code: def randn_like(x):
      """Generate a tensor with random numbers from a normal distribution using the previously initialized genrator.
  
      Use either randn() or manual_seed() to initialize the generator.
      """
  
      if shared.opts.randn_source == "NV":
          return torch.asarray(
              nv_rng.randn(x.shape), device=x.device, dtype=x.dtype
          )
  
      if shared.opts.randn_source == "CPU" or x.device.type == "mps":
          return torch.randn_like(x, device=devices.cpu).to(x.device)
  
      return torch.randn_like(x)
  
file_path: stable-diffusion-webui/modules/rng.py
imports: import torch
  from modules import devices, rng_philox, shared
label_desc: Use image node_id 3 for calling a global function with example usage: randn_like(x) and returns: torch, torch, torch