class_docstr: This is a more standard version of the position embedding, very similar
  to the one used by the Attention is all you need paper, generalized to work
  on images.
class_docstr_tok: ["This","is","a","more","standard","version","of","the","position","embedding",",","very","similar","to","the","one","used","by","the","Attention","is","all","you","need","paper",",","generalized","to","work","on","images","."]
code: def __repr__(self, _repr_indent=4):
      head = "Positional encoding " + self.__class__.__name__
      body = [
          "num_pos_feats: {}".format(self.num_pos_feats),
          "temperature: {}".format(self.temperature),
          "normalize: {}".format(self.normalize),
          "scale: {}".format(self.scale),
      ]
      # _repr_indent = 4
      lines = [head] + [" " * _repr_indent + line for line in body]
      return "\n".join(lines)
  
imports: import copy
  import math
  from typing import Optional
  import torch
  import torch.nn.functional
  from torch import Tensor, nn
label_desc: Use image node_id 3 for calling the PositionEmbeddingSine obj's underlying member method code with example usage: obj.__repr__(_repr_indent) and returns: str