Repository: qoncept/TensorSwift
Branch: master
Commit: f4616d049b2d
Files: 55
Total size: 12.4 MB
Directory structure:
gitextract_qun949lr/
├── .gitignore
├── LICENSE
├── Package.swift
├── README.md
├── Sources/
│ ├── MNIST/
│ │ ├── AppDelegate.swift
│ │ ├── Assets.xcassets/
│ │ │ └── AppIcon.appiconset/
│ │ │ └── Contents.json
│ │ ├── Base.lproj/
│ │ │ ├── LaunchScreen.storyboard
│ │ │ └── Main.storyboard
│ │ ├── Canvas.swift
│ │ ├── CanvasView.swift
│ │ ├── Classifier.swift
│ │ ├── Info.plist
│ │ ├── Line.swift
│ │ ├── Models/
│ │ │ ├── W_conv1
│ │ │ ├── W_conv2
│ │ │ ├── W_fc1
│ │ │ ├── W_fc2
│ │ │ ├── b_conv1
│ │ │ ├── b_conv2
│ │ │ ├── b_fc1
│ │ │ └── b_fc2
│ │ ├── String.swift
│ │ └── ViewController.swift
│ └── TensorSwift/
│ ├── Dimension.swift
│ ├── Info.plist
│ ├── Operators.swift
│ ├── Shape.swift
│ ├── Tensor.swift
│ ├── TensorMath.swift
│ ├── TensorNN.swift
│ ├── TensorSwift.h
│ └── Utils.swift
├── TensorSwift.podspec
├── TensorSwift.xcodeproj/
│ ├── Configs/
│ │ └── Project.xcconfig
│ ├── TensorSwiftTests_Info.plist
│ ├── TensorSwift_Info.plist
│ ├── project.pbxproj
│ └── project.xcworkspace/
│ └── contents.xcworkspacedata
└── Tests/
├── LinuxMain.swift
├── MNISTTests/
│ ├── Array.swift
│ ├── ClassifierTests.swift
│ ├── Downloader.swift
│ ├── DownloaderTests.swift
│ ├── Info.plist
│ ├── MNISTTests-Bridging-Header.h
│ └── SHA1.swift
└── TensorSwiftTests/
├── CalculationPerformanceTests.swift
├── DimensionTests.swift
├── Info.plist
├── PowerTests.swift
├── TensorMathTest.swift
├── TensorNNTests.swift
├── TensorSwiftSample.swift
├── TensorSwiftTests.swift
└── TensorTests.swift
================================================
FILE CONTENTS
================================================
================================================
FILE: .gitignore
================================================
# Xcode
#
build/
*.pbxuser
!default.pbxuser
*.mode1v3
!default.mode1v3
*.mode2v3
!default.mode2v3
*.perspectivev3
!default.perspectivev3
xcuserdata
*.xccheckout
*.moved-aside
DerivedData
*.hmap
*.ipa
*.xcuserstate
# SwiftPackageManager
#
.build
/*.xcodeproj/xcshareddata/
/*.xcodeproj/project.xcworkspace/xcuserdata/
/*.xcodeproj/xcuserdata/
# CocoaPods
#
# We recommend against adding the Pods directory to your .gitignore. However
# you should judge for yourself, the pros and cons are mentioned at:
# http://guides.cocoapods.org/using/using-cocoapods.html#should-i-ignore-the-pods-directory-in-source-control
#
# Pods/
# Carthage
#
# Add this line if you want to avoid checking in source code from Carthage dependencies.
# Carthage/Checkouts
Carthage/Build
================================================
FILE: LICENSE
================================================
The MIT License (MIT)
Copyright (c) 2016 Qoncept, Inc.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: Package.swift
================================================
// swift-tools-version:4.0
// The swift-tools-version declares the minimum version of Swift required to build this package.
import PackageDescription
let package = Package(
name: "TensorSwift",
products: [
// Products define the executables and libraries produced by a package, and make them visible to other packages.
.library(
name: "TensorSwift",
targets: ["TensorSwift"]),
],
dependencies: [
// Dependencies declare other packages that this package depends on.
// .package(url: /* package url */, from: "1.0.0"),
],
targets: [
// Targets are the basic building blocks of a package. A target can define a module or a test suite.
// Targets can depend on other targets in this package, and on products in packages which this package depends on.
.target(
name: "TensorSwift",
dependencies: []),
.testTarget(
name: "TensorSwiftTests",
dependencies: ["TensorSwift"]),
]
)
================================================
FILE: README.md
================================================
# TensorSwift
_TensorSwift_ is a lightweight library to calculate tensors, which has similar APIs to [_TensorFlow_](https://www.tensorflow.org/)'s. _TensorSwift_ is useful to simulate calculating tensors in Swift **using models trained by _TensorFlow_**.
```swift
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b = Tensor(shape: [2, 3], elements: [7, 8, 9, 10, 11, 12])
let sum = a + b // Tensor(shape: [2, 3], elements: [8, 10, 12, 14, 16, 18])
let mul = a * b // Tensor(shape: [2, 3], elements: [7, 16, 27, 40, 55, 72])
let c = Tensor(shape: [3, 1], elements: [7, 8, 9])
let matmul = a.matmul(c) // Tensor(shape: [2, 1], elements: [50, 122])
let zeros = Tensor(shape: [2, 3, 4])
let ones = Tensor(shape: [2, 3, 4], element: 1)
```
## Deep MNIST for Experts
The following code shows how to simulate [Deep MNIST for Experts](https://www.tensorflow.org/versions/r0.8/tutorials/mnist/pros/index.html), a tutorial of _TensorFlow_, by _TensorSwift_.
```swift
public struct Classifier {
public let W_conv1: Tensor
public let b_conv1: Tensor
public let W_conv2: Tensor
public let b_conv2: Tensor
public let W_fc1: Tensor
public let b_fc1: Tensor
public let W_fc2: Tensor
public let b_fc2: Tensor
public func classify(_ x_image: Tensor) -> Int {
let h_conv1 = (x_image.conv2d(filter: W_conv1, strides: [1, 1, 1]) + b_conv1).relu()
let h_pool1 = h_conv1.maxPool(kernelSize: [2, 2, 1], strides: [2, 2, 1])
let h_conv2 = (h_pool1.conv2d(filter: W_conv2, strides: [1, 1, 1]) + b_conv2).relu()
let h_pool2 = h_conv2.maxPool(kernelSize: [2, 2, 1], strides: [2, 2, 1])
let h_pool2_flat = h_pool2.reshaped([1, Dimension(7 * 7 * 64)])
let h_fc1 = (h_pool2_flat.matmul(W_fc1) + b_fc1).relu()
let y_conv = (h_fc1.matmul(W_fc2) + b_fc2).softmax()
return y_conv.elements.enumerated().max { $0.1 < $1.1 }!.0
}
}
```
## Installation
### Swift Package Manager
```swift
.Package(url: "git@github.com:qoncept/TensorSwift.git", from: "0.2.0"),
```
### CocoaPods
```
pod 'TensorSwift', '~> 0.2'
```
### Carthage
```
github "qoncept/TensorSwift" ~> 0.2
```
## License
[The MIT License](LICENSE)
================================================
FILE: Sources/MNIST/AppDelegate.swift
================================================
import UIKit
@UIApplicationMain
class AppDelegate: UIResponder, UIApplicationDelegate {
var window: UIWindow?
func application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplicationLaunchOptionsKey: Any]?) -> Bool {
// Override point for customization after application launch.
return true
}
func applicationWillResignActive(_ application: UIApplication) {
// Sent when the application is about to move from active to inactive state. This can occur for certain types of temporary interruptions (such as an incoming phone call or SMS message) or when the user quits the application and it begins the transition to the background state.
// Use this method to pause ongoing tasks, disable timers, and invalidate graphics rendering callbacks. Games should use this method to pause the game.
}
func applicationDidEnterBackground(_ application: UIApplication) {
// Use this method to release shared resources, save user data, invalidate timers, and store enough application state information to restore your application to its current state in case it is terminated later.
// If your application supports background execution, this method is called instead of applicationWillTerminate: when the user quits.
}
func applicationWillEnterForeground(_ application: UIApplication) {
// Called as part of the transition from the background to the active state; here you can undo many of the changes made on entering the background.
}
func applicationDidBecomeActive(_ application: UIApplication) {
// Restart any tasks that were paused (or not yet started) while the application was inactive. If the application was previously in the background, optionally refresh the user interface.
}
func applicationWillTerminate(_ application: UIApplication) {
// Called when the application is about to terminate. Save data if appropriate. See also applicationDidEnterBackground:.
