silky

int[][] result;
float t, c;

float ease(float p) {
  return 3*p*p - 2*p*p*p;
}

float ease(float p, float g) {
  if (p < 0.5) 
    return 0.5 * pow(2*p, g);

silky

A Tour of PyTorch Internals (Part I)

The fundamental unit in PyTorch is the Tensor. This post will serve as an overview for how we implement Tensors in PyTorch, such that the user can interact with it from the Python shell. In particular, we want to answer four main questions:

1. How does PyTorch extend the Python interpreter to define a Tensor type that can be manipulated from Python code?
2. How does PyTorch wrap the C libraries that actually define the Tensor's properties and methods?
3. How does PyTorch cwrap work to generate code for Tensor methods?
4. How does PyTorch's build system take all of these components to compile and generate a workable application?

Extending the Python Interpreter

PyTorch defines a new package torch. In this post we will consider the ._C module. This module is known as an "extension module" - a Python module written in C. Such modules allow us to define new built-in object types (e.g. the Tensor) and to call C/C++ functions.

silky

-- The meta-circular interpreter from section 5 of Reynolds's Definitional
-- Interpreters for Higher Order Programming Languages
-- (http://www.cs.uml.edu/~giam/91.531/Textbooks/definterp.pdf)

data EXP
  = CONST Const
  | VAR Var
  | APPL Appl
  | LAMBDA Lambda
  | COND Cond

silky

# Initialize placeholders for feeding in to the queue
pl_queue_screens = tf.placeholder(tf.float32, shape=[config.seq_length, config.image_size, config.image_size, config.input_channels], name="queue_inputs")
pl_queue_targets = tf.placeholder(tf.uint8, shape=[config.seq_length], name="queue_targets_cnt")

#  ...

capacity = config.min_after_dequeue + 10 * (config.num_gpus*config.batch_size)
q = tf.RandomShuffleQueue(

silky

Experiments

• http://absulit.com/portfolio/demo/webvr/001/
• https://www.clicktorelease.com/code/polygon-shredder/vr/ #positional
• https://www.clicktorelease.com/tmp/threejs/webvr-physics/ #positional #input #haptic
• https://janusweb.metacade.com/ https://github.com/jbaicoianu/janusweb/
• https://jzitelli.github.io/poolvr/
• https://kuva.io/block-background/ #positional #input
• https://www.shadertoy.com/results?filter=vr
• https://vr-batted-ball-vis.herokuapp.com/index.html

silky

Colours in terminal

It's a common confusion about terminal colours... Actually we have this:

• plain ascii
• ansi escape codes (16 colour codes with bold/italic and background)
• 256 colour palette (216 colours + 16 ansi + 24 gray) (colors are 24bit)
• 24bit true colour ("888" colours (aka 16 milion))

printf "\x1b[${bg};2;${red};${green};${blue}m\n"

silky

#! /usr/bin/env python

""" Convert values between RGB hex codes and xterm-256 color codes.

Nice long listing of all 256 colors and their codes. Useful for
developing console color themes, or even script output schemes.

Resources:
* http://en.wikipedia.org/wiki/8-bit_color
* http://en.wikipedia.org/wiki/ANSI_escape_code

silky

{
  "type": "object",
  "properties": {
    "AWSEBDockerrunVersion": {
      "type": "integer",
      "minimum": 1,
      "maximum": 2
    },
    "authentication": {
      "type": "object",

silky

Direct links to free Springer books (pdf versions)

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

silky

(ns repl-test.mud-experiment
  (:use [overtone.live])
  (:use [overtone.studio.scope])
  (:use mud.core)
  (:require [mud.timing :as timing]))

(defn bpm->rate-of-16 [bpm]
  (* (/ bpm 60) 4.))

(ctl timing/root-s :rate (bpm->rate-of-16 127))