ryin

#!/bin/bash

# Script for installing tmux on systems where you don't have root access.
# tmux will be installed in $HOME/local/bin.
# It's assumed that wget and a C/C++ compiler are installed.

# exit on error
set -e

TMUX_VERSION=1.8

sevko

raytracer

A simple Python raytracer that supports spheres with configurable "material" properties (base color and a bunch of light coefficients). To generate a raytraced image of the pre-defined scene, run: python raytracer.py and open image.ppm with a PPM-compatible viewer (eog works fine on Linux):

acknowledgements

I found the following resources extremely helpful:

yrevar

{0: 'tench, Tinca tinca',
 1: 'goldfish, Carassius auratus',
 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
 3: 'tiger shark, Galeocerdo cuvieri',
 4: 'hammerhead, hammerhead shark',
 5: 'electric ray, crampfish, numbfish, torpedo',
 6: 'stingray',
 7: 'cock',
 8: 'hen',
 9: 'ostrich, Struthio camelus',

aaronpolhamus

n02119789 1 kit_fox
n02100735 2 English_setter
n02110185 3 Siberian_husky
n02096294 4 Australian_terrier
n02102040 5 English_springer
n02066245 6 grey_whale
n02509815 7 lesser_panda
n02124075 8 Egyptian_cat
n02417914 9 ibex
n02123394 10 Persian_cat

mitmul

import weakref
import matplotlib.pyplot as plt
import numpy
from sklearn.datasets import fetch_mldata


class Variable(object):

    def __init__(self, data):
        self.data = data

apaszke

def Rop(y, x, v):
  """Computes an Rop.
  
  Arguments:
    y (Variable): output of differentiated function
    x (Variable): differentiated input
    v (Variable): vector to be multiplied with Jacobian from the right
  """
  w = torch.ones_like(y, requires_grad=True)
  return torch.autograd.grad(torch.autograd.grad(y, x, w), w, v)

a-maumau

if you can access to the GUI environment, It is very easy using "disks" application.

or might be easy with gdisk/fdisk ?   I'm not sure about this.  

------------------------------------------------------------------------  

see the reference for more detail, if you want.
https://richardstechnotes.wordpress.com/2015/12/18/setting-up-an-nvme-ssd-on-ubuntu-14-04-lts/   http://takatakamanbou.hatenablog.com/entry/2015/10/25/235600 : Japanese website

soumith

conda uninstall --force pillow -y

# install libjpeg-turbo to $HOME/turbojpeg
git clone https://github.com/libjpeg-turbo/libjpeg-turbo
pushd libjpeg-turbo
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX:PATH=$HOME/turbojpeg
make
make install

rxwei

See the official Differentiable Programming Manifesto instead.

rwightman

import torch.utils.data as data
import os
import re
import torch
import tarfile
from PIL import Image


IMG_EXTENSIONS = ['.png', '.jpg', '.jpeg']