class_docstr: Generate normal vectors for each mesh node based on neighboring
  faces (functional name: :obj:`generate_mesh_normals`).
code: def forward(self, data: Data) -> Data:
      assert data.pos is not None
      assert data.face is not None
      pos, face = data.pos, data.face
  
      vec1 = pos[face[1]] - pos[face[0]]
      vec2 = pos[face[2]] - pos[face[0]]
      face_norm = F.normalize(vec1.cross(vec2), p=2, dim=-1)  # [F, 3]
  
      face_norm = face_norm.repeat(3, 1)
      idx = face.view(-1)
  
      norm = scatter(face_norm, idx, 0, pos.size(0), reduce="sum")
      norm = F.normalize(norm, p=2, dim=-1)  # [N, 3]
  
      data.norm = norm
  
      return data
  
imports: import torch.nn.functional
  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 scatter
label_desc: Use image node_id 1 for calling the GenerateMeshNormals obj's underlying member method code with example usage: obj.forward(data) and returns: data