}
}
================================================
FILE: Sources/MNIST/Assets.xcassets/AppIcon.appiconset/Contents.json
================================================
{
"images" : [
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "3x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "2x"
}
],
"info" : {
"version" : 1,
"author" : "xcode"
}
}
================================================
FILE: Sources/MNIST/Base.lproj/LaunchScreen.storyboard
================================================
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="10116" systemVersion="15E65" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" launchScreen="YES" useTraitCollections="YES" initialViewController="01J-lp-oVM">
<dependencies>
<deployment identifier="iOS"/>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="10085"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="EHf-IW-A2E">
<objects>
<viewController id="01J-lp-oVM" sceneMemberID="viewController">
<layoutGuides>
<viewControllerLayoutGuide type="top" id="Llm-lL-Icb"/>
<viewControllerLayoutGuide type="bottom" id="xb3-aO-Qok"/>
</layoutGuides>
<view key="view" contentMode="scaleToFill" id="Ze5-6b-2t3">
<rect key="frame" x="0.0" y="0.0" width="600" height="600"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="calibratedWhite"/>
</view>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="iYj-Kq-Ea1" userLabel="First Responder" sceneMemberID="firstResponder"/>
</objects>
<point key="canvasLocation" x="53" y="375"/>
</scene>
</scenes>
</document>
================================================
FILE: Sources/MNIST/Base.lproj/Main.storyboard
================================================
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="10116" systemVersion="15E65" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" initialViewController="BYZ-38-t0r">
<dependencies>
<deployment identifier="iOS"/>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="10085"/>
<capability name="Aspect ratio constraints" minToolsVersion="5.1"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="tne-QT-ifu">
<objects>
<viewController id="BYZ-38-t0r" customClass="ViewController" customModule="MNIST" customModuleProvider="target" sceneMemberID="viewController">
<layoutGuides>
<viewControllerLayoutGuide type="top" id="y3c-jy-aDJ"/>
<viewControllerLayoutGuide type="bottom" id="wfy-db-euE"/>
</layoutGuides>
<view key="view" contentMode="scaleToFill" id="8bC-Xf-vdC">
<rect key="frame" x="0.0" y="0.0" width="600" height="600"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<subviews>
<view contentMode="scaleToFill" translatesAutoresizingMaskIntoConstraints="NO" id="uby-G9-0HG" customClass="CanvasView" customModule="MNIST" customModuleProvider="target">
<rect key="frame" x="0.0" y="0.0" width="600" height="600"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="calibratedWhite"/>
<constraints>
<constraint firstAttribute="width" secondItem="uby-G9-0HG" secondAttribute="height" multiplier="1:1" id="iMN-cJ-Vll"/>
</constraints>
</view>
<button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="7vG-JB-rEi">
<rect key="frame" x="273" y="560" width="54" height="30"/>
<state key="normal" title="Classify"/>
<connections>
<action selector="onPressClassifyButton:" destination="BYZ-38-t0r" eventType="touchUpInside" id="84U-07-SXk"/>
</connections>
</button>
</subviews>
<color key="backgroundColor" red="0.93725490199999995" green="0.93725490199999995" blue="0.95686274510000002" alpha="1" colorSpace="calibratedRGB"/>
<constraints>
<constraint firstItem="wfy-db-euE" firstAttribute="top" relation="greaterThanOrEqual" secondItem="uby-G9-0HG" secondAttribute="bottom" id="3fz-2w-v7P"/>
<constraint firstItem="uby-G9-0HG" firstAttribute="top" relation="greaterThanOrEqual" secondItem="8bC-Xf-vdC" secondAttribute="top" priority="500" id="3ok-ag-yr9"/>
<constraint firstItem="uby-G9-0HG" firstAttribute="centerX" secondItem="8bC-Xf-vdC" secondAttribute="centerX" id="8eu-2d-nsr"/>
<constraint firstItem="7vG-JB-rEi" firstAttribute="centerX" secondItem="8bC-Xf-vdC" secondAttribute="centerX" id="BhB-lX-8dI"/>
<constraint firstItem="wfy-db-euE" firstAttribute="top" secondItem="7vG-JB-rEi" secondAttribute="bottom" constant="10" id="O49-dA-vBd"/>
<constraint firstAttribute="trailing" relation="greaterThanOrEqual" secondItem="uby-G9-0HG" secondAttribute="trailing" priority="500" id="Sfv-CX-pTg"/>
<constraint firstItem="uby-G9-0HG" firstAttribute="width" secondItem="8bC-Xf-vdC" secondAttribute="width" priority="500" id="Wnr-Cj-5Zd"/>
<constraint firstItem="uby-G9-0HG" firstAttribute="height" secondItem="8bC-Xf-vdC" secondAttribute="height" priority="500" id="k6J-97-4Bu"/>
<constraint firstItem="uby-G9-0HG" firstAttribute="leading" relation="greaterThanOrEqual" secondItem="8bC-Xf-vdC" secondAttribute="leading" priority="500" id="mkG-Cu-hyV"/>
<constraint firstItem="uby-G9-0HG" firstAttribute="centerY" secondItem="8bC-Xf-vdC" secondAttribute="centerY" id="pWY-OM-cRn"/>
</constraints>
</view>
<connections>
<outlet property="canvasView" destination="uby-G9-0HG" id="1zv-6w-oc8"/>
</connections>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="dkx-z0-nzr" sceneMemberID="firstResponder"/>
</objects>
</scene>
</scenes>
</document>
================================================
FILE: Sources/MNIST/Canvas.swift
================================================
import CoreGraphics
struct Canvas {
var lines: [Line] = [Line()]
mutating func draw(_ point: CGPoint) {
lines[lines.endIndex - 1].points.append(point)
}
mutating func newLine() {
lines.append(Line())
}
}
================================================
FILE: Sources/MNIST/CanvasView.swift
================================================
import UIKit
class CanvasView: UIView {
private(set) var canvas: Canvas
required init?(coder: NSCoder) {
canvas = Canvas()
super.init(coder: coder)
self.addGestureRecognizer(UIPanGestureRecognizer(target: self, action: #selector(CanvasView.onPanGesture(_:))))
}
var image: UIImage {
UIGraphicsBeginImageContext(bounds.size)
layer.render(in: UIGraphicsGetCurrentContext()!)
let result = UIGraphicsGetImageFromCurrentImageContext()
UIGraphicsEndImageContext()
return result!
}
override func draw(_ rect: CGRect) {
let context = UIGraphicsGetCurrentContext()
for line in canvas.lines {
context?.setLineWidth(20.0)
context?.setStrokeColor(UIColor(red: 0.0, green: 0.0, blue: 0.0, alpha: 1.0).cgColor)
context?.setLineCap(.round)
context?.setLineJoin(.round)
for (index, point) in line.points.enumerated() {
if index == 0 {
context?.move(to: CGPoint(x: point.x, y: point.y))
} else {
context?.addLine(to: CGPoint(x: point.x, y: point.y))
}
}
}
context?.strokePath()
}
@objc func onPanGesture(_ gestureRecognizer: UIPanGestureRecognizer) {
canvas.draw(gestureRecognizer.location(in: self))
if gestureRecognizer.state == .ended {
canvas.newLine()
}
setNeedsDisplay()
}
func clear() {
canvas = Canvas()
setNeedsDisplay()
}
}
================================================
FILE: Sources/MNIST/Classifier.swift
================================================
import Foundation
import TensorSwift
public struct Classifier {
public let W_conv1: Tensor
public let b_conv1: Tensor
public let W_conv2: Tensor
public let b_conv2: Tensor
public let W_fc1: Tensor
public let b_fc1: Tensor
public let W_fc2: Tensor
public let b_fc2: Tensor
public func classify(_ x_image: Tensor) -> Int {
let h_conv1 = (x_image.conv2d(filter: W_conv1, strides: [1, 1, 1]) + b_conv1).relu()
let h_pool1 = h_conv1.maxPool(kernelSize: [2, 2, 1], strides: [2, 2, 1])
let h_conv2 = (h_pool1.conv2d(filter: W_conv2, strides: [1, 1, 1]) + b_conv2).relu()
let h_pool2 = h_conv2.maxPool(kernelSize: [2, 2, 1], strides: [2, 2, 1])
let h_pool2_flat = h_pool2.reshaped([1, Dimension(7 * 7 * 64)])
let h_fc1 = (h_pool2_flat.matmul(W_fc1) + b_fc1).relu()
let y_conv = (h_fc1.matmul(W_fc2) + b_fc2).softmax()
return y_conv.elements.enumerated().max { $0.1 < $1.1 }!.0
}
}
extension Classifier {
public init(path: String) {
W_conv1 = Tensor(shape: [5, 5, 1, 32], elements: loadFloatArray(path, file: "W_conv1"))
b_conv1 = Tensor(shape: [32], elements: loadFloatArray(path, file: "b_conv1"))
W_conv2 = Tensor(shape: [5, 5, 32, 64], elements: loadFloatArray(path, file: "W_conv2"))
b_conv2 = Tensor(shape: [64], elements: loadFloatArray(path, file: "b_conv2"))
W_fc1 = Tensor(shape: [Dimension(7 * 7 * 64), 1024], elements: loadFloatArray(path, file: "W_fc1"))
b_fc1 = Tensor(shape: [1024], elements: loadFloatArray(path, file: "b_fc1"))
W_fc2 = Tensor(shape: [1024, 10], elements: loadFloatArray(path, file: "W_fc2"))
b_fc2 = Tensor(shape: [10], elements: loadFloatArray(path, file: "b_fc2"))
}
}
private func loadFloatArray(_ directory: String, file: String) -> [Float] {
let data = try! Data(contentsOf: URL(fileURLWithPath: directory.stringByAppendingPathComponent(file)))
return Array(UnsafeBufferPointer(start: UnsafeMutablePointer<Float>(mutating: (data as NSData).bytes.bindMemory(to: Float.self, capacity: data.count)), count: data.count / 4))
}
================================================
FILE: Sources/MNIST/Info.plist
================================================
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>APPL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
<key>LSRequiresIPhoneOS</key>
<true/>
<key>UILaunchStoryboardName</key>
<string>LaunchScreen</string>
<key>UIMainStoryboardFile</key>
<string>Main</string>
<key>UIRequiredDeviceCapabilities</key>
<array>
<string>armv7</string>
</array>
<key>UISupportedInterfaceOrientations</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
<key>UISupportedInterfaceOrientations~ipad</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationPortraitUpsideDown</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
<key>NSAppTransportSecurity</key>
<dict>
<key>NSExceptionDomains</key>
<dict>
<key>yann.lecun.com</key>
<string></string>
</dict>
<key>NSAllowsArbitraryLoads</key>
<true/>
</dict>
</dict>
</plist>
================================================
FILE: Sources/MNIST/Line.swift
================================================
import CoreGraphics
struct Line {
var points: [CGPoint]
init() {
self.init([])
}
init(_ points: [CGPoint]) {
self.points = points
}
}
================================================
FILE: Sources/MNIST/Models/W_fc1
================================================
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================================================
FILE: Sources/MNIST/Models/b_conv1
================================================
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================================================
FILE: Sources/MNIST/Models/b_conv2
================================================
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================================================
FILE: Sources/MNIST/Models/b_fc2
================================================
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================================================
FILE: Sources/MNIST/String.swift
================================================
import Foundation
extension String {
public func stringByAppendingPathComponent(_ str: String) -> String {
return (self as NSString).appendingPathComponent(str)
}
}
================================================
FILE: Sources/MNIST/ViewController.swift
================================================
import UIKit
import TensorSwift
class ViewController: UIViewController {
@IBOutlet private var canvasView: CanvasView!
private let inputSize = 28
private let classifier = Classifier(path: Bundle.main.resourcePath!)
