class_docstr: Data object used for all RasaModels.
  
  It contains all features needed to train the models.
  'data' is a mapping of attribute name, e.g. TEXT, INTENT, etc., and feature name,
  e.g. SENTENCE, SEQUENCE, etc., to a list of feature arrays representing the actual
  features.
  'label_key' and 'label_sub_key' point to the labels inside 'data'. For
  example, if your intent labels are stored under INTENT -> IDS, 'label_key' would
  be "INTENT" and 'label_sub_key' would be "IDS".
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docstr: Adds a dictionary of feature sizes for different attributes.
  
  Args:
      sparse_feature_sizes: a dictionary of attribute that has sparse
                     features to a dictionary of a feature type
                     to a list of different sparse feature sizes.
docstr_tok: ["Adds","a","dictionary","of","feature","sizes","for","different","attributes",".","Args",":","sparse_feature_sizes",":","a","dictionary","of","attribute","that","has","sparse","features","to","a","dictionary","of","a","feature","type","to","a","list","of","different","sparse","feature","sizes","."]
code: def add_sparse_feature_sizes(
      self, sparse_feature_sizes: Dict[Text, Dict[Text, List[int]]]
  ) -> None:
      """Adds a dictionary of feature sizes for different attributes.
  
      Args:
          sparse_feature_sizes: a dictionary of attribute that has sparse
                         features to a dictionary of a feature type
                         to a list of different sparse feature sizes.
      """
      self.sparse_feature_sizes = sparse_feature_sizes
  
imports: import logging
  from typing import Optional, DefaultDict, Dict, Iterable, Text, List, Tuple, Any, Union, NamedTuple, ItemsView, overload, cast
  from collections import defaultdict, OrderedDict
  import numpy
  import scipy.sparse
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 19 for calling the RasaModelData obj's underlying member method code with example usage: obj.add_sparse_feature_sizes(sparse_feature_sizes) without return types