code: def __init__(self, metadata: TrainingSetMetadataDict):
      super().__init__()
      self.max_h3_resolution = MAX_H3_RESOLUTION
      self.h3_padding_value = H3_PADDING_VALUE
      self.computed_fill_value = float(
          metadata["preprocessing"]["computed_fill_value"]
      )
  
imports: import logging
  from typing import List
  import numpy
  import torch
  from ludwig.constants import COLUMN, H3, PROC_COLUMN
  from ludwig.features.base_feature import BaseFeatureMixin, InputFeature
  from ludwig.schema.features.h3_feature import H3InputFeatureConfig
  from ludwig.types import FeatureMetadataDict, ModelConfigDict, PreprocessingConfigDict, TrainingSetMetadataDict
  from ludwig.utils.h3_util import h3_to_components
  from ludwig.utils.types import TorchscriptPreprocessingInput
label_desc: Use image node_id 1 to create a new _H3Preprocessing object from inherited base classes: torch.nn with example: obj = _H3Preprocessing(metadata)