@IBAction func onPressClassifyButton(_ sender: UIButton) {
let input: Tensor
do {
let image = canvasView.image
let cgImage = image.cgImage!
var pixels = [UInt8](repeating: 0, count: inputSize * inputSize)
let context = CGContext(data: &pixels, width: inputSize, height: inputSize, bitsPerComponent: 8, bytesPerRow: inputSize, space: CGColorSpaceCreateDeviceGray(), bitmapInfo: 0)!
context.clear(CGRect(x: 0.0, y: 0.0, width: CGFloat(inputSize), height: CGFloat(inputSize)))
let rect = CGRect(x: 0.0, y: 0.0, width: CGFloat(inputSize), height: CGFloat(inputSize))
context.draw(cgImage, in: rect)
input = Tensor(shape: [Dimension(inputSize), Dimension(inputSize), 1], elements: pixels.map { (pixel: UInt8) -> Float in -(Float(pixel) / 255.0 - 0.5) + 0.5 })
}
let estimatedLabel = classifier.classify(input)
let alertController = UIAlertController(title: "\(estimatedLabel)", message: nil, preferredStyle: .alert)
alertController.addAction(UIAlertAction(title: "Dismiss", style: .default) { _ in self.canvasView.clear() })
present(alertController, animated: true, completion: nil)
}
}
================================================
FILE: Sources/TensorSwift/Dimension.swift
================================================
public struct Dimension {
public let value: Int
public init(_ value: Int) {
guard value >= 0 else { fatalError("`value` must be greater than or equal to 0: \(value)") }
self.value = value
}
}
extension Dimension: ExpressibleByIntegerLiteral {
public init(integerLiteral value: Int) {
self.init(value)
}
}
extension Dimension: Equatable {}
public func ==(lhs: Dimension, rhs: Dimension) -> Bool {
return lhs.value == rhs.value
}
extension Dimension: CustomStringConvertible {
public var description: String {
return value.description
}
}
public func +(lhs: Dimension, rhs: Dimension) -> Dimension {
return Dimension(lhs.value + rhs.value)
}
public func -(lhs: Dimension, rhs: Dimension) -> Dimension {
return Dimension(lhs.value - rhs.value)
}
public func *(lhs: Dimension, rhs: Dimension) -> Dimension {
return Dimension(lhs.value * rhs.value)
}
public func /(lhs: Dimension, rhs: Dimension) -> Dimension {
return Dimension(lhs.value / rhs.value)
}
================================================
FILE: Sources/TensorSwift/Info.plist
================================================
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>FMWK</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleSignature</key>
<string>????</string>
<key>CFBundleVersion</key>
<string>$(CURRENT_PROJECT_VERSION)</string>
<key>NSPrincipalClass</key>
<string></string>
</dict>
</plist>
================================================
FILE: Sources/TensorSwift/Operators.swift
================================================
infix operator ** : PowerPrecedence
precedencegroup PowerPrecedence {
associativity: right
higherThan: MultiplicationPrecedence
}
================================================
FILE: Sources/TensorSwift/Shape.swift
================================================
public struct Shape {
public let dimensions: [Dimension]
public func volume() -> Int {
return dimensions.reduce(1) { $0 * $1.value }
}
public init(_ dimensions: [Dimension]) {
self.dimensions = dimensions
}
}
extension Shape: ExpressibleByArrayLiteral {
public init(arrayLiteral elements: Dimension...) {
self.init(elements)
}
}
extension Shape: Equatable {}
public func ==(lhs: Shape, rhs: Shape) -> Bool {
return lhs.dimensions == rhs.dimensions
}
extension Shape: CustomStringConvertible {
public var description: String {
return dimensions.description
}
}
================================================
FILE: Sources/TensorSwift/Tensor.swift
================================================
#if os(iOS) || os(OSX)
import Accelerate
#endif
public struct Tensor {
public typealias Element = Float
public let shape: Shape
public fileprivate(set) var elements: [Element]
public init(shape: Shape, elements: [Element]) {
let volume = shape.volume()
precondition(elements.count >= volume, "`elements.count` must be greater than or equal to `shape.volume`: elements.count = \(elements.count), shape.volume = \(shape.volume())")
self.shape = shape
self.elements = (elements.count == volume) ? elements : Array(elements[0..<volume])
}
}
extension Tensor { // Additional Initializers
public init(shape: Shape, element: Element = 0.0) {
self.init(shape: shape, elements: [Element](repeating: element, count: shape.volume()))
}
}
extension Tensor {
public mutating func reshape(_ shape: Shape) {
self = reshaped(shape)
}
public func reshaped(_ shape: Shape) -> Tensor {
return Tensor(shape: shape, elements: elements)
}
}
extension Tensor { // like CollentionType
internal func index(_ indices: [Int]) -> Int {
assert(indices.count == shape.dimensions.count, "`indices.count` must be \(shape.dimensions.count): \(indices.count)")
return zip(shape.dimensions, indices).reduce(0) {
assert(0 <= $1.1 && $1.1 < $1.0.value, "Illegal index: indices = \(indices), shape = \(shape)")
return $0 * $1.0.value + $1.1
}
}
public subscript(indices: Int...) -> Element {
get {
return elements[index(indices)]
}
set {
elements[index(indices)] = newValue
}
}
public func volume() -> Int {
return shape.volume()
}
}
extension Tensor: Sequence {
public func makeIterator() -> IndexingIterator<[Element]> {
return elements.makeIterator()
}
}
extension Tensor: Equatable {}
public func ==(lhs: Tensor, rhs: Tensor) -> Bool {
return lhs.shape == rhs.shape && lhs.elements == rhs.elements
}
internal func commutativeBinaryOperation(_ lhs: Tensor, _ rhs: Tensor, operation: (Float, Float) -> Float) -> Tensor {
let lSize = lhs.shape.dimensions.count
let rSize = rhs.shape.dimensions.count
if lSize == rSize {
precondition(lhs.shape == rhs.shape, "Incompatible shapes of tensors: lhs.shape = \(lhs.shape), rhs.shape = \(rhs.shape)")
return Tensor(shape: lhs.shape, elements: zipMap(lhs.elements, rhs.elements, operation: operation))
}
let a: Tensor
let b: Tensor
if lSize < rSize {
a = rhs
b = lhs
} else {
a = lhs
b = rhs
}
assert(hasSuffix(array: a.shape.dimensions, suffix: b.shape.dimensions), "Incompatible shapes of tensors: lhs.shape = \(lhs.shape), rhs.shape = \(rhs.shape)")
return Tensor(shape: a.shape, elements: zipMapRepeat(a.elements, b.elements, operation: operation))
}
internal func noncommutativeBinaryOperation(_ lhs: Tensor, _ rhs: Tensor, operation: (Float, Float) -> Float) -> Tensor {
let lSize = lhs.shape.dimensions.count
let rSize = rhs.shape.dimensions.count
if lSize == rSize {
precondition(lhs.shape == rhs.shape, "Incompatible shapes of tensors: lhs.shape = \(lhs.shape), rhs.shape = \(rhs.shape)")
return Tensor(shape: lhs.shape, elements: zipMap(lhs.elements, rhs.elements, operation: operation))
} else if lSize < rSize {
precondition(hasSuffix(array: rhs.shape.dimensions, suffix: lhs.shape.dimensions), "Incompatible shapes of tensors: lhs.shape = \(lhs.shape), rhs.shape = \(rhs.shape)")
return Tensor(shape: rhs.shape, elements: zipMapRepeat(rhs.elements, lhs.elements, operation: { operation($1, $0) }))
} else {
precondition(hasSuffix(array: lhs.shape.dimensions, suffix: rhs.shape.dimensions), "Incompatible shapes of tensors: lhs.shape = \(lhs.shape), rhs.shape = \(rhs.shape)")
return Tensor(shape: lhs.shape, elements: zipMapRepeat(lhs.elements, rhs.elements, operation: operation))
}
}
public func +(lhs: Tensor, rhs: Tensor) -> Tensor {
return commutativeBinaryOperation(lhs, rhs, operation: +)
}
public func -(lhs: Tensor, rhs: Tensor) -> Tensor {
return noncommutativeBinaryOperation(lhs, rhs, operation: -)
}
public func *(lhs: Tensor, rhs: Tensor) -> Tensor {
return commutativeBinaryOperation(lhs, rhs, operation: *)
}
public func /(lhs: Tensor, rhs: Tensor) -> Tensor {
return noncommutativeBinaryOperation(lhs, rhs, operation: /)
}
public func *(lhs: Tensor, rhs: Float) -> Tensor {
return Tensor(shape: lhs.shape, elements: lhs.elements.map { $0 * rhs })
}
public func *(lhs: Float, rhs: Tensor) -> Tensor {
return Tensor(shape: rhs.shape, elements: rhs.elements.map { lhs * $0 })
}
public func /(lhs: Tensor, rhs: Float) -> Tensor {
return Tensor(shape: lhs.shape, elements: lhs.elements.map { $0 / rhs })
}
public func /(lhs: Float, rhs: Tensor) -> Tensor {
return Tensor(shape: rhs.shape, elements: rhs.elements.map { lhs / $0 })
}
extension Tensor { // Matrix
public func matmul(_ tensor: Tensor) -> Tensor {
precondition(shape.dimensions.count == 2, "This tensor is not a matrix: shape = \(shape)")
precondition(tensor.shape.dimensions.count == 2, "The given tensor is not a matrix: shape = \(tensor.shape)")
precondition(tensor.shape.dimensions[0] == shape.dimensions[1], "Incompatible shapes of matrices: self.shape = \(shape), tensor.shape = \(tensor.shape)")
#if os(iOS) || os(OSX)
let result = Tensor(shape: [shape.dimensions[0], tensor.shape.dimensions[1]])
let n = Int32(tensor.shape.dimensions[1].value)
let k = Int32(shape.dimensions[1].value)
cblas_sgemm(
CblasRowMajor, // Order
CblasNoTrans, // TransA
CblasNoTrans, // TransB
Int32(shape.dimensions[0].value), // M
n, // N
k, // K
1.0, // alpha
elements, // A
k, // lda
tensor.elements, // B
n, // ldb
1.0, // beta
UnsafeMutablePointer<Float>(mutating: result.elements), // C
n // ldc
)
return result
#else
let n = shape.dimensions[1].value
let numRows = shape.dimensions[0]
