Andreas andreaslillebo

In most of deep learning projects, the training scripts always start with lines to load in data, which can easily take a handful minutes. Only after data ready can start testing my buggy code. It is so frustratingly often that I wait for ten minutes just to find I made a stupid typo, then I have to restart and wait for another ten minutes hoping no other typos are made.

In order to make my life easy, I devote lots of effort to reduce the overhead of I/O loading. Here I list some useful tricks I found and hope they also save you some time.

use Numpy Memmap to load array and say goodbye to HDF5.

I used to relay on HDF5 to read/write data, especially when loading only sub-part of all data. Yet that was before I realized how fast and charming Numpy Memmapfile is. In short, Memmapfile does not load in the whole array at open, and only later "lazily" load in the parts that are required for real operations.

Sometimes I may want to copy the full array to memory at once, as it makes later operations

These instructions will explain how to install tensorflow on mac with cuda enabled GPU suport. I assume you know what tensorflow is and why you would want to have a deep learning framework running on your computer.

Prerequisites

Make sure to update your homebrew formulas

brew update

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

YARD CHEATSHEET http://yardoc.org

May 2020 - updated fork: https://gist.github.com/phansch/db18a595d2f5f1ef16646af72fe1fb0e

cribbed from http://pastebin.com/xgzeAmBn

Templates to remind you of the options and formatting for the different types of objects you might want to document using YARD.

	# Inspired by http://www.madebyloren.com/posts/migrating-to-uuids-as-primary-keys

	task id_to_uuid: :environment do
	puts "[START] Convert id to uuid"
	ActiveRecord::Base.connection.enable_extension 'uuid-ossp' unless ActiveRecord::Base.connection.extensions.include? 'uuid-ossp'
	ActiveRecord::Base.connection.enable_extension 'pgcrypto' unless ActiveRecord::Base.connection.extensions.include? 'pgcrypto'

	table_names = ActiveRecord::Base.connection.tables - ["schema_migrations", "ar_internal_metadata", "migration_validators"]
	table_names.each do \|table_name\|
	puts "[CREATE] uuid column for #{table_name}"

	// Fix for validations on simple form

	// Need to import bootstrap functions and mixins if you want to dynamically set colors
	// Otherwise replace theme-color... with hex color
	@import 'bootstrap/functions';
	@import 'bootstrap/variables';
	@import 'bootstrap/mixins';

	.has-invalid {
	.invalid-feedback {

	module FactoryGirl
	module Doctor
	module FloatDuration
	refine Float do
	def duration
	t = self
	format("%02d:%02d.%03d", t / 60, t % 60, t.modulo(1) * 1000)
	end
	end
	end

	# The BootstrapBreadcrumbsBuilder is a Bootstrap compatible breadcrumb builder.
	# It provides basic functionalities to render a breadcrumb navigation according to Bootstrap 4's conventions.
	#
	# You can use it with the :builder option on render_breadcrumbs:
	# <%= render_breadcrumbs builder: ::BootstrapBreadcrumbsBuilder %>
	#
	# Note: You may need to adjust the autoload_paths in your config/application.rb file for rails to load this class:
	# config.autoload_paths += %W(#{config.root}/lib)
	#
	class BootstrapBreadcrumbsBuilder < BreadcrumbsOnRails::Breadcrumbs::Builder

	import 'package:flutter/material.dart';
	import 'theme.dart' as Theme;

	void main() {
	runApp(
	new MaterialApp(
	title: 'CompanyApp',
	color: Theme.CompanyColors.blue[500],
	theme: Theme.CompanyThemeData,
	home: new Scaffold(