import json
import mlflow
import numpy as np
import torch
from torch.autograd import Variable

logged_model = 'mlruns/1/d5b6f9c1784a4d2dbb8592cd4ad364d7/artifacts/model'
loaded_model = mlflow.pyfunc.load_model(logged_model)


with open(f'{logged_model}/input_example.json') as f:
    data = json.load(f)
    input_example = np.array(data['inputs'][0])
    input_example = Variable(torch.from_numpy(input_example)).float()

loaded_model.predict(input_example)