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-- Get Max ID from table | |
SELECT MAX(id) FROM table; | |
-- Get Next ID from table | |
SELECT nextval('table_id_seq'); | |
-- Set Next ID Value to MAX ID | |
SELECT setval('table_id_seq', (SELECT MAX(id) FROM table)); |
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import Foundation | |
import SceneKit | |
class Icosahedron : Geometry { | |
// The golden ratio | |
static let t = (1.0 + sqrt(5.0)) / 2.0; | |
// These vertices represent three orthogonal rectangles | |
// The corners of which define the 12 vertices of an icosahedron | |
// We get the normalized vector so that our points are on the unit sphere |
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import UIKit | |
import Forbind | |
import ForbindExtensions | |
enum LoadingState { | |
case NotSet | |
case Loading | |
case Loaded | |
} |
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# Install QEMU OSX port with ARM support | |
sudo port install qemu +target_arm | |
export QEMU=$(which qemu-system-arm) | |
# Dowload kernel and export location | |
curl -OL \ | |
https://github.com/dhruvvyas90/qemu-rpi-kernel/blob/master/kernel-qemu-4.1.7-jessie | |
export RPI_KERNEL=./kernel-qemu-4.1.7-jessie | |
# Download filesystem and export location |
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import Darwin | |
enum Signal: Int32 { | |
case HUP = 1 | |
case INT = 2 | |
case QUIT = 3 | |
case ABRT = 6 | |
case KILL = 9 | |
case ALRM = 14 | |
case TERM = 15 |
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#!/bin/bash | |
# Run this on This AMI on AWS: | |
# https://console.aws.amazon.com/ec2/v2/home?region=us-east-1#LaunchInstanceWizard:ami=ami-b36981d8 | |
# You should get yourself a fully working GPU enabled tensorflow installation. | |
cd ~ | |
# grab cuda 7.0 |
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/** | |
Calculate initial compass bearing between two locations | |
- parameter fromLocation: Source Location | |
- parameter toLocation: Destination Location | |
- returns: bearing (CLLocationDirection) | |
*/ | |
private func bearingFromLocation(fromLocation: CLLocation, toLocation: CLLocation) -> CLLocationDirection { | |
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// | |
// MakeTransparentHoleOnOverlayView.swift | |
// | |
// Created by James Laurenstin on 2015-04-10. | |
// Copyright (c) 2015 Aldo Group Inc. All rights reserved. | |
// | |
import UIKit | |
class MakeTransparentHoleOnOverlayView: UIView { |
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""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |