code: def safe_cholesky(x):
      if x.size(-1) == 1:
          if CHOLESKY_RELATIVE_JITTER:
              x = x.clamp(min=torch.finfo(x.dtype).tiny)
          return x.sqrt()
  
      if CHOLESKY_RELATIVE_JITTER:
          # Add adaptive jitter.
          x = x.clone()
          x_max = x.data.abs().max(-1).values
          jitter = (
              CHOLESKY_RELATIVE_JITTER
              * torch.finfo(x.dtype).eps
              * x_max
          )
          x.data.diagonal(dim1=-1, dim2=-2).add_(jitter)
  
      return torch.linalg.cholesky(x)
  
imports: import math
  import torch
  from torch.fft import irfft, rfft
  from ..None import settings
label_desc: Use image node_id 15 for calling a global function with example usage: safe_cholesky(x) and returns: torch, x