class_docstr: Saves the globally normalized degree of target nodes
  (functional name: :obj:`target_indegree`).
  
  .. math::
  
      \mathbf{u}(i,j) = \frac{\deg(j)}{\max_{v \in \mathcal{V}} \deg(v)}
  
  in its edge attributes.
  
  Args:
      cat (bool, optional): Concat pseudo-coordinates to edge attributes
          instead of replacing them. (default: :obj:`True`)
class_docstr_tok: ["Saves","the","globally","normalized","degree","of","target","nodes","(","functional","name",":",":","obj",":","`","target_indegree","`",")",".","..","math",":",":","\\mathbf","{","u","}","(","i",",","j",")","=","\\frac","{","\\deg","(","j",")","}","{","\\max_","{","v","\\in","\\mathcal","{","V","}","}","\\deg","(","v",")","}","in","its","edge","attributes",".","Args",":","cat","(","bool",",","optional",")",":","Concat","pseudo-coordinates","to","edge","attributes","instead","of","replacing","them",".","(","default",":",":","obj",":","`","True","`",")"]
code: def __repr__(self) -> str:
      return (
          f"{self.__class__.__name__}(norm={self.norm}, "
          f"max_value={self.max})"
      )
  
file_path: pytorch_geometric/torch_geometric/transforms/target_indegree.py
imports: from typing import Optional
  import torch
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
  from torch_geometric.utils import degree
label_desc: Use image node_id 3 for calling the TargetIndegree obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str