OrionReed

// 3D Dom viewer, copy-paste this into your console to visualise the DOM as a stack of solid blocks.
// You can also minify and save it as a bookmarklet (https://www.freecodecamp.org/news/what-are-bookmarklets/)
(() => {
  const SHOW_SIDES = false; // color sides of DOM nodes?
  const COLOR_SURFACE = true; // color tops of DOM nodes?
  const COLOR_RANDOM = false; // randomise color?
  const COLOR_HUE = 190; // hue in HSL (https://hslpicker.com)
  const MAX_ROTATION = 180; // set to 360 to rotate all the way round
  const THICKNESS = 20; // thickness of layers
  const DISTANCE = 10000; // ¯\\_(ツ)_/¯

mrange

[F#] Implementing Coroutines (async/await) using continuations

Coroutines or async/await is not a new concept as it was named in 1958 by Melvin Conway. Coroutines had support in languages such as Simula(1962), Smalltalk(1972) and Modula-2(1978) but I think one can argue that coroutines came into mainstream with C# 5(2012) when Microsoft added async/await to C#.

The problem with subroutines

A thread can only execute a single subroutine at a time as a subroutine starts and then runs to completion. In a server environment subroutines can be problematic as in order to service connections concurrently we would usually would start a thread per connection, this was the idiom a few years ago. A thread depending on the operating system and settings needs about 1 MiB of user stack space meaning 1,024 threads needs 1 GiB of for just user stack space. In addition there's the cost of kernel stack space, book-keeping and scheduling of threads. This drives cost of VM/hardwa

swlaschin

Architecture

• Use Onion architecture

  • Dependencies go inwards. That is, the Core domain doesn't know about outside layers

• Use pipeline model to implement workflows/use-cases/stories

  • Business logic makes decisions
  • IO does storage with minimal logic
  • Keep Business logic and IO separate

• Keep IO at edges

mrry

# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

sirreal

module Main where

import Prelude
import Data.List
import Data.Either (Either(..))
import Data.Maybe (Maybe(..))
import Data.Newtype (class Newtype, unwrap)
import Data.Tuple (Tuple(..), fst, snd)

import Unsafe.Coerce (unsafeCoerce)

baraldilorenzo

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman