transformer_model/scripts/utils/model_loader_wrapper.py

from streamlit_simulation.utils.env import use_dummy
from transformer_model.scripts.config_transformer import FORECAST_HORIZON
from transformer_model.scripts.utils.informer_dataset_class import \
    InformerDataset
from transformer_model.scripts.utils.load_final_model import \
    load_real_transformer_model

try:
    from streamlit_simulation.utils.dummy import (DummyDataset,
                                                  DummyTransformerModel)
except ImportError:
    DummyTransformerModel = None
    DummyDataset = None


def load_final_transformer_model():
    if use_dummy():
        if DummyTransformerModel is None:
            raise ImportError("DummyTransformerModel not available")
        return DummyTransformerModel(), "cpu"
    else:
        return load_real_transformer_model()


def load_model_and_dataset():
    model, device = load_final_transformer_model()

    if use_dummy():
        if DummyDataset is None:
            raise ImportError("DummyDataset not available")
        dataset = DummyDataset(length=200)
    else:
        train_dataset = InformerDataset(
            data_split="train", random_seed=13, forecast_horizon=FORECAST_HORIZON
        )
        test_dataset = InformerDataset(
            data_split="test", random_seed=13, forecast_horizon=FORECAST_HORIZON
        )
        test_dataset.scaler = train_dataset.scaler
        dataset = test_dataset

    return model, dataset, device