code: def denormalize(self, input_vector):
      if type(input_vector) == np.ndarray:
          input_vector = torch.from_numpy(input_vector)
      input_vector = input_vector.to(**self.tpdv)
      mean, var = self.debiased_mean_var()
      out = (
          input_vector * torch.sqrt(var)[(None,) * self.norm_axes]
          + mean[(None,) * self.norm_axes]
      )
      out = out.cpu().numpy()
      return out
  
imports: import torch
  import torch.nn
  from torch.distributions import Categorical
  import numpy
  import parl
label_desc: Use image node_id 6 for calling the PopArt obj's underlying member method code with example usage: obj.denormalize(input_vector) and returns: out