docstr: Returns the input container wrapping the original input model.
docstr_tok: ["Returns","the","input","container","wrapping","the","original","input","model","."]
code: def input_container(self):
      """
      Returns the input container wrapping the original input model.
      """
      return self.onnxconverter_topology.raw_model
  
imports: import numpy
  import os
  from packaging.version import Version, parse
  import torch
  from uuid import uuid4
  from onnxconverter_common.registration import get_converter
  from onnxconverter_common.topology import Topology
  import onnx
  from hummingbird.ml.containers import PyTorchSklearnContainerRegression, PyTorchSklearnContainerClassification, PyTorchSklearnContainerTransformer, PyTorchSklearnContainerAnomalyDetection, TorchScriptSklearnContainerRegression, TorchScriptSklearnContainerClassification, TorchScriptSklearnContainerTransformer, TorchScriptSklearnContainerAnomalyDetection, ONNXSklearnContainerRegression, ONNXSklearnContainerClassification, ONNXSklearnContainerTransformer, ONNXSklearnContainerAnomalyDetection, TVMSklearnContainerRegression, TVMSklearnContainerClassification, TVMSklearnContainerTransformer, TVMSklearnContainerAnomalyDetection, BatchContainer
  from hummingbird.ml._utils import pandas_installed, tvm_installed, get_device, from_strings_to_ints
  from hummingbird.ml._executor import Executor
  from hummingbird.ml.exceptions import MissingConverter
  from hummingbird.ml.operator_converters import constants
label_desc: Use image node_id 2 for calling the Topology obj's underlying member method code with example usage: obj.input_container() and returns: self