class_docstr: This is the accelerated model for tensorflow and onnxruntime.
class_docstr_tok: ["This","is","the","accelerated","model","for","tensorflow","and","onnxruntime","."]
code: def status(self):
      status = super().status
      status.update(
          {
              "onnx_path": "onnx_saved_model.onnx",
              "attr_path": "onnx_saved_model_attr.pkl",
              "compile_path": "onnx_saved_model_compile.pkl",
              "intra_op_num_threads": self.session_options.intra_op_num_threads,
              "inter_op_num_threads": self.session_options.inter_op_num_threads,
          }
      )
      return status
  
imports: import os
  from bigdl.nano.utils.common import SafePickle
  from pathlib import Path
  from typing import Sequence, Any, Union, Dict
  from tempfile import TemporaryDirectory
  import tensorflow
  from bigdl.nano.utils.tf import convert_all
  from bigdl.nano.tf.model import KerasOptimizedModel
  from bigdl.nano.utils.common import invalidInputError
  from ..core.onnxruntime_model import ONNXRuntimeModel
  import onnxruntime
label_desc: Use image node_id 5 for calling the KerasONNXRuntimeModel obj's underlying member method code with example usage: obj.status() and returns: status