let numCols = tensor.shape.dimensions[1]
let leftHead = UnsafeMutablePointer<Float>(self.elements)
let rightHead = UnsafeMutablePointer<Float>(tensor.elements)
let elements = [Float](count: (numCols * numRows).value, repeatedValue: 0.0)
for r in 0..<numRows.value {
for i in 0..<n {
var pointer = UnsafeMutablePointer<Float>(elements) + r * numCols.value
let left = leftHead[r * n + i]
var rightPointer = rightHead + i * numCols.value
for _ in 0..<numCols.value {
pointer.memory += left * rightPointer.memory
pointer += 1
rightPointer += 1
}
}
}
return Tensor(shape: [numRows, numCols], elements: elements)
#endif
}
}
================================================
FILE: Sources/TensorSwift/TensorMath.swift
================================================
import Darwin
public func **(lhs: Tensor, rhs: Tensor) -> Tensor {
return noncommutativeBinaryOperation(lhs, rhs, operation: powf)
}
public func **(lhs: Tensor, rhs: Tensor.Element) -> Tensor {
return Tensor(shape: lhs.shape, elements: lhs.elements.map { powf($0, rhs) })
}
public func **(lhs: Tensor.Element, rhs: Tensor) -> Tensor {
return Tensor(shape: rhs.shape, elements: rhs.elements.map { powf(lhs, $0) })
}
extension Tensor {
public func sin() -> Tensor {
return Tensor(shape: shape, elements: elements.map(sinf))
}
public func cos() -> Tensor {
return Tensor(shape: shape, elements: elements.map(cosf))
}
public func tan() -> Tensor {
return Tensor(shape: shape, elements: elements.map(tanf))
}
public func asin() -> Tensor {
return Tensor(shape: shape, elements: elements.map(asinf))
}
public func acos() -> Tensor {
return Tensor(shape: shape, elements: elements.map(acosf))
}
public func atan() -> Tensor {
return Tensor(shape: shape, elements: elements.map(atanf))
}
public func sinh() -> Tensor {
return Tensor(shape: shape, elements: elements.map(sinhf))
}
public func cosh() -> Tensor {
return Tensor(shape: shape, elements: elements.map(coshf))
}
public func tanh() -> Tensor {
return Tensor(shape: shape, elements: elements.map(tanhf))
}
public func exp() -> Tensor {
return Tensor(shape: shape, elements: elements.map(expf))
}
public func log() -> Tensor {
return Tensor(shape: shape, elements: elements.map(logf))
}
public func sqrt() -> Tensor {
return Tensor(shape: shape, elements: elements.map(sqrtf))
}
public func cbrt() -> Tensor {
return Tensor(shape: shape, elements: elements.map(cbrtf))
}
}
extension Tensor {
public func sigmoid() -> Tensor {
return Tensor(shape: shape, elements: elements.map { 1.0 / (1.0 + expf(-$0)) })
}
}
================================================
FILE: Sources/TensorSwift/TensorNN.swift
================================================
import Darwin
#if os(iOS) || os(OSX)
import Accelerate
#endif
extension Tensor {
public func softmax() -> Tensor {
let exps = exp()
let sum = exps.elements.reduce(0.0, +)
return exps / sum
}
public func relu() -> Tensor {
return Tensor(shape: shape, elements: elements.map { fmax($0, 0.0) })
}
}
extension Tensor {
public func maxPool(kernelSize: [Int], strides: [Int]) -> Tensor { // padding = Same
precondition(shape.dimensions.count == 3, "`shape.dimensions.count` must be 3: \(shape.dimensions.count)")
precondition(kernelSize.count == 3, "`ksize.count` must be 3: \(kernelSize.count)")
precondition(kernelSize[2] == 1, "`ksize[3]` != 1 is not supported: \(kernelSize[2])")
precondition(strides.count == 3, "`strides.count` must be 3: \(strides.count)")
precondition(strides[2] == 1, "`strides[2]` != 1 is not supported: \(strides[2])")
let inRows = shape.dimensions[0].value
let inCols = shape.dimensions[1].value
let numChannels = shape.dimensions[2].value
let filterHeight = kernelSize[0]
let filterWidth = kernelSize[1]
let inMinDy = -(filterHeight - 1) / 2
let inMaxDy = inMinDy + filterHeight - 1
let inMinDx = -(filterWidth - 1) / 2
let inMaxDx = inMinDx + filterWidth - 1
let rowStride = strides[0]
let colStride = strides[1]
let outRows = shape.dimensions[0].value.ceilDiv(rowStride)
let outCols = shape.dimensions[1].value.ceilDiv(colStride)
// Initialize with -infinity for maximization.
let elements = [Element](repeating: -Float.infinity, count: outCols * outRows * numChannels)
for y in 0..<outRows {
let inY0 = y * rowStride
let inMinY = Swift.max(inY0 + inMinDy, 0)
let inMaxY = Swift.min(inY0 + inMaxDy, inRows - 1)
for inY in inMinY...inMaxY {
var outPixelIndex = y * outCols
for x in 0..<outCols {
let inX0 = x * colStride
let inMinX = Swift.max(inX0 + inMinDx, 0)
let inMaxX = Swift.min(inX0 + inMaxDx, inCols - 1)
var inPointer = UnsafeMutablePointer<Element>(mutating: self.elements) + (inY * inCols + inMinX) * numChannels
for _ in inMinX...inMaxX {
var outPointer = UnsafeMutablePointer<Element>(mutating: elements) + outPixelIndex * numChannels
for _ in 0..<numChannels {
outPointer.pointee = Swift.max(outPointer.pointee, inPointer.pointee)
outPointer += 1
inPointer += 1
}
}
outPixelIndex += 1
}
}
}
return Tensor(shape: [Dimension(outRows), Dimension(outCols), Dimension(numChannels)], elements: elements)
}
public func conv2d(filter: Tensor, strides: [Int]) -> Tensor { // padding = Same
let inChannels = filter.shape.dimensions[2].value
precondition(shape.dimensions.count == 3, "`shape.dimensions.count` must be 3: \(shape.dimensions.count)")
precondition(filter.shape.dimensions.count == 4, "`filter.shape.dimensions.count` must be 4: \(filter.shape.dimensions.count)")
precondition(strides.count == 3, "`strides.count` must be 3: \(strides.count)")
precondition(strides[2] == 1, "`strides[2]` must be 1")
precondition(shape.dimensions[2].value == inChannels, "The number of channels of this tensor and the filter are not compatible: \(shape.dimensions[2]) != \(inChannels)")
let inRows = shape.dimensions[0].value
let inCols = shape.dimensions[1].value
let filterHeight = filter.shape.dimensions[0].value
let filterWidth = filter.shape.dimensions[1].value
let inMinDy = -(filterHeight - 1) / 2
let inMaxDy = inMinDy + filterHeight - 1
let inMinDx = -(filterWidth - 1) / 2
let inMaxDx = inMinDx + filterWidth - 1
let rowStride = strides[0]
let colStride = strides[1]
let outRows = inRows.ceilDiv(rowStride)
let outCols = inCols.ceilDiv(colStride)
let outChannels = filter.shape.dimensions[3].value
#if os(iOS) || os(OSX)
let elementsPointer = UnsafePointer<Float>(elements)
// a.shape == [outRows * outCols, rowSize]
let rowSize = filterHeight * filterWidth * inChannels
let a = [Float](repeating: 0, count: outRows * outCols * rowSize)
for y in 0..<outRows {
let inY0 = y * rowStride
let inMinY = Swift.max(inY0 + inMinDy, 0)
let inMaxY = Swift.min(inY0 + inMaxDy, inRows - 1)
for x in 0..<outCols{
let inX0 = x * colStride
let inMinX = Swift.max(inX0 + inMinDx, 0)
let inMaxX = Swift.min(inX0 + inMaxDx, inCols - 1)
// Add (x,y)'s patch as a vector
var dest = UnsafeMutablePointer<Float>(mutating: a) + ((y * outCols + x) * filterHeight - Swift.min(inY0 + inMinDy, 0)) * filterWidth * inChannels
var src = elementsPointer + (inMinY * inCols + inMinX) * inChannels
for _ in inMinY...inMaxY {
memcpy(dest - Swift.min(inX0 + inMinDx, 0) * inChannels, src, (inMinX...inMaxX).count * inChannels * MemoryLayout<Float>.size)
dest += filterWidth * inChannels
src += inCols * inChannels
}
}
}
let result = Tensor(shape: [Dimension(outRows), Dimension(outCols), Dimension(outChannels)])
let n = Int32(outChannels)
let k = Int32(rowSize)
// Calculate [M, N] matrix, it automatically turns into [outRows, outCols, outChannels] Tensor
cblas_sgemm(
CblasRowMajor, // Order
CblasNoTrans, // TransA
CblasNoTrans, // TransB
Int32(outRows * outCols), // M
n, // N
k, // K
1.0, // alpha
UnsafePointer<Float>(a), // A
k, // lda
UnsafePointer<Float>(filter.elements), // B
n, // ldb
1.0, // beta
UnsafeMutablePointer<Float>(mutating: result.elements), // C
n // ldc
)
return result
#else
let elements = [Float](count: outCols * outRows * outChannels, repeatedValue: 0.0)
for y in 0..<outRows {
let inY0 = y * rowStride
let inMinY = max(inY0 + inMinDy, 0)
let inMaxY = min(inY0 + inMaxDy, inRows - 1)
for x in 0..<outCols{
let inX0 = x * colStride
let inMinX = max(inX0 + inMinDx, 0)
let inMaxX = min(inX0 + inMaxDx, inCols - 1)
let inYOffset = inY0 + inMinDy
let inXOffset = inX0 + inMinDx
for inY in inMinY...inMaxY {
for inX in inMinX...inMaxX {
matmuladd(
inChannels, outChannels,
(inY * inCols + inX) * inChannels, UnsafeMutablePointer(self.elements),
((inY - inYOffset) * filterWidth + (inX - inXOffset)) * inChannels * outChannels, UnsafeMutablePointer(filter.elements),
(y * outCols + x) * outChannels, UnsafeMutablePointer(elements)
)
}
}
}
}
return Tensor(shape: [Dimension(outRows), Dimension(outCols), Dimension(outChannels)], elements: elements)
#endif
}
}
#if os(iOS) || os(OSX)
#else
private func matmuladd(inCols1Rows2: Int, _ outCols: Int, _ o1: Int, _ vec: UnsafeMutablePointer<Float>, _ o2: Int, _ mat: UnsafeMutablePointer<Float>, _ oo: Int, _ out: UnsafeMutablePointer<Float>) {
var v = vec + o1
for i in 0..<inCols1Rows2 {
var o = out + oo
let left = v.memory
for c in 0..<outCols {
o.memory += left * mat[i * outCols + c + o2]
o += 1
}
v += 1
}
}
#endif
================================================
FILE: Sources/TensorSwift/TensorSwift.h
================================================
#import <Foundation/Foundation.h>
//! Project version number for TensorSwift.
