A Simple Ansible script to convert a clean Ubuntu 18.04 to a CUDA 10, PyTorch 1.0 preview, fastai, miniconda3 deep learning machine.

I have prepared a simple Ansible script which will enable you to convert a clean Ubuntu 18.04 image (as supplied by Google Compute Engine or PaperSpace) into a CUDA 10, PyTorch 1.0 preview, fastai 1.0.x, miniconda3 powerhouse, ready to live the (mixed-precision!) deep learning dream. I built this script specifically in order to be able to do mixed-precision neural network training on NVIDIA’s TensorCores. It currently makes use of the vxlabs.

Configuring Emacs, lsp-mode and Microsoft's Visual Studio Code Python language server.

In a previous post I showed how to get Palantir’s Python Language Server working together with Emacs and lsp-mode. In this post, we look at the brand new elephant in the room, Microsoft’s arguably far more powerful own Python Language Server, and how to integrate it with Emacs. Motivation Since that previous post on Palantir’s language server, I’ve been using Emacs far more intensively for Python coding in tmux on remote machines with GPUs for deep learning.

PyTorch 1.0 preview (Dec 6, 2018) packages with full CUDA 10 support for your Ubuntu 18.04 x86_64 systems.

(The wheel has now been updated to the latest PyTorch 1.0 preview as of December 6, 2018.) You’ve just received a shiny new NVIDIA Turing (RTX 2070, 2080 or 2080 Ti), or maybe even a beautiful Tesla V100, and now you would like to try out mixed precision (well mostly fp16) training on those lovely tensor cores, using PyTorch on an Ubuntu 18.04 LTS x86_64 system. The idea is that these tensor cores chew through fp16 much faster than they do through fp32.

Importing all of your orgmode notes into Apple Notes for mobile access.

Over the years, I’ve built up quite a collection of notes as Org mode text files. So far, it has proven to be the most expressive and the most robust note-taking modality out of a long list of candidates that I’ve tried. Note-taking using Org mode has one big drawback however: Mobile accessibility. In other words, consulting one’s org mode notes database from a mobile device is painful. This should not be the case; notes should be always and instantly available, even on mobile.

Configuring Emacs, lsp-mode and the python language server.

The language server protocol was proposed by Microsoft as a way for different editors and development environments to share language analysis backends This post describes how to configure Emacs, lsp-mode and the palantir python-language-server for improved code intelligence when working on Python projects. (I’m planning a companion post for Emacs, C++ and the cquery language server.) Goal Before starting, it is motivating to see what we are working towards.

Interactive programming with Fennel Lua Lisp, Emacs and Lisp Game Jam winner EXO_encounter 667

Phil Hagelberg recently won the Lisp Game Jam 2018 with his entry EXO_encounter 667. What I found most interesting however, was his interactive programming setup. He programmed his game in (and contributed new features to) a Lisp to Lua compiler called Fennel, and used the game programming library Löve. With Emacs and some Lua thread magic, *he was able to perform runtime changes and introspection to his live running game project*.

Asynchronous rsync with Emacs, dired and tramp.

tmtxt-dired-async by Trần Xuân Trường is an unfortunately lesser known Emacs package which extends dired, the Emacs file manager, to be able to run rsync and other commands (zip, unzip, downloading) asynchronously. This means you can copy gigabytes of directories around whilst still happily continuing with all of your other tasks in the Emacs operating system. It has a feature where you can add any number of files from different locations into a wait list with C-c C-a, and then asynchronously rsync the whole wait list into a final destination directory with C-c C-v.