code: def init_empty_grad(emb_dimension, walk_length, batch_size):
      """initialize gradient matrix"""
      grad_u = torch.zeros((batch_size * walk_length, emb_dimension))
      grad_v = torch.zeros((batch_size * walk_length, emb_dimension))
  
      return grad_u, grad_v
  
imports: import random
  import numpy
  import torch
  import torch.multiprocessing
  import torch.nn
  import torch.nn.functional
  from torch.multiprocessing import Queue
  from torch.nn import init
label_desc: Use image node_id 4 for calling a global function with example usage: init_empty_grad(emb_dimension, walk_length, batch_size) and returns: grad_u,  grad_v