class_docstr: Encode the categorical features to numerical features.
class_docstr_tok: ["Encode","the","categorical","features","to","numerical","features","."]
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 typing import Tuple
  from typing import Union
  from keras_tuner.engine import hyperparameters
  from tensorflow import nest
  from tensorflow.keras import layers
  from autokeras import analysers
  from autokeras import keras_layers
  from autokeras.engine import block
  from autokeras.utils import io_utils
  from autokeras.utils import utils
label_desc: Use image node_id 3 for calling the CategoricalToNumerical obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: instance