code: def backward_walk_ops(start_ops, tensor_blacklist, op_type_blacklist):
      found_ops = []
      op_stack = [op for op in start_ops]
      while len(op_stack) > 0:
          op = op_stack.pop()
          if op.type not in op_type_blacklist and op not in found_ops:
              found_ops.append(op)
              for input in op.inputs:
                  if input not in tensor_blacklist:
                      op_stack.append(input.op)
      return found_ops
  
imports: import warnings
  import numpy
  from packaging import version
  from ...utils._exceptions import DimensionError
  from .._explainer import Explainer
  from ..tf_utils import _get_graph, _get_model_inputs, _get_model_output, _get_session
  from .deep_utils import _check_additivity
label_desc: Use image node_id 3 for calling a global function with example usage: backward_walk_ops(start_ops, tensor_blacklist, op_type_blacklist) and returns: found_ops