Info when using cuda
if device.type == 'cuda':
    print(torch.cuda.get_device_name(0))

ThoenigAdrian

float rand_FloatRange(float a, float b)
{
	return ((b - a) * ((float)rand() / RAND_MAX)) + a;
}