mnist_train_batch_prep.swift

func prepareBatchProvider() -> MLBatchProvider {
    var featureProviders = [MLFeatureProvider]()

    var count = 0
    errno = 0
    let trainFilePath = Bundle.main.url(forResource: "mnist_train", withExtension: "csv")!
    if freopen(trainFilePath.path, "r", stdin) == nil {
        print("error opening file")
    }
    while let line = readLine()?.split(separator: ",") {
        count += 1

        let imageMultiArr = try! MLMultiArray(shape: [1, 28, 28], dataType: .float32)
        let outputMultiArr = try! MLMultiArray(shape: [1], dataType: .int32)

        for r in 0..<28 {
            for c in 0..<28 {
                let i = (r*28)+c
                imageMultiArr[i] = NSNumber(value: Float(String(line[i + 1]))! / Float(255.0))
            }
        }

        outputMultiArr[0] = NSNumber(value: Int(String(line[0]))!)

        let imageValue = MLFeatureValue(multiArray: imageMultiArr)
        let outputValue = MLFeatureValue(multiArray: outputMultiArr)

        let dataPointFeatures: [String: MLFeatureValue] = ["image": imageValue,
                                                           "output_true": outputValue]

        if let provider = try? MLDictionaryFeatureProvider(dictionary: dataPointFeatures) {
            featureProviders.append(provider)
        }
    }

    return MLArrayBatchProvider(array: featureProviders)
}