示例#1
0
        public async Task Run([CosmosDBTrigger(
                                   databaseName: "TelementryDB",
                                   collectionName: "DeviceReading",
                                   ConnectionStringSetting = "COSMOS_CONNECTION_STRING",
                                   LeaseCollectionName = "leases",
                                   CreateLeaseCollectionIfNotExists = true)] IReadOnlyList <Document> input)
        {
            try
            {
                List <DeviceReading> backupDocuments = new List <DeviceReading>();
                CloudBlobClient      cloudBlobClient = _azureStorageHelpers.ConnectToBlobClient(
                    _config[Constants.STORAGE_ACCOUNT_NAME],
                    _config[Constants.STORAGE_ACCOUNT_KEY]);
                CloudBlobContainer blobContainer = _azureStorageHelpers.GetBlobContainer(
                    cloudBlobClient,
                    _config[Constants.STORAGE_CONTAINER]);
                string backupFile = Path.Combine($"{DateTime.Now.ToString("dd-MM-yyyy")}-backup.json");

                if (input != null && input.Count > 0)
                {
                    foreach (var document in input)
                    {
                        // Persist to blob storage
                        var deviceReading = JsonConvert.DeserializeObject <DeviceReading>(document.ToString());
                        backupDocuments.Add(deviceReading);
                        _logger.LogInformation($"{document.Id} has been added to list");
                    }
                }

                var jsonData = JsonConvert.SerializeObject(backupDocuments);

                using (StreamWriter file = File.CreateText(backupFile))
                {
                    JsonSerializer serializer = new JsonSerializer();
                    serializer.Serialize(file, jsonData);
                }

                await _azureStorageHelpers.UploadBlobToStorage(blobContainer, backupFile);
            }
            catch (Exception ex)
            {
                _logger.LogWarning($"Something went wrong. Exception thrown: {ex.Message}");
                throw;
            }
        }
        private async Task TrainAndSaveModel(MLContext mlContext, string trainFilePath, string testFilePath, string modelPath, CloudBlobContainer cloudBlobContainer)
        {
            // Read flat file from local folder
            _logger.LogInformation("Loading the file into the pipeline");
            IDataView dataView = mlContext.Data.LoadFromTextFile <TaxiTrip>(trainFilePath, hasHeader: true, separatorChar: ',');

            // Create the pipeline
            _logger.LogInformation("Training pipeline");
            var pipeline = mlContext.Transforms.CopyColumns(outputColumnName: "Label", inputColumnName: "FareAmount")
                           .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: "VendorIdEncoded", inputColumnName: "VendorId"))
                           .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: "RateCodeEncoded", inputColumnName: "RateCode"))
                           .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: "PaymentTypeEncoded", inputColumnName: "PaymentType"))
                           .Append(mlContext.Transforms.Concatenate("Features", "VendorIdEncoded", "RateCodeEncoded", "PassengerCount", "TripDistance", "PaymentTypeEncoded"))
                           .Append(mlContext.Regression.Trainers.FastTree());

            // Fit the model
            _logger.LogInformation("Fitting model");
            var model = pipeline.Fit(dataView);

            // Test the model
            _logger.LogInformation("Evaluating the model");
            var modelRSquaredValue = Evaluate(_mlContext, model, testFilePath);

            _logger.LogInformation($"R-Squared value for model is {modelRSquaredValue}");

            if (modelRSquaredValue >= 0.7)
            {
                _logger.LogInformation("Good fit! Saving model");
                mlContext.Model.Save(model, dataView.Schema, modelPath);

                // Upload Model to Blob Storage
                _logger.LogInformation("Uploading model to Blob Storage");
                await _azureStorageHelpers.UploadBlobToStorage(cloudBlobContainer, modelPath);
            }
            else
            {
                _logger.LogInformation("The model is a poor fit");
            }
        }