class_docstr: Block for structured data.
  
  # Arguments
      categorical_encoding: Boolean. Whether to use the CategoricalToNumerical
          to encode the categorical features to numerical features. Defaults
          to True.
      normalize: Boolean. Whether to normalize the features.
          If unspecified, it will be tuned automatically.
      seed: Int. Random seed.
code: def from_config(cls, config):
      column_types = config.pop("column_types")
      column_names = config.pop("column_names")
      instance = cls(**config)
      instance.column_types = column_types
      instance.column_names = column_names
      return instance
  
imports: from typing import Optional
  from tensorflow import nest
  from autokeras.blocks import basic
  from autokeras.blocks import preprocessing
  from autokeras.blocks import reduction
  from autokeras.engine import block
label_desc: Use image node_id 2 for calling the StructuredDataBlock obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: instance