docstr: Get a mask, or integer index, of the features selected.
  
  Parameters
  ----------
  indices : bool
      Default False
      If True, the return value will be an array of integers, rather than a boolean mask.
  
  Returns
  -------
  list :
      returns support: An index that selects the retained features from a feature vector.
      If indices is False, this is a boolean array of shape [# input features],
      in which an element is True iff its corresponding feature is selected for retention.
      If indices is True, this is an integer array of shape [# output features] whose values
      are indices into the input feature vector.
docstr_tok: ["Get","a","mask",",","or","integer","index",",","of","the","features","selected",".","Parameters","--","--","--","--","--","indices",":","bool","Default","False","If","True",",","the","return","value","will","be","an","array","of","integers",",","rather","than","a","boolean","mask",".","Returns","--","--","--","-","list",":","returns","support",":","An","index","that","selects","the","retained","features","from","a","feature","vector",".","If","indices","is","False",",","this","is","a","boolean","array","of","shape","[","#","input","features","]",",","in","which","an","element","is","True","iff","its","corresponding","feature","is","selected","for","retention",".","If","indices","is","True",",","this","is","an","integer","array","of","shape","[","#","output","features","]","whose","values","are","indices","into","the","input","feature","vector","."]
code: def get_support(self, indices=False):
      """
      Get a mask, or integer index, of the features selected.
  
      Parameters
      ----------
      indices : bool
          Default False
          If True, the return value will be an array of integers, rather than a boolean mask.
  
      Returns
      -------
      list :
          returns support: An index that selects the retained features from a feature vector.
          If indices is False, this is a boolean array of shape [# input features],
          in which an element is True iff its corresponding feature is selected for retention.
          If indices is True, this is an integer array of shape [# output features] whose values
          are indices into the input feature vector.
      """
      self._get_support_mask()
      if indices:
          return self.selected_features_
  
      mask = np.zeros_like(self.scores_, dtype=bool)
      # pylint: disable=E1137
      mask[self.selected_features_] = True
      return mask
  
imports: import time
  import numpy
  import pandas
  from sklearn.base import BaseEstimator
  from sklearn.feature_selection import SelectorMixin
  from sklearn.utils.validation import check_is_fitted
  import torch
  from nni.feature_engineering.feature_selector import FeatureSelector
  from .None import constants
  from .fginitialize import PrepareData
  from .fgtrain import _train
label_desc: Use image node_id 12 for calling the FeatureGradientSelector obj's underlying member method code with example usage: obj.get_support(indices) and returns: mask, self