Afiq Johari
07/05/2023, 6:37 AMtune
configuration when running the Auto
models?
For instance, the Auto
models utilize the tune
and ray
packages, which are automatically invoked by the Auto
models themselves. I like more control over the behavior of ray
and tune
, particularly regarding the output directory and the number of CPUs to allocate.
nf = NeuralForecast(
models=[
AutoNHITS(h=48, config=config_nhits, loss=MQLoss(), num_samples=5),
AutoLSTM(h=48, loss=MQLoss(), num_samples=2),
],
freq='H'
)
nf.fit(df=Y_df)
Appreciate any guidance on this 🙏
https://nixtla.github.io/neuralforecast/examples/getting_started_complete.htmlCristian (Nixtla)
07/05/2023, 12:46 PMinit
method of the auto
models:results
object within the model, so you can then manually export it to any directoryresults
object here: https://nixtla.github.io/neuralforecast/examples/automatic_hyperparameter_tuning.html