code: def __init__(
      self,
      input_feature_config: BagInputFeatureConfig,
      encoder_obj=None,
      **kwargs,
  ):
      super().__init__(input_feature_config, **kwargs)
  
      if encoder_obj:
          self.encoder_obj = encoder_obj
      else:
          self.encoder_obj = self.initialize_encoder(
              input_feature_config.encoder
          )
  
imports: import logging
  from collections import Counter
  import numpy
  import torch
  from ludwig.constants import BAG, COLUMN, NAME, PROC_COLUMN
  from ludwig.features.base_feature import BaseFeatureMixin, InputFeature
  from ludwig.features.feature_utils import set_str_to_idx
  from ludwig.features.set_feature import _SetPreprocessing
  from ludwig.schema.features.bag_feature import BagInputFeatureConfig
  from ludwig.types import FeatureMetadataDict, ModelConfigDict, PreprocessingConfigDict, TrainingSetMetadataDict
  from ludwig.utils.strings_utils import create_vocabulary
label_desc: Use image node_id 1 to create a new BagInputFeature object from inherited base classes: BagFeatureMixin, InputFeature with example: obj = BagInputFeature(input_feature_config, encoder_obj)