code: def _predict_process_ids(user_ids, item_ids, num_items, use_cuda):
      if item_ids is None:
          item_ids = np.arange(num_items, dtype=np.int64)
  
      if np.isscalar(user_ids):
          user_ids = np.array(user_ids, dtype=np.int64)
  
      user_ids = torch.from_numpy(
          user_ids.reshape(-1, 1).astype(np.int64)
      )
      item_ids = torch.from_numpy(
          item_ids.reshape(-1, 1).astype(np.int64)
      )
  
      if item_ids.size()[0] != user_ids.size(0):
          user_ids = user_ids.expand(item_ids.size())
  
      user_var = gpu(user_ids, use_cuda)
      item_var = gpu(item_ids, use_cuda)
  
      return user_var.squeeze(), item_var.squeeze()
  
imports: import numpy
  import torch
  from spotlight.torch_utils import gpu
label_desc: Use image node_id 1 for calling a global function with example usage: _predict_process_ids(user_ids, item_ids, num_items, use_cuda) and returns: user_var,  item_var