raise Exception("Validation dataset is empty. Provide valid validation data for early stopping.")
if self._params.preload_training:
data = self.scenario.data = self.scenario.create_data().to_raw_dataset(progress_bar=self._params.progress_bar)
// compute the codec
codec = data.params().codec
After Change
raise Exception("Training dataset is empty.")
if data.params().val:
val_pipeline = data.get_pipeline(PipelineMode.Evaluation, data.params().val)
if len(val_pipeline) == 0:
raise Exception("Validation dataset is empty. Provide valid validation data for early stopping.")
else: