class_docstr: The same data information shared by the WideAndDeep model and its feature generation part.
  
  Each instance could contain the following fields:
  wide_base_cols: Data of wide_base_cols together with wide_cross_cols will be fed
                  into the wide model. List of String. Default is an empty list.
  wide_base_dims: Dimensions of wide_base_cols. The dimensions of the data in
                  wide_base_cols should be within the range of wide_base_dims.
                  List of int. Default is an empty list.
  wide_cross_cols: Data of wide_cross_cols will be fed into the wide model.
                   List of String. Default is an empty list.
  wide_cross_dims: Dimensions of wide_cross_cols. The dimensions of the data in
                   wide_cross_cols should be within the range of wide_cross_dims.
                   List of int. Default is an empty list.
  indicator_cols: Data of indicator_cols will be fed into the deep model as multi-hot vectors.
                  List of String. Default is an empty list.
  indicator_dims: Dimensions of indicator_cols. The dimensions of the data in
                  indicator_cols should be within the range of indicator_dims.
                  List of int. Default is an empty list.
  embed_cols: Data of embed_cols will be fed into the deep model as embeddings.
              List of String. Default is an empty list.
  embed_in_dims: Input dimension of the data in embed_cols. The dimensions of the data in
                 embed_cols should be within the range of embed_in_dims.
                 List of int. Default is an empty list.
  embed_out_dims: The dimensions of embeddings. List of int. Default is an empty list.
  continuous_cols: Data of continuous_cols will be treated as continuous values for
                   the deep model. List of String. Default is an empty list.
  label: The name of the 'label' column. String. Default is 'label'.
code: def __init__(
      self,
      wide_base_cols=None,
      wide_base_dims=None,
      wide_cross_cols=None,
      wide_cross_dims=None,
      indicator_cols=None,
      indicator_dims=None,
      embed_cols=None,
      embed_in_dims=None,
      embed_out_dims=None,
      continuous_cols=None,
      label="label",
      bigdl_type="float",
  ):
      self.wide_base_cols = [] if not wide_base_cols else wide_base_cols
      self.wide_base_dims = (
          [] if not wide_base_dims else [int(d) for d in wide_base_dims]
      )
      self.wide_cross_cols = (
          [] if not wide_cross_cols else wide_cross_cols
      )
      self.wide_cross_dims = (
          []
          if not wide_cross_dims
          else [int(d) for d in wide_cross_dims]
      )
      self.indicator_cols = [] if not indicator_cols else indicator_cols
      self.indicator_dims = (
          [] if not indicator_dims else [int(d) for d in indicator_dims]
      )
      self.embed_cols = [] if not embed_cols else embed_cols
      self.embed_in_dims = (
          [] if not embed_in_dims else [int(d) for d in embed_in_dims]
      )
      self.embed_out_dims = (
          [] if not embed_out_dims else [int(d) for d in embed_out_dims]
      )
      self.continuous_cols = (
          [] if not continuous_cols else continuous_cols
      )
      self.label = label
      self.bigdl_type = bigdl_type
  
imports: from __future__ import division, print_function, unicode_literals
  import sys
  import os
  import math
  from optparse import OptionParser
  from time import time
  import tempfile
  from bigdl.friesian.utils import SafePickle
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.data.file import exists, makedirs
  from bigdl.friesian.feature import FeatureTable
  from bigdl.dllib.utils.file_utils import get_remote_file_to_local
  from bigdl.orca.learn.tf2.estimator import Estimator
  import tensorflow
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 1 to create a new ColumnFeatureInfo object from inherited base classes: object with example: obj = ColumnFeatureInfo(wide_base_cols, wide_base_dims, wide_cross_cols, wide_cross_dims, indicator_cols, indicator_dims, embed_cols, embed_in_dims, embed_out_dims, continuous_cols, label, bigdl_type)