FOUNDATION_EXPORT double TensorSwiftVersionNumber;
//! Project version string for TensorSwift.
FOUNDATION_EXPORT const unsigned char TensorSwiftVersionString[];
// In this header, you should import all the public headers of your framework using statements like #import <TensorSwift/PublicHeader.h>
================================================
FILE: Sources/TensorSwift/Utils.swift
================================================
extension Int {
internal func ceilDiv(_ rhs: Int) -> Int {
return (self + rhs - 1) / rhs
}
}
internal func hasSuffix<Element: Equatable>(array: [Element], suffix: [Element]) -> Bool {
guard array.count >= suffix.count else { return false }
return zip(array[(array.count - suffix.count)..<array.count], suffix).reduce(true) { $0 && $1.0 == $1.1 }
}
internal func zipMap(_ a: [Float], _ b: [Float], operation: (Float, Float) -> Float) -> [Float] {
var result: [Float] = []
for i in a.indices {
result.append(operation(a[i], b[i]))
}
return result
}
internal func zipMapRepeat(_ a: [Float], _ infiniteB: [Float], operation: (Float, Float) -> Float) -> [Float] {
var result: [Float] = []
for i in a.indices {
result.append(operation(a[i], infiniteB[i % infiniteB.count]))
}
return result
}
================================================
FILE: TensorSwift.podspec
================================================
Pod::Spec.new do |s|
s.name = "TensorSwift"
s.version = "0.2.2"
s.summary = "TensorSwift is a lightweight library to calculate tensors, which has similar APIs to TensorFlow's."
s.homepage = "https://github.com/qoncept/TensorSwift"
s.license = { :type => "MIT", :file => "LICENSE" }
s.authors = { "Yuta Koshizawa" => "koshizawa@qoncept.co.jp", "Takehiro Araki" => "araki@qoncept.co.jp" }
s.ios.deployment_target = "8.0"
s.osx.deployment_target = "10.9"
# s.watchos.deployment_target = "2.0"
# s.tvos.deployment_target = "9.0"
s.source = { :git => "https://github.com/qoncept/TensorSwift.git", :tag => "#{s.version}" }
s.source_files = "Sources/*.swift"
end
================================================
FILE: TensorSwift.xcodeproj/Configs/Project.xcconfig
================================================
PRODUCT_NAME = $(TARGET_NAME)
SUPPORTED_PLATFORMS = macosx iphoneos iphonesimulator appletvos appletvsimulator watchos watchsimulator
MACOSX_DEPLOYMENT_TARGET = 10.10
DYLIB_INSTALL_NAME_BASE = @rpath
OTHER_SWIFT_FLAGS = -DXcode
COMBINE_HIDPI_IMAGES = YES
USE_HEADERMAP = NO
================================================
FILE: TensorSwift.xcodeproj/TensorSwiftTests_Info.plist
================================================
<?xml version="1.0" encoding="UTF-8"?>
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>BNDL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleSignature</key>
<string>????</string>
<key>CFBundleVersion</key>
<string>$(CURRENT_PROJECT_VERSION)</string>
<key>NSPrincipalClass</key>
<string></string>
</dict>
</plist>
================================================
FILE: TensorSwift.xcodeproj/TensorSwift_Info.plist
================================================
<?xml version="1.0" encoding="UTF-8"?>
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>FMWK</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleSignature</key>
<string>????</string>
<key>CFBundleVersion</key>
<string>$(CURRENT_PROJECT_VERSION)</string>
<key>NSPrincipalClass</key>
<string></string>
</dict>
</plist>
================================================
FILE: TensorSwift.xcodeproj/project.pbxproj
================================================
// !$*UTF8*$!
{
archiveVersion = 1;
classes = {
};
objectVersion = 46;
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GCC_WARN_UNUSED_FUNCTION = YES;
GCC_WARN_UNUSED_VARIABLE = YES;
SWIFT_OPTIMIZATION_LEVEL = "-Owholemodule";
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name = Release;
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GCC_WARN_UNUSED_VARIABLE = YES;
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name = Debug;
};
/* End XCBuildConfiguration section */
/* Begin XCConfigurationList section */
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isa = XCConfigurationList;
buildConfigurations = (
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isa = XCConfigurationList;
buildConfigurations = (
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defaultConfigurationIsVisible = 0;
defaultConfigurationName = Debug;
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rootObject = __RootObject_ /* Project object */;
}
================================================
FILE: TensorSwift.xcodeproj/project.xcworkspace/contents.xcworkspacedata
================================================
<?xml version="1.0" encoding="UTF-8"?>
<Workspace
version = "1.0">
<FileRef
location = "self:">
</FileRef>
</Workspace>
================================================
FILE: Tests/LinuxMain.swift
================================================
import XCTest
@testable import TensorSwiftTests
XCTMain([
testCase(TensorSwiftTests.allTests),
testCase(DimensionTests.allTests),
testCase(PowerTests.allTests),
testCase(TensorTests.allTests),
testCase(TensorNNTests.allTests),
testCase(CalculationPerformanceTests.allTests),
testCase(TensorSwiftSample.allTests),
])
================================================
FILE: Tests/MNISTTests/Array.swift
================================================
extension Array {
func grouped(_ count: Int) -> [[Element]] {
var result: [[Element]] = []
var group: [Element] = []
for element in self {
group.append(element)
if group.count == count {
result.append(group)
group = []
}
}
return result
}
}
================================================
FILE: Tests/MNISTTests/ClassifierTests.swift
================================================
import XCTest
import TensorSwift
@testable import MNIST
class ClassifierTests: XCTestCase {
func testClassify() {
let classifier = Classifier(path: Bundle(for: ViewController.self).resourcePath!)
let (images, labels) = downloadTestData()
let count = 1000
let xArray: [[Float]] = images.withUnsafeBytes { ptr in
[UInt8](UnsafeBufferPointer(start: UnsafePointer<UInt8>(ptr + 16), count: 28 * 28 * count))
.map { Float($0) / 255.0 }
.grouped(28 * 28)
}
let yArray: [Int] = labels.withUnsafeBytes { ptr in
[UInt8](UnsafeBufferPointer(start: UnsafePointer<UInt8>(ptr + 8), count: count))
.map { Int($0) }
}
let accuracy = Float(zip(xArray, yArray)
.reduce(0) { $0 + (classifier.classify(Tensor(shape: [28, 28, 1], elements: $1.0)) == $1.1 ? 1 : 0) })
/ Float(yArray.count)
print("accuracy: \(accuracy)")
XCTAssertGreaterThan(accuracy, 0.97)
}
}
================================================
FILE: Tests/MNISTTests/Downloader.swift
================================================
import Foundation
func downloadTestData() -> (images: Data, labels: Data) {
let baseUrl = "http://yann.lecun.com/exdb/mnist/"
let testImagesUrl = URL(string: baseUrl)!.appendingPathComponent("t10k-images-idx3-ubyte.gz")
let testLabelsUrl = URL(string: baseUrl)!.appendingPathComponent("t10k-labels-idx1-ubyte.gz")
print("download: \(testImagesUrl)")
let testImages = try! Data(contentsOf: testImagesUrl)
print("download: \(testLabelsUrl)")
let testLabels = try! Data(contentsOf: testLabelsUrl)
return (images: ungzip(testImages)!, labels: ungzip(testLabels)!)
