code: def __init__(
      self,
      features=None,
      excluded_features=None,
      output_column_prefix=None,
      column_interpretations=None,
      verbose=True,
  ):
      self._setup()
  
      _features, _exclude = _internal_utils.process_features(
          features, excluded_features
      )
  
      # Check the column_interpretations parameter type
      if column_interpretations is None:
          column_interpretations = {}
  
      if not isinstance(column_interpretations, dict) or not all(
          isinstance(k, str) and isinstance(v, str)
          for k, v in column_interpretations.items()
      ):
          raise TypeError(
              "`column_interpretations` must be a dictionary of "
              "column names to interpretation strings."
          )
  
      state = {}
      state[
          "user_column_interpretations"
      ] = column_interpretations.copy()
      state["column_interpretations"] = column_interpretations.copy()
      state["output_column_prefix"] = output_column_prefix
      state["fitted"] = False
      state["verbose"] = verbose
  
      state["transforms"] = {}
      state["transform_chain"] = None
  
      state["features"] = _features
      state["excluded_features"] = _exclude
  
      if _exclude:
          self._exclude = True
          self._features = _exclude
      else:
          self._exclude = False
          self._features = _features
  
      self.__proxy__.update(state)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from .None import TransformerBase
  from .None import TransformerChain
  from .None import TransformToFlatDictionary
  from turicreate.toolkits._model import PythonProxy
  from turicreate.toolkits._model import ExposeAttributesFromProxy
  from turicreate.toolkits._internal_utils import _toolkit_repr_print
  from turicreate.toolkits._internal_utils import _precomputed_field
  from turicreate.toolkits._internal_utils import _raise_error_if_not_sframe
  from turicreate.util import _raise_error_if_not_of_type
  from turicreate.toolkits._internal_utils import _check_categorical_option_type
  from .None import _internal_utils
  from array import array
  import textwrap
  from turicreate import SFrame
  import turicreate
label_desc: Use image node_id 3 to create a new AutoVectorizer object from inherited base classes: _TransformerBase, ExposeAttributesFromProxy with example: obj = AutoVectorizer(features, excluded_features, output_column_prefix, column_interpretations, verbose)