code: def msg_func(edges):
      """
  
      Description
      -----------
      Send messages along edges.
  
      Parameters
      ----------
      edges : EdgeBatch
          A batch of edges.
  
      Returns
      -------
      dict mapping 'm' to Float32 tensor of shape (E, K * T)
          Messages computed. E for the number of edges, K for the number of
          radial filters and T for the number of features to use
          (types of atomic number in the paper).
      """
      return {
          "m": th.einsum(
              "ij,ik->ijk", edges.src["hv"], edges.data["he"]
          ).view(len(edges), -1)
      }
  
file_path: dgl/python/dgl/nn/pytorch/conv/atomicconv.py
imports: import numpy
  import torch
  import torch.nn
label_desc: Use image node_id 1 for calling a global function with example usage: msg_func(edges) and returns: dict