}
private func ungzip(_ source: Data) -> Data? {
guard source.count > 0 else {
return nil
}
var stream: z_stream = z_stream.init(next_in: UnsafeMutablePointer<Bytef>(mutating: (source as NSData).bytes.bindMemory(to: Bytef.self, capacity: source.count)), avail_in: uint(source.count), total_in: 0, next_out: nil, avail_out: 0, total_out: 0, msg: nil, state: nil, zalloc: nil, zfree: nil, opaque: nil, data_type: 0, adler: 0, reserved: 0)
guard inflateInit2_(&stream, MAX_WBITS + 32, ZLIB_VERSION, Int32(MemoryLayout<z_stream>.size)) == Z_OK else {
return nil
}
let data = NSMutableData()
while stream.avail_out == 0 {
let bufferSize = 0x10000
let buffer: UnsafeMutablePointer<Bytef> = UnsafeMutablePointer<Bytef>.allocate(capacity: bufferSize)
stream.next_out = buffer
stream.avail_out = uint(MemoryLayout.size(ofValue: buffer))
inflate(&stream, Z_FINISH)
let length: size_t = MemoryLayout.size(ofValue: buffer) - Int(stream.avail_out)
if length > 0 {
data.append(buffer, length: length)
}
buffer.deallocate(capacity: bufferSize)
}
inflateEnd(&stream)
return (NSData(data: data as Data) as Data)
}
================================================
FILE: Tests/MNISTTests/DownloaderTests.swift
================================================
import XCTest
class DownloaderTests: XCTestCase {
func testDownloadTestData() {
let testData = downloadTestData()
XCTAssertEqual(testData.images.count, 7840016)
XCTAssertEqual(testData.images.sha1, "65e11ec1fd220343092a5070b58418b5c2644e26")
}
}
================================================
FILE: Tests/MNISTTests/Info.plist
================================================
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>NSAppTransportSecurity</key>
<dict>
<key>NSExceptionDomains</key>
<dict>
<key>yann.lecun.com</key>
<string></string>
</dict>
<key>NSAllowsArbitraryLoads</key>
<true/>
</dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>BNDL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
</dict>
</plist>
================================================
FILE: Tests/MNISTTests/MNISTTests-Bridging-Header.h
================================================
#ifndef MNISTTests_Bridging_Header_h
#define MNISTTests_Bridging_Header_h
#import <CommonCrypto/CommonCrypto.h>
#import "zlib.h"
#endif /* MNISTTests_Bridging_Header_h */
================================================
FILE: Tests/MNISTTests/SHA1.swift
================================================
import Foundation
extension Data {
var sha1: String {
let data = self
var digest = [UInt8](repeating: 0, count: Int(CC_SHA1_DIGEST_LENGTH))
CC_SHA1((data as NSData).bytes, CC_LONG(data.count), &digest)
let hexBytes = digest.map { String(format: "%02hhx", $0) }
return hexBytes.joined(separator: "")
}
}
================================================
FILE: Tests/TensorSwiftTests/CalculationPerformanceTests.swift
================================================
import XCTest
@testable import TensorSwift
private func getTensor1000x1000() -> Tensor {
let elements = [Float](repeating: 0.1 ,count: 1000*1000)
return Tensor(shape: [1000, 1000], elements: elements)
}
private func getTensor1x1000() -> Tensor {
let elements = [Float](repeating: 0, count: 1000)
return Tensor(shape: [1, 1000], elements: elements)
}
class CalculationPerformanceTests : XCTestCase {
func testElementAccess(){
let W = getTensor1000x1000()
measure{
for _ in 0..<100000{
let _ = W[500,500]
}
}
}
func testElementAccessRaw(){
let W = getTensor1000x1000()
measure{
for _ in 0..<100000{
let _ = W.elements[500*W.shape.dimensions[1].value + 500]
}
}
}
func testMultiplication(){
let W = getTensor1000x1000()
let x = getTensor1x1000()
measure{
let _ = x.matmul(W)
}
}
func testMultiplicationRaw() {
let W = getTensor1000x1000()
let x = getTensor1x1000()
measure{
let xRow = x.shape.dimensions[0].value
let WRow = W.shape.dimensions[0].value
let WColumn = W.shape.dimensions[1].value
var elements = [Float](repeating: 0, count: 1000)
for r in 0..<xRow {
for i in 0..<WRow {
let tmp = x.elements[r * WRow + i]
for c in 0..<WColumn {
elements[r * WRow + c] = tmp * W.elements[i * WRow + c]
}
}
}
let _ = Tensor(shape: [1,1000], elements: elements)
}
}
static var allTests : [(String, (CalculationPerformanceTests) -> () throws -> Void)] {
return [
("testElementAccess", testElementAccess),
("testElementAccessRaw", testElementAccessRaw),
("testElementMultiplication", testMultiplication),
("testElementMultiplicationRaw", testMultiplicationRaw),
]
}
}
================================================
FILE: Tests/TensorSwiftTests/DimensionTests.swift
================================================
import XCTest
@testable import TensorSwift
class DimensionTests: XCTestCase {
func testAdd() {
do {
let a = Dimension(2)
let b = Dimension(3)
XCTAssertEqual(a + b, 5)
}
}
func testSub() {
do {
let a = Dimension(3)
let b = Dimension(2)
XCTAssertEqual(a - b, 1)
}
}
func testMul() {
do {
let a = Dimension(2)
let b = Dimension(3)
XCTAssertEqual(a * b, 6)
}
}
func testDiv() {
do {
let a = Dimension(6)
let b = Dimension(2)
XCTAssertEqual(a / b, 3)
}
}
static var allTests : [(String, (DimensionTests) -> () throws -> Void)] {
return [
("testAdd", testAdd),
("testSub", testSub),
("testMul", testMul),
("testDiv", testDiv),
]
}
}
================================================
FILE: Tests/TensorSwiftTests/Info.plist
================================================
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>BNDL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleSignature</key>
<string>????</string>
<key>CFBundleVersion</key>
<string>1</string>
</dict>
</plist>
================================================
FILE: Tests/TensorSwiftTests/PowerTests.swift
================================================
import XCTest
@testable import TensorSwift
class PowerTests: XCTestCase {
func testScalar() {
let tensor = Tensor(shape: [2, 2], elements: [1, 2, 3, 4])
let scalar = Tensor.Element(2)
XCTAssertEqual(tensor ** scalar, Tensor(shape: [2, 2], elements: [1, 4, 9, 16]))
XCTAssertEqual(scalar ** tensor, Tensor(shape: [2, 2], elements: [2, 4, 8, 16]))
XCTAssertEqual(scalar ** tensor ** scalar, Tensor(shape: [2, 2], elements: [2, 16, 512, 65536]))
}
func testMatrices() {
let tensor = Tensor(shape: [2, 2], elements: [1, 2, 3, 4])
let tensor2 = Tensor(shape: [2, 2], elements: [2, 2, 2, 2])
XCTAssertEqual(tensor ** tensor2, Tensor(shape: [2, 2], elements: [1, 4, 9, 16]))
XCTAssertEqual(tensor ** tensor, Tensor(shape: [2, 2], elements: [1, 4, 27, 256]))
XCTAssertEqual(tensor ** tensor2 ** tensor, Tensor(shape: [2, 2], elements: [1, 16, powf(3, 8), powf(4, 16)]))
}
static var allTests : [(String, (PowerTests) -> () throws -> Void)] {
return [
("testScalar", testScalar),
("testMatrices", testMatrices),
]
}
}
================================================
FILE: Tests/TensorSwiftTests/TensorMathTest.swift
================================================
import XCTest
@testable import TensorSwift
class TensorMathTest: XCTestCase {
func testPow() {
do {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b = Tensor(shape: [2, 3], elements: [6, 5, 4, 3, 2, 1])
XCTAssertEqual(a ** b, Tensor(shape: [2, 3], elements: [1, 32, 81, 64, 25, 6]))
XCTAssertEqual(b ** a, Tensor(shape: [2, 3], elements: [6, 25, 64, 81, 32, 1]))
}
do {
let a = Tensor(shape: [2, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [2], elements: [2, 3])
XCTAssertEqual(a ** b, Tensor(shape: [2, 3, 2], elements: [1, 8, 9, 64, 25, 216, 49, 512, 81, 1000, 121, 1728]))
XCTAssertEqual(b ** a, Tensor(shape: [2, 3, 2], elements: [2, 9, 8, 81, 32, 729, 128, 6561, 512, 59049, 2048, 531441]))
}
do {
let a = Tensor(shape: [2, 1, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [3, 2], elements: [6, 5, 4, 3, 2, 1])
XCTAssertEqual(a ** b, Tensor(shape: [2, 1, 3, 2], elements: [1, 32, 81, 64, 25, 6, 117649, 32768, 6561, 1000, 121, 12]))
XCTAssertEqual(b ** a, Tensor(shape: [2, 1, 3, 2], elements: [6, 25, 64, 81, 32, 1, 279936, 390625, 262144, 59049, 2048, 1]))
}
do {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b: Float = 2.0
XCTAssertEqual(a ** b, Tensor(shape: [2, 3], elements: [1, 4, 9, 16, 25, 36]))
XCTAssertEqual(b ** a, Tensor(shape: [2, 3], elements: [2, 4, 8, 16, 32, 64]))
}
}
func testSigmoid() {
do {
let a = Tensor(shape: [2, 3], elements: [-10, -1, 0, 1, 10, 100])
XCTAssertEqual(a.sigmoid(), Tensor(shape: [2, 3], elements: [4.53978719e-05, 2.68941432e-01, 5.00000000e-01, 7.31058598e-01, 9.99954581e-01, 1.00000000e+00]))
}
}
}
================================================
FILE: Tests/TensorSwiftTests/TensorNNTests.swift
================================================
import XCTest
@testable import TensorSwift
class TensorNNTests: XCTestCase {
func testMaxPool() {
do {
let a = Tensor(shape: [2,3,1], elements: [0,1,2,3,4,5])
