code: def test_interpretation(model, dataloaders_with_covariates):
      raw_predictions = model.predict(
          dataloaders_with_covariates["val"],
          mode="raw",
          return_x=True,
          fast_dev_run=True,
      )
      model.plot_prediction(
          raw_predictions.x,
          raw_predictions.output,
          idx=0,
          add_loss_to_title=True,
      )
      model.plot_interpretation(
          raw_predictions.x, raw_predictions.output, idx=0
      )
  
file_path: pytorch-forecasting/tests/test_models/test_nhits.py
imports: import pickle
  import shutil
  import lightning.pytorch
  from lightning.pytorch.callbacks import EarlyStopping
  from lightning.pytorch.loggers import TensorBoardLogger
  import pytest
  from pytorch_forecasting.metrics import MQF2DistributionLoss, QuantileLoss
  from pytorch_forecasting.metrics.distributions import ImplicitQuantileNetworkDistributionLoss
  from pytorch_forecasting.models import NHiTS
label_desc: Use image node_id 5 for calling a global function with example usage: test_interpretation(model, dataloaders_with_covariates) without return types