code: def safe_grad(t):
      with warnings.catch_warnings():
          warnings.filterwarnings(
              "ignore", "The .grad attribute of a Tensor"
          )
          return t.grad
  
imports: import contextlib
  import warnings
  import weakref
  from typing import ContextManager, List, Optional, Tuple, TYPE_CHECKING
  import torch
  from torch._C._functorch import _add_batch_dim, _unwrap_functional_tensor, _wrap_functional_tensor, current_level, get_unwrapped, is_batchedtensor, maybe_get_bdim, maybe_get_level, peek_interpreter_stack, TransformType
  from torch._guards import Source
  from torch.multiprocessing.reductions import StorageWeakRef
  from torch.utils._python_dispatch import is_traceable_wrapper_subclass, transform_subclass
  from torch.utils.weak import WeakIdRef
  import torch._prims_common
label_desc: Use image node_id 2 for calling a global function with example usage: safe_grad(t) and returns: t