tft_train1

# training: load a saved model or (re)train
if LOAD:
    print("have loaded a previously saved model from disk:" + mpath)
    model = TFTModel.load_model(mpath)                            # load previously model from disk 
else:
    model.fit(  series=ts_ttrain, 
                future_covariates=cov_t, 
                val_series=ts_ttest, 
                val_future_covariates=cov_t, 
                verbose=True)
    print("have saved the model after training:", mpath)
    model.save_model(mpath)