# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # # SPDX-License-Identifier: MIT-0 # # Permission is hereby granted, free of charge, to any person obtaining a copy of this # software and associated documentation files (the "Software"), to deal in the Software # without restriction, including without limitation the rights to use, copy, modify, # merge, publish, distribute, sublicense, and/or sell copies of the Software, and to # permit persons to whom the Software is furnished to do so. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, # INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A # PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT # HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION # OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. library(plumber) library(readr) library(jsonlite) # load the trained model prefix <- '/opt/ml/' model_path <- paste0(prefix, 'model/model') code_path <- paste0(prefix, 'model/code/') load(model_path) print("Loaded model successfully") # function to use our model. You may require to transform data to make compatible with model inference <- function(x){ data = read_csv(x) output <- predict(regressor, newdata=data) list(output=output) } app <- plumb(paste0(code_path,'endpoints.R')) app$run(host='0.0.0.0', port=8080)