code: def postprocess_predictions(
      self,
      result,
      metadata,
  ):
      predictions_col = f"{self.feature_name}_{PREDICTIONS}"
      if predictions_col in result:
  
          def idx2str(pred_set):
              return [
                  metadata["idx2str"][i]
                  for i, pred in enumerate(pred_set)
                  if pred
              ]
  
          result[predictions_col] = result[predictions_col].map(idx2str)
  
      probabilities_col = f"{self.feature_name}_{PROBABILITIES}"
      if probabilities_col in result:
  
          def get_prob(prob_set):
              # Cast to float32 because empty np.array objects are np.float64, causing mismatch errors during saving.
              return np.array(
                  [prob for prob in prob_set if prob >= self.threshold],
                  dtype=np.float32,
              )
  
          result[probabilities_col] = result[probabilities_col].map(
              get_prob
          )
  
      return result
  
imports: import logging
  from typing import Any, Dict, List, Union
  import numpy
  import torch
  from ludwig.constants import COLUMN, HIDDEN, LOGITS, NAME, PREDICTIONS, PROBABILITIES, PROC_COLUMN, SET
  from ludwig.features.base_feature import BaseFeatureMixin, InputFeature, OutputFeature, PredictModule
  from ludwig.features.feature_utils import set_str_to_idx
  from ludwig.schema.features.set_feature import SetInputFeatureConfig, SetOutputFeatureConfig
  from ludwig.types import FeatureMetadataDict, FeaturePostProcessingOutputDict, ModelConfigDict, PreprocessingConfigDict, TrainingSetMetadataDict
  from ludwig.utils import output_feature_utils
  from ludwig.utils.strings_utils import create_vocabulary, UNKNOWN_SYMBOL
  from ludwig.utils.tokenizers import get_tokenizer_from_registry, TORCHSCRIPT_COMPATIBLE_TOKENIZERS
  from ludwig.utils.types import TorchscriptPreprocessingInput
label_desc: Use image node_id 11 for calling the SetOutputFeature obj's underlying member method code with example usage: obj.postprocess_predictions(result, metadata) and returns: result, unknown, np