code: def cast_column(column, backend):
      try:
          return column.astype(int)
      except ValueError:
          logger.warning(
              "H3Feature could not be read as int directly. Reading as float and converting to int."
          )
          return column.astype(float).astype(int)
  
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 2 for calling the H3FeatureMixin obj's underlying member method code with example usage: obj.cast_column(column, backend) and returns: column, column