schlerp

/* Sleep Demo Serial
 * -----------------
 * Example code to demonstrate the sleep functions in a Arduino. Arduino will wake up
 * when new data is received in the serial port USART
 * Based on Sleep Demo Serial from http://www.arduino.cc/playground/Learning/ArduinoSleepCode 
 *
 * Copyright (C) 2006 MacSimski 2006-12-30 
 * Copyright (C) 2007 D. Cuartielles 2007-07-08 - Mexico DF
 * 
 *  With modifications from Ruben Laguna  2008-10-15

schlerp

// Pin 13 has an LED connected on most Arduino boards.
// Pin 11 has the LED on Teensy 2.0
// Pin 6  has the LED on Teensy++ 2.0
// Pin 13 has the LED on Teensy 3.0
// give it a name:
int led = 13;


// set up morse code timeings...
int base_time = 100;             // 200 ms base speed ~ 24 wpm

schlerp

void setup () {
  // do what ever to get it all set up
  // only ran once at poweron
}

void main () {
  if (sensorpin is low && analogread value less than x) {
    set pin high
  }
  

schlerp

from __future__ import absolute_import, division, print_function

import os
import pickle
from six.moves import urllib

import tflearn
from tflearn.data_utils import *

path = "data/sherlock_edited.txt"

schlerp

A STUDY IN SCARLET

Table of contents

Part I
Mr. Sherlock Holmes
The Science Of Deduction
The Lauriston Garden Mystery
What John Rance Had To Tell
Our Advertisement Brings A Visitor

schlerp

'''
ga_tfl.py

applying genetic algorithms to TFLearn neural networks
'''

import random
import tflearn
from tflearn.data_utils import *

schlerp

import numpy as np
import itertools
import random


# set up hyper params
pop_size = 10
learn_rate = 3
epochs = 500
train_epochs = 25

schlerp

import os
from hl7apy.parser import parse_message


input_folder_prod = ''
input_folder_test = ''


def get_fnames(folder):
    ret = []

schlerp

import time
import pygame

from pygame.locals import *

'''

brainstorm:
    level: collection of maps
    game: collection of levels

schlerp

import tflearn
from tflearn.layers.conv import conv_2d, max_pool_2d, avg_pool_2d
from tflearn.layers.merge_ops import merge
from tflearn.layers.normalization import local_response_normalization


def inceptionv3_block(input_block, filter_width=1, stride=1, 
                      activation='relu', regularizer='L2', normalise=False):

    # 1x1 convolutions