import joblib import os import json """ Deserialize fitted model """ def model_fn(model_dir): model = joblib.load(os.path.join(model_dir, "model.joblib")) return model """ input_fn request_body: The body of the request sent to the model. request_content_type: (string) specifies the format/variable type of the request """ def input_fn(request_body, request_content_type): if request_content_type == 'application/json': request_body = json.loads(request_body) inpVar = request_body['Input'] return inpVar else: raise ValueError("This model only supports application/json input") """ predict_fn input_data: returned array from input_fn above model (sklearn model) returned model loaded from model_fn above """ def predict_fn(input_data, model): return model.predict(input_data) """ output_fn prediction: the returned value from predict_fn above content_type: the content type the endpoint expects to be returned. Ex: JSON, string """ def output_fn(prediction, content_type): res = int(prediction[0]) respJSON = {'Output': res} return respJSON