D.P vodp

There are two options:

With Docker
With Mamba/Conda

In either case it is utmost important to find version compatibility between GPU driver version, CUDA compute capability, Pytorch version.

Installation with Docker

Docker provides an isolated workspace which is ideal to replicate development environment. This works well if I do not want to change my default installations just to test out some crazy Github repos out there. This is learnt from past experiences of sweat and blood. The best place to pick prebuilt docker images which are well tested against Nvidia software layers, including CUDA toolkits, CuDNN, and versions of either Tensorflow or Pytorch.

Ubuntu 15.10 have been released for a couple of days. It is a bleeding-edge system coming with Linux kernel 4.2 and GCC 5. However, compiling and running Caffe on this new system is no longer as smooth as on earlier versions. I have done some research related to this issue and finally find a way out. I summarize it here in this short tutorial and I hope more people and enjoy this new system without breaking their works.

Install NVIDIA Driver

The latest NVIDIA driver is officially included in Ubuntu 15.10 repositories. One can install it directly via apt-get.

sudo apt-get install nvidia-352-updates nvidia-modprobe

The nvidia-modprobe utility is used to load NVIDIA kernel modules and create NVIDIA character device files automatically everytime your machine boots up.

Reboot your machine and verify everything works by issuing nvidia-smi or running deviceQuery in CUDA samples.

	set nocompatible " be iMproved, required
	filetype off " required

	" set the runtime path to include Vundle and initialize
	set rtp+=~/.vim/bundle/Vundle.vim
	call vundle#begin()
	" alternatively, pass a path where Vundle should install plugins
	"call vundle#begin('~/some/path/here')

	" let Vundle manage Vundle, required

	git clone http://github.com/vodp/dotvim.git ~/.vim
	ln -s ~/.vim/vimrc ~/.vimrc
	cd ~/.vim
	git submodule init
	git submodule update

	import pprint
	import requests
	import os
	from urllib.request import urlopen

	accessToken = "xxxxxxxxxx"
	boardId = "0000000000"
	folderPath = "./images"

	response = requests.get(

	`a.to_wkt()` is given as:

	```
	'MULTIPOLYGON (((2109217.3973398101516068 5370171.8551779156550765, 2109086.7371385982260108 5370171.8551779156550765, 2108888.6720090019516647 5370607.1467390833422542, 2108757.2944846912287176 5370877.3507153857499361, 2108754.0846232827752829 5370886.9710437450557947, 2108754.0846232827752829 5371098.4806109704077244, 2108685.3188911522738636 5371098.4806109704077244, 2108622.4096368318423629 5371404.6376518597826362, 2108437.2972728596068919 5371886.1122269183397293, 2108403.8887338265776634 5372467.5511537045240402, 2108344.9671500963158906 5372708.0660511292517185, 2108290.7719067553989589 5372796.0155019462108612, 2108290.7719067553989589 5372951.7314770808443427, 2108194.8183210748247802 5372951.7314770808443427, 2107967.4938193489797413 5373320.6395924696698785, 2107364.1464737001806498 5373938.4708401244133711, 2107364.1464737001806498 5374559.0676228860393167, 2107590.7530796825885773 5374708.4650361891835928, 2107690.8046139874495566 5374804.9823431912809610, 2107827