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update samples from Release-38 as a part of SDK release
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# Copyright(c) Microsoft Corporation.
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# Licensed under the MIT license.
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library(azuremlsdk)
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library(jsonlite)
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ws <- load_workspace_from_config()
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# Register the model
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model <- register_model(ws, model_path = "project_files/model.rds",
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model_name = "model.rds")
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# Create environment
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r_env <- r_environment(name = "r_env")
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# Create inference config
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inference_config <- inference_config(
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entry_script = "score.R",
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source_directory = "project_files",
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environment = r_env)
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# Create ACI deployment config
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deployment_config <- aci_webservice_deployment_config(cpu_cores = 1,
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memory_gb = 1)
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# Deploy the web service
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service <- deploy_model(ws,
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'rservice',
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list(model),
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inference_config,
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deployment_config)
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wait_for_deployment(service, show_output = TRUE)
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# If you encounter any issue in deploying the webservice, please visit
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# https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-troubleshoot-deployment
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# Inferencing
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# versicolor
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plant <- data.frame(Sepal.Length = 6.4,
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Sepal.Width = 2.8,
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Petal.Length = 4.6,
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Petal.Width = 1.8)
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# setosa
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plant <- data.frame(Sepal.Length = 5.1,
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Sepal.Width = 3.5,
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Petal.Length = 1.4,
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Petal.Width = 0.2)
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# virginica
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plant <- data.frame(Sepal.Length = 6.7,
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Sepal.Width = 3.3,
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Petal.Length = 5.2,
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Petal.Width = 2.3)
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# Test the web service
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predicted_val <- invoke_webservice(service, toJSON(plant))
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predicted_val
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# Delete the web service
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delete_webservice(service)
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# Copyright(c) Microsoft Corporation.
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# Licensed under the MIT license.
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library(jsonlite)
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init <- function() {
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model_path <- Sys.getenv("AZUREML_MODEL_DIR")
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model <- readRDS(file.path(model_path, "model.rds"))
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message("model is loaded")
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function(data) {
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plant <- as.data.frame(fromJSON(data))
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prediction <- predict(model, plant)
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result <- as.character(prediction)
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toJSON(result)
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}
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}
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