Minimal GluonTS / DeepAR example

gluonts_deepar_minimal.py

import pandas as pd
import numpy as np
import mxnet as mx
from gluonts.dataset.pandas import PandasDataset
from gluonts.dataset.split import split
from gluonts.mx import DeepAREstimator, Trainer
from gluonts.model.predictor import Predictor
from pathlib import Path

def train_model():
    model = DeepAREstimator(
        prediction_length=12, freq="M", trainer=Trainer(epochs=5)
    ).train(training_data)
    model.serialize(Path("temp"))


df = pd.read_csv(
    "https://raw.githubusercontent.com/AileenNielsen/"
    "TimeSeriesAnalysisWithPython/master/data/AirPassengers.csv",
    index_col=0,
    parse_dates=True,
)
dataset = PandasDataset(df, target="#Passengers")
training_data, test_gen = split(dataset, offset=-36)

# commenting if reusing model
#train_model()

model = Predictor.deserialize(Path("temp"), ctx=mx.gpu(0))

test_data = test_gen.generate_instances(prediction_length=12, windows=3)

np.random.seed(42)
mx.random.seed(42)
forecasts = list(model.predict(test_data.input))
print(forecasts[0].median)