code: def torch_backward(x, retain_graph=None):
      """
      Like ``x.backward()`` for a :class:`~torch.Tensor`, but also accepts
      numbers and tensors without grad_fn (resulting in a no-op)
      """
      if torch.is_tensor(x) and x.grad_fn:
          x.backward(retain_graph=retain_graph)
  
imports: import math
  import numbers
  from collections import Counter, defaultdict
  from contextlib import contextmanager
  import torch
  from opt_einsum import shared_intermediates
  from opt_einsum.sharing import count_cached_ops
  from pyro.distributions.util import is_identically_zero
  from pyro.ops import packed
  from pyro.ops.einsum.adjoint import require_backward
  from pyro.ops.rings import MarginalRing
  from pyro.poutine.util import site_is_subsample
  from ..None import settings
label_desc: Use image node_id 5 for calling a global function with example usage: torch_backward(x, retain_graph) without return types