code: def _baseline_forward(self, inp):
      if self.baseline_inp is None:
          self.baseline_inp = inp.data.clone()
          self.baseline_inp.fill_(0.0)
          self.baseline_inp = Variable(self.baseline_inp)
      else:
          self.baseline_inp.fill_(0.0)
      # get ref
      _ = self.model(self.baseline_inp)
  
file_path: tensorwatch/tensorwatch/saliency/deeplift.py
imports: from .backprop import GradxInputExplainer
  import types
  import torch.nn.functional
  from torch.autograd import Variable
label_desc: Use image node_id 4 for calling the DeepLIFTRescaleExplainer obj's underlying member method code with example usage: obj._baseline_forward(inp) without return types