mirror of
https://github.com/Azure/MachineLearningNotebooks.git
synced 2025-12-21 10:05:09 -05:00
60 lines
1.7 KiB
R
60 lines
1.7 KiB
R
# Copyright(c) Microsoft Corporation.
|
|
# Licensed under the MIT license.
|
|
|
|
library(azuremlsdk)
|
|
library(jsonlite)
|
|
|
|
ws <- load_workspace_from_config()
|
|
|
|
# Register the model
|
|
model <- register_model(ws, model_path = "project_files/model.rds",
|
|
model_name = "model.rds")
|
|
|
|
# Create environment
|
|
r_env <- r_environment(name = "r_env")
|
|
|
|
# Create inference config
|
|
inference_config <- inference_config(
|
|
entry_script = "score.R",
|
|
source_directory = "project_files",
|
|
environment = r_env)
|
|
|
|
# Create ACI deployment config
|
|
deployment_config <- aci_webservice_deployment_config(cpu_cores = 1,
|
|
memory_gb = 1)
|
|
|
|
# Deploy the web service
|
|
service <- deploy_model(ws,
|
|
'rservice',
|
|
list(model),
|
|
inference_config,
|
|
deployment_config)
|
|
wait_for_deployment(service, show_output = TRUE)
|
|
|
|
# If you encounter any issue in deploying the webservice, please visit
|
|
# https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-troubleshoot-deployment
|
|
|
|
# Inferencing
|
|
# versicolor
|
|
plant <- data.frame(Sepal.Length = 6.4,
|
|
Sepal.Width = 2.8,
|
|
Petal.Length = 4.6,
|
|
Petal.Width = 1.8)
|
|
# setosa
|
|
plant <- data.frame(Sepal.Length = 5.1,
|
|
Sepal.Width = 3.5,
|
|
Petal.Length = 1.4,
|
|
Petal.Width = 0.2)
|
|
# virginica
|
|
plant <- data.frame(Sepal.Length = 6.7,
|
|
Sepal.Width = 3.3,
|
|
Petal.Length = 5.2,
|
|
Petal.Width = 2.3)
|
|
|
|
# Test the web service
|
|
predicted_val <- invoke_webservice(service, toJSON(plant))
|
|
predicted_val
|
|
|
|
# Delete the web service
|
|
delete_webservice(service)
|