let r = a.maxPool(kernelSize: [1,3,1], strides: [1,1,1])
XCTAssertEqual(r, Tensor(shape: [2,3,1], elements: [1,2,2,4,5,5]))
}
do {
let a = Tensor(shape: [2,2,2], elements: [0,1,2,3,4,5,6,7])
do {
let r = a.maxPool(kernelSize:[1,2,1], strides: [1,1,1])
XCTAssertEqual(r, Tensor(shape: [2,2,2], elements: [2, 3, 2, 3, 6, 7, 6, 7]))
}
do {
let r = a.maxPool(kernelSize:[1,2,1], strides: [1,2,1])
XCTAssertEqual(r, Tensor(shape: [2,1,2], elements: [2, 3, 6, 7]))
}
}
}
func testConv2d() {
do {
let a = Tensor(shape: [2,4,1], elements: [1,2,3,4,5,6,7,8])
do {
let filter = Tensor(shape: [2,1,1,2], elements: [1,2,1,2])
let result = a.conv2d(filter: filter, strides: [1,1,1])
XCTAssertEqual(result, Tensor(shape: [2,4,2], elements: [6,12,8,16,10,20,12,24,5,10,6,12,7,14,8,16]))
}
do {
let filter = Tensor(shape: [1,1,1,5], elements: [1,2,1,2,3])
let result = a.conv2d(filter: filter, strides: [1,1,1])
XCTAssertEqual(result, Tensor(shape: [2,4,5], elements: [1,2,1,2,3,2,4,2,4,6,3,6,3,6,9,4,8,4,8,12,5,10,5,10,15,6,12,6,12,18,7,14,7,14,21,8,16,8,16,24]))
}
}
do {
let a = Tensor(shape: [2,2,4], elements: [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16])
let filter = Tensor(shape: [1,1,4,2], elements: [1,2,1,2,3,2,1,1])
let result = a.conv2d(filter: filter, strides: [1,1,1])
XCTAssertEqual(result, Tensor(shape: [2,2,2], elements: [16, 16, 40, 44, 64, 72, 88, 100]))
}
do {
let a = Tensor(shape: [4,2,2], elements: [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16])
let filter = Tensor(shape: [2,2,2,1], elements: [1,2,1,2,3,2,1,1])
let result = a.conv2d(filter: filter, strides: [2,2,1])
XCTAssertEqual(result, Tensor(shape: [2,1,1], elements: [58,162]))
}
do {
let a = Tensor(shape: [4,4,1], elements: [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16])
let filter = Tensor(shape: [3,3,1,1], elements: [1,2,1,2,3,2,1,1,1])
let result = a.conv2d(filter: filter, strides: [3,3,1])
XCTAssertEqual(result, Tensor(shape: [2,2,1], elements: [18,33,95,113]))
}
do {
let a = Tensor(shape: [1,3,1], elements: [1,2,3])
let filter = Tensor(shape: [1,3,1,2], elements: [1,1,2,2,3,3])
let result = a.conv2d(filter: filter, strides: [1,1,1])
XCTAssertEqual(result, Tensor(shape: [1,3,2], elements: [8, 8, 14, 14, 8, 8]))
}
}
func testMaxPoolPerformance(){
let image = Tensor(shape: [28,28,3], element: 0.1)
measure{
_ = image.maxPool(kernelSize: [2,2,1], strides: [2,2,1])
}
}
func testConv2dPerformance(){
let image = Tensor(shape: [28,28,1], element: 0.1)
let filter = Tensor(shape: [5,5,1,16], element: 0.1)
measure{
_ = image.conv2d(filter: filter, strides: [1,1,1])
}
}
static var allTests : [(String, (TensorNNTests) -> () throws -> Void)] {
return [
("testMaxPool", testMaxPool),
("testConv2d", testConv2d),
("testMaxPoolPerformance", testMaxPoolPerformance),
("testConv2dPerformance", testConv2dPerformance),
]
}
}
================================================
FILE: Tests/TensorSwiftTests/TensorSwiftSample.swift
================================================
import XCTest
import TensorSwift
class TensorSwiftSample: XCTestCase {
func testSample() {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b = Tensor(shape: [2, 3], elements: [7, 8, 9, 10, 11, 12])
let sum = a + b // Tensor(shape: [2, 3], elements: [8, 10, 12, 14, 16, 18])
let mul = a * b // Tensor(shape: [2, 3], elements: [7, 16, 27, 40, 55, 72])
let c = Tensor(shape: [3, 1], elements: [7, 8, 9])
let matmul = a.matmul(c) // Tensor(shape: [2, 1], elements: [50, 122])
let zeros = Tensor(shape: [2, 3, 4])
let ones = Tensor(shape: [2, 3, 4], element: 1)
XCTAssertEqual(sum, Tensor(shape: [2, 3], elements: [8, 10, 12, 14, 16, 18]))
XCTAssertEqual(mul, Tensor(shape: [2, 3], elements: [7, 16, 27, 40, 55, 72]))
XCTAssertEqual(matmul, Tensor(shape: [2, 1], elements: [50, 122]))
XCTAssertEqual(zeros, Tensor(shape: [2, 3, 4], elements: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]))
XCTAssertEqual(ones, Tensor(shape: [2, 3, 4], elements: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]))
}
static var allTests : [(String, (TensorSwiftSample) -> () throws -> Void)] {
return [
("testSample", testSample),
]
}
}
================================================
FILE: Tests/TensorSwiftTests/TensorSwiftTests.swift
================================================
//
// TensorSwiftTests.swift
// TensorSwift
//
// Created by Araki Takehiro on 2016/09/28.
//
//
import XCTest
class TensorSwiftTests: XCTestCase {
override func setUp() {
super.setUp()
// Put setup code here. This method is called before the invocation of each test method in the class.
}
override func tearDown() {
// Put teardown code here. This method is called after the invocation of each test method in the class.
super.tearDown()
}
static var allTests : [(String, (TensorSwiftTests) -> () throws -> Void)] {
return [
]
}
}
================================================
FILE: Tests/TensorSwiftTests/TensorTests.swift
================================================
import XCTest
@testable import TensorSwift
class TensorTests: XCTestCase {
func testIndex() {
do {
let a = Tensor(shape: [])
XCTAssertEqual(a.index([]), 0)
}
do {
let a = Tensor(shape: [7])
XCTAssertEqual(a.index([3]), 3)
}
do {
let a = Tensor(shape: [5, 7])
XCTAssertEqual(a.index([1, 2]), 9)
}
do {
let a = Tensor(shape: [5, 7, 11])
XCTAssertEqual(a.index([3, 1, 2]), 244)
}
}
func testAdd() {
do {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b = Tensor(shape: [2, 3], elements: [7, 8, 9, 10, 11, 12])
let r = a + b
XCTAssertEqual(r, Tensor(shape: [2, 3], elements: [8, 10, 12, 14, 16, 18]))
}
do {
let a = Tensor(shape: [2, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [2], elements: [100, 200])
XCTAssertEqual(a + b, Tensor(shape: [2, 3, 2], elements: [101, 202, 103, 204, 105, 206, 107, 208, 109, 210, 111, 212]))
XCTAssertEqual(b + a, Tensor(shape: [2, 3, 2], elements: [101, 202, 103, 204, 105, 206, 107, 208, 109, 210, 111, 212]))
}
do {
let a = Tensor(shape: [2, 1, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [3, 2], elements: [100, 200, 300, 400, 500, 600])
XCTAssertEqual(a + b, Tensor(shape: [2, 1, 3, 2], elements: [101, 202, 303, 404, 505, 606, 107, 208, 309, 410, 511, 612]))
XCTAssertEqual(b + a, Tensor(shape: [2, 1, 3, 2], elements: [101, 202, 303, 404, 505, 606, 107, 208, 309, 410, 511, 612]))
}
}
func testSub() {
do {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b = Tensor(shape: [2, 3], elements: [12, 11, 10, 9, 8, 7])
let r = a - b
XCTAssertEqual(r, Tensor(shape: [2, 3], elements: [-11, -9, -7, -5, -3, -1]))
}
do {
let a = Tensor(shape: [2, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [2], elements: [100, 200])
XCTAssertEqual(a - b, Tensor(shape: [2, 3, 2], elements: [-99, -198, -97, -196, -95, -194, -93, -192, -91, -190, -89, -188]))
XCTAssertEqual(b - a, Tensor(shape: [2, 3, 2], elements: [99, 198, 97, 196, 95, 194, 93, 192, 91, 190, 89, 188]))
}
do {
let a = Tensor(shape: [2, 1, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [3, 2], elements: [100, 200, 300, 400, 500, 600])
XCTAssertEqual(a - b, Tensor(shape: [2, 1, 3, 2], elements: [-99, -198, -297, -396, -495, -594, -93, -192, -291, -390, -489, -588]))
XCTAssertEqual(b - a, Tensor(shape: [2, 1, 3, 2], elements: [99, 198, 297, 396, 495, 594, 93, 192, 291, 390, 489, 588]))
}
}
func testMul() {
do {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b = Tensor(shape: [2, 3], elements: [7, 8, 9, 10, 11, 12])
XCTAssertEqual(a * b, Tensor(shape: [2, 3], elements: [7, 16, 27, 40, 55, 72]))
XCTAssertEqual(b * a, Tensor(shape: [2, 3], elements: [7, 16, 27, 40, 55, 72]))
}
do {
let a = Tensor(shape: [2, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [2], elements: [10, 100])
XCTAssertEqual(a * b, Tensor(shape: [2, 3, 2], elements: [10, 200, 30, 400, 50, 600, 70, 800, 90, 1000, 110, 1200]))
XCTAssertEqual(b * a, Tensor(shape: [2, 3, 2], elements: [10, 200, 30, 400, 50, 600, 70, 800, 90, 1000, 110, 1200]))
}
do {
let a = Tensor(shape: [2, 1, 3, 2], elements: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
let b = Tensor(shape: [3, 2], elements: [10, 100, 1000, -10, -100, -1000])
XCTAssertEqual(a * b, Tensor(shape: [2, 1, 3, 2], elements: [10, 200, 3000, -40, -500, -6000, 70, 800, 9000, -100, -1100, -12000]))
XCTAssertEqual(b * a, Tensor(shape: [2, 1, 3, 2], elements: [10, 200, 3000, -40, -500, -6000, 70, 800, 9000, -100, -1100, -12000]))
}
do {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b: Float = 2.0
XCTAssertEqual(a * b, Tensor(shape: [2, 3], elements: [2, 4, 6, 8, 10, 12]))
XCTAssertEqual(b * a, Tensor(shape: [2, 3], elements: [2, 4, 6, 8, 10, 12]))
}
}
func testDiv() {
do {
let a = Tensor(shape: [2, 3], elements: [2048, 512, 128, 32, 8, 2])
let b = Tensor(shape: [2, 3], elements: [2, 4, 8, 16, 32, 64])
