// Method to load single row of data to try a single prediction
// You can change this code and create your own sample data here (Hardcoded or from any source)
private static SentimentModelInput CreateSingleDataSample(MLContext mlContext, string dataFilePath)
{
// Read dataset to get a single row for trying a prediction
IDataView dataView = mlContext.Data.LoadFromTextFile <SentimentModelInput>(
path: dataFilePath,
hasHeader: false,
separatorChar: '\t',
allowQuoting: false,
allowSparse: false);
// Here (ModelInput object) you could provide new test data, hardcoded or from the end-user application, instead of the row from the file.
SentimentModelInput sampleForPrediction = mlContext.Data.CreateEnumerable <SentimentModelInput>(dataView, false)
.First();
return(sampleForPrediction);
}
public async Task <IActionResult> PostFile([FromBody] SentenceModel sentenceModel)
{
MLContext mlContext = new MLContext();
// Training code used by ML.NET CLI and AutoML to generate the model
//ModelBuilder.CreateModel();
ITransformer mlModel = mlContext.Model.Load(MODEL_FILEPATH, out DataViewSchema inputSchema);
var predEngine = mlContext.Model.CreatePredictionEngine <SentimentModelInput, SentimentModelOutput>(mlModel);
// Create sample data to do a single prediction with it
var modelInput = new SentimentModelInput();
modelInput.Sentence = sentenceModel.Sentence;
// Try a single prediction
var predictionResult = predEngine.Predict(modelInput);
Console.WriteLine(predictionResult);
return(Ok(new { predictionResult.Score, predictionResult.Prediction }));
}
static void Main(string[] args)
{
MLContext mlContext = new MLContext();
// Training code used by ML.NET CLI and AutoML to generate the model
//ModelBuilder.CreateModel();
ITransformer mlModel = mlContext.Model.Load(GetAbsolutePath(MODEL_FILEPATH), out DataViewSchema inputSchema);
var predEngine = mlContext.Model.CreatePredictionEngine <SentimentModelInput, SentimentModelOutput>(mlModel);
// Create sample data to do a single prediction with it
SentimentModelInput sampleData = CreateSingleDataSample(mlContext, DATA_FILEPATH);
// Try a single prediction
SentimentModelOutput predictionResult = predEngine.Predict(sampleData);
Console.WriteLine($"Single Prediction --> Actual value: {sampleData.Label} | Predicted value: {predictionResult.Prediction}");
Console.WriteLine("=============== End of process, hit any key to finish ===============");
Console.ReadKey();
}
