Merge pull request #12 from qoncept/dev-0.2.3

Update for Swift 4

Package.swift

@@ -1,5 +1,28 @@
+// 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"
+    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"]),
+    ]
 )

README.md

@@ -1,6 +1,6 @@
 # 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___.
+_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])
@@ -31,15 +31,15 @@ public struct Classifier {
     public let b_fc1: Tensor
     public let W_fc2: Tensor
     public let b_fc2: Tensor
-
-    public func classify(x_image: Tensor) -> Int {
+    
+    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, 7 * 7 * 64])
+        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()
@@ -54,7 +54,7 @@ public struct Classifier {
 ### Swift Package Manager
 
 ```swift
-.Package(url: "[email protected]:qoncept/TensorSwift.git", majorVersion: 0, minor: 2),
+.Package(url: "[email protected]:qoncept/TensorSwift.git", from: "0.2.0"),
 ```
 
 ### CocoaPods

MNIST/CanvasView.swift → Sources/MNIST/CanvasView.swift

@@ -22,7 +22,7 @@ class CanvasView: UIView {
         let context = UIGraphicsGetCurrentContext()
         for line in canvas.lines {
             context?.setLineWidth(20.0)
-            context?.setStrokeColor(UIColor(colorLiteralRed: 0.0, green: 0.0, blue: 0.0, alpha: 1.0).cgColor)
+            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() {
@@ -36,7 +36,7 @@ class CanvasView: UIView {
         context?.strokePath()
     }
 
-    func onPanGesture(_ gestureRecognizer: UIPanGestureRecognizer) {
+    @objc func onPanGesture(_ gestureRecognizer: UIPanGestureRecognizer) {
         canvas.draw(gestureRecognizer.location(in: self))
         if gestureRecognizer.state == .ended {
             canvas.newLine()

MNIST/Classifier.swift → Sources/MNIST/Classifier.swift

@@ -18,7 +18,7 @@ public struct Classifier {
         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, 7 * 7 * 64])
+        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()
@@ -33,7 +33,7 @@ extension Classifier {
         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: [7 * 7 * 64, 1024], elements: loadFloatArray(path, file: "W_fc1"))
+        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"))

MNIST/ViewController.swift → Sources/MNIST/ViewController.swift

@@ -22,7 +22,7 @@ class ViewController: UIViewController {
             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 { -(Float($0) / 255.0 - 0.5) + 0.5 })
+            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)