XCTAssertEqual(a / b, Tensor(shape: [2, 3], elements: [1024, 128, 16, 2, 0.25, 0.03125]))
XCTAssertEqual(b / a, Tensor(shape: [2, 3], elements: [0.0009765625, 0.0078125, 0.0625, 0.5, 4, 32]))
}
do {
let a = Tensor(shape: [2, 3, 2], elements: [2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096])
let b = Tensor(shape: [2], elements: [8, 2])
XCTAssertEqual(a / b, Tensor(shape: [2, 3, 2], elements: [0.25, 2.0, 1.0, 8.0, 4.0, 32.0, 16.0, 128.0, 64.0, 512.0, 256.0, 2048.0]))
XCTAssertEqual(b / a, Tensor(shape: [2, 3, 2], elements: [4.0, 0.5, 1.0, 0.125, 0.25, 0.03125, 0.0625, 0.0078125, 0.015625, 0.001953125, 0.00390625, 0.00048828125]))
}
do {
let a = Tensor(shape: [3, 1, 2, 2], elements: [2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096])
let b = Tensor(shape: [2, 2], elements: [8, 2, -8, -2])
XCTAssertEqual(a / b, Tensor(shape: [3, 1, 2, 2], elements: [0.25, 2.0, -1.0, -8.0, 4.0, 32.0, -16.0, -128.0, 64.0, 512.0, -256.0, -2048.0]))
XCTAssertEqual(b / a, Tensor(shape: [3, 1, 2, 2], elements: [4.0, 0.5, -1.0, -0.125, 0.25, 0.03125, -0.0625, -0.0078125, 0.015625, 0.001953125, -0.00390625, -0.00048828125]))
}
do {
let a = Tensor(shape:[2, 3], elements: [ 1, 2, 4, 8, 16, 32])
let b: Float = 2.0
XCTAssertEqual(a / b, Tensor(shape: [2, 3], elements: [0.5, 1, 2, 4, 8, 16]))
XCTAssertEqual(b / a, Tensor(shape: [2, 3], elements: [2, 1, 0.5, 0.25, 0.125, 0.0625]))
}
}
func testMatmul() {
do {
let a = Tensor(shape: [2, 3], elements: [1, 2, 3, 4, 5, 6])
let b = Tensor(shape: [3, 4], elements: [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18])
let r = a.matmul(b)
XCTAssertEqual(r, Tensor(shape: [2, 4], elements: [74, 80, 86, 92, 173, 188, 203, 218]))
}
do {
let a = Tensor(shape: [3, 3], elements: [1, 1, 1, 2, 2, 2, 3, 3, 3])
let b = Tensor(shape: [3, 3], elements: [1, 1, 1, 2, 2, 2, 3, 3, 3])
let r = a.matmul(b)
XCTAssertEqual(r, Tensor(shape: [3, 3], elements: [6, 6, 6, 12, 12, 12, 18, 18, 18]))
}
}
func testMatmulPerformance(){
let a = Tensor(shape: [1000, 1000], element: 0.1)
let b = Tensor(shape: [1000, 1000], element: 0.1)
measure{
_ = a.matmul(b)
}
}
static var allTests : [(String, (TensorTests) -> () throws -> Void)] {
return [
("testIndex", testIndex),
("testAdd", testAdd),
("testSub", testSub),
("testMul", testMul),
("testDiv", testDiv),
("testMatmul", testMatmul),
("testMatmulPerformance", testMatmulPerformance),
]
}
}
gitextract_qun949lr/
├── .gitignore
├── LICENSE
├── Package.swift
├── README.md
├── Sources/
│ ├── MNIST/
│ │ ├── AppDelegate.swift
│ │ ├── Assets.xcassets/
│ │ │ └── AppIcon.appiconset/
│ │ │ └── Contents.json
│ │ ├── Base.lproj/
│ │ │ ├── LaunchScreen.storyboard
│ │ │ └── Main.storyboard
│ │ ├── Canvas.swift
│ │ ├── CanvasView.swift
│ │ ├── Classifier.swift
│ │ ├── Info.plist
│ │ ├── Line.swift
│ │ ├── Models/
│ │ │ ├── W_conv1
│ │ │ ├── W_conv2
│ │ │ ├── W_fc1
│ │ │ ├── W_fc2
│ │ │ ├── b_conv1
│ │ │ ├── b_conv2
│ │ │ ├── b_fc1
│ │ │ └── b_fc2
│ │ ├── String.swift
│ │ └── ViewController.swift
│ └── TensorSwift/
│ ├── Dimension.swift
│ ├── Info.plist
│ ├── Operators.swift
│ ├── Shape.swift
│ ├── Tensor.swift
│ ├── TensorMath.swift
│ ├── TensorNN.swift
│ ├── TensorSwift.h
│ └── Utils.swift
├── TensorSwift.podspec
├── TensorSwift.xcodeproj/
│ ├── Configs/
│ │ └── Project.xcconfig
│ ├── TensorSwiftTests_Info.plist
│ ├── TensorSwift_Info.plist
│ ├── project.pbxproj
│ └── project.xcworkspace/
│ └── contents.xcworkspacedata
└── Tests/
├── LinuxMain.swift
├── MNISTTests/
│ ├── Array.swift
│ ├── ClassifierTests.swift
│ ├── Downloader.swift
│ ├── DownloaderTests.swift
│ ├── Info.plist
│ ├── MNISTTests-Bridging-Header.h
│ └── SHA1.swift
└── TensorSwiftTests/
├── CalculationPerformanceTests.swift
├── DimensionTests.swift
├── Info.plist
├── PowerTests.swift
├── TensorMathTest.swift
├── TensorNNTests.swift
├── TensorSwiftSample.swift
├── TensorSwiftTests.swift
└── TensorTests.swift
Condensed preview — 55 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (132K chars).
[
{
"path": ".gitignore",
"chars": 764,
"preview": "# Xcode\n#\nbuild/\n*.pbxuser\n!default.pbxuser\n*.mode1v3\n!default.mode1v3\n*.mode2v3\n!default.mode2v3\n*.perspectivev3\n!defau"
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{
"path": "LICENSE",
"chars": 1080,
"preview": "The MIT License (MIT)\n\nCopyright (c) 2016 Qoncept, Inc.\n\nPermission is hereby granted, free of charge, to any person obt"
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{
"path": "Package.swift",
"chars": 1037,
"preview": "// swift-tools-version:4.0\n// The swift-tools-version declares the minimum version of Swift required to build this packa"
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"path": "README.md",
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"preview": "# TensorSwift\n\n_TensorSwift_ is a lightweight library to calculate tensors, which has similar APIs to [_TensorFlow_](htt"
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{
"path": "Sources/MNIST/AppDelegate.swift",
"chars": 2032,
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{
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"preview": "{\n \"images\" : [\n {\n \"idiom\" : \"iphone\",\n \"size\" : \"29x29\",\n \"scale\" : \"2x\"\n },\n {\n \"idiom\""
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{
"path": "Sources/MNIST/Base.lproj/LaunchScreen.storyboard",
"chars": 1665,
"preview": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<document type=\"com.apple.InterfaceBuilder3.CocoaTouch.Storyboard"
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{
"path": "Sources/MNIST/Canvas.swift",
"chars": 251,
"preview": "import CoreGraphics\n\nstruct Canvas {\n var lines: [Line] = [Line()]\n \n mutating func draw(_ point: CGPoint) {\n "
},
{
"path": "Sources/MNIST/CanvasView.swift",
"chars": 1617,
"preview": "import UIKit\n\nclass CanvasView: UIView {\n private(set) var canvas: Canvas\n \n required init?(coder: NSCoder) {\n "
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{
"path": "Sources/MNIST/Classifier.swift",
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"preview": "import Foundation\nimport TensorSwift\n\npublic struct Classifier {\n public let W_conv1: Tensor\n public let b_conv1: "
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{
"path": "Sources/MNIST/Info.plist",
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{
"path": "Sources/MNIST/Line.swift",
"chars": 180,
"preview": "import CoreGraphics\n\nstruct Line {\n var points: [CGPoint]\n \n init() {\n self.init([])\n }\n \n init"
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{
"path": "Sources/MNIST/Models/b_conv1",
"chars": 71,
"preview": "Ԝ=7=֩=x=o=s=Z=^=[;=ߋ=fVj=f=\u0004m=Z=T\u0004=\b==e\u000f=W=\u0018=3=\u0002=\f\u0007=/X=='^=؍=\"=`==[[=d="
},
{
"path": "Sources/MNIST/Models/b_conv2",
"chars": 123,
"preview": "\u0012=\u0004=^=\r\u0004={F=k=D=_ڴ=f==zI=Ŧ=ܕ=9=\u0001=== =ذ=\\==u='===l=Ҭ=\u001cա=,===O=PͰ==Ķ=\f===\u0007.=\u0019=숵=_=9=~==Li==Ds=k6==9=s===YJ=H=\u001f==%Π=.=\u0004=ׇ="
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{
"path": "Sources/MNIST/Models/b_fc2",
"chars": 20,
"preview": "\u0015=K=II==G==6==16=y%="
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{
"path": "Sources/MNIST/String.swift",
"chars": 182,
"preview": "import Foundation\n\nextension String {\n public func stringByAppendingPathComponent(_ str: String) -> String {\n "
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{
"path": "Sources/MNIST/ViewController.swift",
"chars": 1545,
"preview": "import UIKit\nimport TensorSwift\n\nclass ViewController: UIViewController {\n @IBOutlet private var canvasView: CanvasVi"
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"path": "Sources/TensorSwift/Dimension.swift",
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"path": "Sources/TensorSwift/TensorSwift.h",
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"chars": 357,
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"preview": "import XCTest\nimport TensorSwift\n@testable import MNIST\n\nclass ClassifierTests: XCTestCase {\n func testClassify() {\n "
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"chars": 2122,
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"chars": 1197,
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"chars": 2001,
"preview": "import XCTest\n@testable import TensorSwift\n\nclass TensorMathTest: XCTestCase {\n func testPow() {\n do {\n "
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// ... and 5 more files (download for full content)
About this extraction
This page contains the full source code of the qoncept/TensorSwift GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 55 files (12.4 MB), approximately 38.4k tokens. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.