class_docstr: Class implementing Imputer operators in MissingIndicator.
code: def __init__(self, logical_operator, device):
      super(MissingIndicator, self).__init__(logical_operator)
      sklearn_missing_indicator = logical_operator.raw_operator
      self.transformer = True
      self.missing_values = torch.nn.Parameter(
          torch.tensor(
              [sklearn_missing_indicator.missing_values],
              dtype=torch.float32,
          ),
          requires_grad=False,
      )
      self.features = sklearn_missing_indicator.features
      self.is_nan = (
          True
          if (
              sklearn_missing_indicator.missing_values
              in ["NaN", None, np.nan]
          )
          else False
      )
      self.column_indices = torch.nn.Parameter(
          torch.LongTensor(sklearn_missing_indicator.features_),
          requires_grad=False,
      )
  
file_path: hummingbird/hummingbird/ml/operator_converters/_imputer_implementations.py
imports: import torch
  import numpy
  from ._physical_operator import PhysicalOperator
  from .None import constants
label_desc: Use image node_id 1 to create a new MissingIndicator object from inherited base classes: PhysicalOperator, torch.nn with example: obj = MissingIndicator(logical_operator, device)