code: def _load_or_randn(size, init_values, seed, device):
      if init_values is None:
          rng = get_rng(seed)
          tensor = normal(
              size,
              mean=0.0,
              std=0.001,
              random_state=rng,
              dtype=np.double,
          )
          tensor = torch.tensor(
              tensor, requires_grad=True, device=device
          )
      else:
          tensor = torch.tensor(
              init_values, requires_grad=True, device=device
          )
      return tensor
  
file_path: cornac/cornac/models/vmf/vmf.py
imports: from tqdm.auto import tqdm
  import numpy
  import torch
  from ...utils.common import scale
  from ...utils.init_utils import normal
  from ...utils import get_rng
label_desc: Use image node_id 1 for calling a global function with example usage: _load_or_randn(size, init_values, seed, device) and returns: tensor