code: def orthogonal(shape, scale=1.1):
      """
      Initialization function for weights in class GCMC.
      From Lasagne. Reference: Saxe et al., http://arxiv.org/abs/1312.6120
      """
      flat_shape = (shape[0], np.prod(shape[1:]))
      a = np.random.normal(0.0, 1.0, flat_shape)
      u, _, v = np.linalg.svd(a, full_matrices=False)
  
      # pick the one with the correct shape
      q = u if u.shape == flat_shape else v
      q = q.reshape(shape)
      return torch.tensor(
          scale * q[: shape[0], : shape[1]], dtype=torch.float32
      )
  
imports: import math
  import numpy
  import scipy.sparse
  import torch
  import torch.nn
  from recbole.model.abstract_recommender import GeneralRecommender
  from recbole.model.layers import SparseDropout
  from recbole.utils import InputType
label_desc: Use image node_id 1 for calling a global function with example usage: orthogonal(shape, scale) and returns: torch