code: def forward(self, x, step=None):
      if step is None:
          x = x + self.pe[: x.size(1), :]
      else:
          x = x + self.pe[:, step]
      return self.dropout(x)
  
imports: from collections import OrderedDict
  import os
  import numpy
  import torch
  from torch import nn
  from gluoncv.torch.utils.coot_utils import truncated_normal_fill
label_desc: Use image node_id 2 for calling the PositionalEncoding obj's underlying member method code with example usage: obj.forward(x, step) and returns: self