class_docstr: A torch.Tensor input or an intermediate value in the FX graph
class_docstr_tok: ["A","torch.Tensor","input","or","an","intermediate","value","in","the","FX","graph"]
code: def _strict_mode_banned_ops(self):
      return (
          torch._dynamo.config._autograd_backward_strict_mode_banned_ops
      )
  
imports: import functools
  import inspect
  import operator
  import types
  from typing import Dict, List
  import sympy
  import torch._numpy
  import torch.fx
  import torch.random
  from torch._dynamo import compiled_autograd
  from torch.fx.experimental.symbolic_shapes import guard_scalar, GuardOnDataDependentSymNode, has_free_symbols, is_symbolic, SymTypes
  from ..None import config, variables
  from .._trace_wrapped_higher_order_op import trace_wrapped
  from ..exc import unimplemented, UserError, UserErrorType
  from ..guards import GuardBuilder, install_guard
  from ..source import AttrSource
  from ..utils import fqn, get_custom_getattr, get_fake_value, get_real_value, guard_if_dyn, object_has_getattribute, product, proxy_args_kwargs, tensortype_to_dtype
  from .base import VariableTracker
  from .constant import ConstantVariable
  from .lists import SizeVariable
label_desc: Use image node_id 10 for calling the TensorVariable obj's underlying member method code with example usage: obj._strict_mode_banned_ops() and returns: torch