code: def forward(self, frames) -> pd.DataFrame:
      outcome = []
      predictions = self.model(frames)
      for prediction in predictions:
          label = self.as_numpy(prediction.data.argmax())
          outcome.append({"label": str(label)})
  
      return pd.DataFrame(outcome, columns=["label"])
  
file_path: evadb/evadb/functions/mnist_image_classifier.py
imports: from collections import OrderedDict
  import pandas
  from evadb.functions.abstract.pytorch_abstract_function import PytorchAbstractClassifierFunction
  from evadb.utils.generic_utils import try_to_import_torch, try_to_import_torchvision
label_desc: Use image node_id 5 for calling the MnistImageClassifier obj's underlying member method code with example usage: obj.forward(frames) and returns: pd