docstr: Check if it is fitted.
docstr_tok: ["Check","if","it","is","fitted","."]
code: def _get_support_mask(self):
      """
      Check if it is fitted.
      """
      check_is_fitted(self, "scores_")
  
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 17 for calling the FeatureGradientSelector obj's underlying member method code with example usage: obj._get_support_mask() without return types