Question

亚马逊有关于如何在iOS上使用他们的机器学习平台的文档，但没有Swift实现，我无法将其转换为Swift。这是Objective-C代码：

    // Use a created model that has a created real-time endpoint
NSString *MLModelId = @"example-model-id";

// Call GetMLModel to get the realtime endpoint URL
AWSMachineLearningGetMLModelInput *getMLModelInput =          [AWSMachineLearningGetMLModelInput new];
getMLModelInput.MLModelId = MLModelId;

[[[MachineLearning getMLModel:getMLModelInput]    continueWithSuccessBlock:^id(AWSTask *task) {
   AWSMachineLearningGetMLModelOutput *getMLModelOutput = task.result;

   // Validate that the ML model is completed
   if (getMLModelOutput.status != AWSMachineLearningEntityStatusCompleted) {
       NSLog(@"ML Model is not completed");
       return nil;
    }

    // Validate that the realtime endpoint is ready
    if (getMLModelOutput.endpointInfo.endpointStatus !=     AWSMachineLearningRealtimeEndpointStatusReady) {
       NSLog(@"Realtime endpoint is not ready");
       return nil;
    }
}
AWSMachineLearningPredictInput *predictInput = [AWSMachineLearningPredictInput new];
predictInput.predictEndpoint = getMLModelOutput.endpointInfo.endpointUrl;
predictInput.MLModelId = MLModelId;
predictInput.record = @{};

// Call and return prediction
return [MachineLearning predict:predictInput];

这是我尝试的快速代码

var  getMLModelInput  = AWSMachineLearningGetMLModelInput()
// Use a created model that has a created real-time endpoint
let MLModelId = "example-model-id"

// Call GetMLModel to get the realtime endpoint URL
getMLModelInput.MLModelId = MLModelId;
let task = AWSMachineLearning.getMLModel(getMLModelInput) // This line won't work because the method .getMLModel expects and instance of AWSMachineLearning

我试图在用于上传到s3的代码之后模拟我的Swift代码：

    let transferManager = AWSS3TransferManager.defaultS3TransferManager()

    let testFileURL1 = NSURL(fileURLWithPath: NSTemporaryDirectory()).URLByAppendingPathComponent("tmp")

    let uploadRequest1 : AWSS3TransferManagerUploadRequest = AWSS3TransferManagerUploadRequest()

    let data = userCSV.dataUsingEncoding(NSUTF8StringEncoding)
    data!.writeToURL(testFileURL1, atomically: true)

    uploadRequest1.bucket = "users/1"
    uploadRequest1.key =  "tmpkey.csv"
    uploadRequest1.body = testFileURL1

    let task = transferManager.upload(uploadRequest1)
    task.continueWithBlock { (task) -> AnyObject! in
        if task.error != nil {
            print("Error: \(task.error)")
        } else {
            print("Upload successful")

        }
        return nil
    }

但我无法弄清楚如何为机器学习模型构建任务对象。任何帮助将不胜感激！

Answer 1

AWS网站上的代码段在开头缺少一行：

AWSMachineLearning *MachineLearning = [AWSMachineLearning defaultMachineLearning];

你可以像这样把它翻译成Swift

let MachineLearning = AWSMachineLearning.defaultMachineLearning()

然后你可以这样打电话：

let MachineLearning = AWSMachineLearning.defaultMachineLearning()

let getMLModelInput  = AWSMachineLearningGetMLModelInput()
// Use a created model that has a created real-time endpoint
getMLModelInput.MLModelId = "example-model-id"

MachineLearning.getMLModel(getMLModelInput).continueWithBlock { (task) -> AnyObject? in
    //
}

您应该查看此集成test case以获取更多详细信息。

iOS亚马逊机器学习Swift

1 个答案: