Fix up models so they can run.

.gitignore

@@ -3,4 +3,6 @@
 
 .build
 *.xcodeproj
+*.png
 .DS_Store
+cifar-10-batches-py/

Autoencoder/main.swift

@@ -47,7 +47,7 @@ func plot(image: [Float], name: String) {
 
 /// Reads a file into an array of bytes.
 func readFile(_ filename: String) -> [UInt8] {
-    let possibleFolders = [".", "Resources"]
+    let possibleFolders = [".", "Resources", "Autoencoder/Resources"]
     for folder in possibleFolders {
         let parent = URL(fileURLWithPath: folder)
         let filePath = parent.appendingPathComponent(filename).path

MNIST/main.swift

@@ -17,9 +17,17 @@ import TensorFlow
 
 /// Reads a file into an array of bytes.
 func readFile(_ path: String) -> [UInt8] {
-    let url = URL(fileURLWithPath: path)
-    let data = try! Data(contentsOf: url, options: [])
-    return [UInt8](data)
+    let possibleFolders  = [".", "MNIST"]
+    for folder in possibleFolders {
+        let parent = URL(fileURLWithPath: folder)
+        let filePath = parent.appendingPathComponent(path)
+        guard FileManager.default.fileExists(atPath: filePath.path) else {
+            continue
+        }
+        let data = try! Data(contentsOf: filePath, options: [])
+        return [UInt8](data)
+    }
+    fatalError("Filename not found: \(path)")
 }
 
 /// Reads MNIST images and labels from specified file paths.
@@ -76,6 +84,8 @@ let labels = Tensor<Float>(oneHotAtIndices: numericLabels, depth: 10)
 var classifier = Classifier()
 let optimizer = RMSProp(for: classifier)
 
+print("Beginning training...")
+
 // The training loop.
 for epoch in 1...epochCount {
     var correctGuessCount = 0