code: def convert_sklearn_variance_threshold(
      operator, device, extra_config
  ):
      """
      Converter for `sklearn.feature_selection.VarianceThreshold`.
  
      Args:
          operator: An operator wrapping a `sklearn.feature_selection.VarianceThreshold` model
          device: String defining the type of device the converted operator should be run on
          extra_config: Extra configuration used to select the best conversion strategy
  
      Returns:
          A PyTorch model
      """
      assert operator is not None, "Cannot convert None operator"
  
      var = operator.raw_operator.variances_
      threshold = operator.raw_operator.threshold
      indices = np.array(
          [i for i in range(len(var)) if var[i] > threshold]
      )
      return ArrayFeatureExtractor(
          operator, np.ascontiguousarray(indices), device
      )
  
imports: import numpy
  from onnxconverter_common.registration import register_converter
  from .._array_feature_extractor_implementations import ArrayFeatureExtractor
label_desc: Use image node_id 2 for calling a global function with example usage: convert_sklearn_variance_threshold(operator, device, extra_config) and returns: ArrayFeatureExtractor