ium_444517/predict_registry.py

import json
import mlflow
import numpy as np
import sys


PATH = "/mlruns/14/80fe21a0804844088147d15a3cebb3e5/artifacts/lego-model"
model = mlflow.pyfunc.load_model(PATH)

with open(f'{model}/{(sys.argv[1:])[0]}', 'r') as file:
    json_data = json.load(file)
    print(f"Prediction: {model.predict(np.array([json_data['inputs']]))}")
mlflow attempt task 2 prediction registry 2022-05-15 13:24:08 +02:00			`import json`
			`import mlflow`
			`import numpy as np`
			`import sys`


mlflow attempt task 2 prediction registry 2022-05-15 13:30:37 +02:00			`PATH = "/mlruns/14/80fe21a0804844088147d15a3cebb3e5/artifacts/lego-model"`
mlflow attempt task 2 prediction registry 2022-05-15 13:36:03 +02:00			`model = mlflow.pyfunc.load_model(PATH)`
mlflow attempt task 2 prediction registry 2022-05-15 13:24:08 +02:00
mlflow attempt task 2 prediction registry 2022-05-15 13:36:03 +02:00			`with open(f'{model}/{(sys.argv[1:])[0]}', 'r') as file:`
mlflow attempt task 2 prediction registry 2022-05-15 13:24:08 +02:00			`json_data = json.load(file)`
mlflow attempt task 2 prediction registry 2022-05-15 13:36:03 +02:00			`print(f"Prediction: {model.predict(np.array([json_data['inputs']]))}")`