pjstein pjstein

Learn Go in ~5mins

Your first Go program as a classical "Hello World" is pretty simple:

First we create a workspace for our project:

	{
	# Caddy is running behind an application load balancer hosted at AWS, so this configures Caddy to trust the headers set by it
	servers {
	trusted_proxies static private_ranges
	}

	# Avoid DoS attacks by confirming with a backend app that a requested domain should have an on-demand certificate generated
	on_demand_tls {
	ask http://web.internal:5000/confirm_domain
	interval 1m

	### JHW 2018
	import numpy as np
	import umap



	# This code from the excellent module at:
	# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module

	import random

	WAYLAND_PROTOCOLS=/usr/share/wayland-protocols

	# wayland-scanner is a tool which generates C headers and rigging for Wayland
	# protocols, which are specified in XML. wlroots requires you to rig these up
	# to your build system yourself and provide them in the include path.
	xdg-shell-protocol.h:
	wayland-scanner server-header \
	$(WAYLAND_PROTOCOLS)/stable/xdg-shell/xdg-shell.xml $@

	xdg-shell-protocol.c: xdg-shell-protocol.h

	---
	Description: AWS AppSync Notes API

	Parameters:
	APIName:
	Type: String
	Description: Name of the API - used to generate unique names for resources
	MinLength: 3
	MaxLength: 20
	AllowedPattern: '^[a-zA-Z][a-zA-Z0-9_]*$'

	"""
	A bare bones examples of optimizing a black-box function (f) using
	Natural Evolution Strategies (NES), where the parameter distribution is a
	gaussian of fixed standard deviation.
	"""

	import numpy as np
	np.random.seed(0)

	# the function we want to optimize

	""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
	import numpy as np
	import cPickle as pickle
	import gym

	# hyperparameters
	H = 200 # number of hidden layer neurons
	batch_size = 10 # every how many episodes to do a param update?
	learning_rate = 1e-4
	gamma = 0.99 # discount factor for reward

	{0: 'tench, Tinca tinca',
	1: 'goldfish, Carassius auratus',
	2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
	3: 'tiger shark, Galeocerdo cuvieri',
	4: 'hammerhead, hammerhead shark',
	5: 'electric ray, crampfish, numbfish, torpedo',
	6: 'stingray',
	7: 'cock',
	8: 'hen',
	9: 'ostrich, Struthio camelus',