code: def logits(self, inputs, **kwargs):  # hidden
      hidden = inputs[HIDDEN]
      return self.decoder_obj(hidden)
  
imports: import logging
  from typing import Dict, List, Union
  import numpy
  import torch
  from ludwig.constants import COLUMN, HIDDEN, LOGITS, NAME, PREDICTIONS, PROC_COLUMN, VECTOR
  from ludwig.features.base_feature import InputFeature, OutputFeature, PredictModule
  from ludwig.schema.features.vector_feature import VectorInputFeatureConfig, VectorOutputFeatureConfig
  from ludwig.types import FeatureMetadataDict, FeaturePostProcessingOutputDict, ModelConfigDict, PreprocessingConfigDict, TrainingSetMetadataDict
  from ludwig.utils import output_feature_utils
  from ludwig.utils.types import TorchscriptPreprocessingInput
label_desc: Use image node_id 2 for calling the VectorOutputFeature obj's underlying member method code with example usage: obj.logits(inputs) and returns: self