code: def run_node(cls, node, input, device="CPU"):
      input_tensors = []
  
      if len(node.input) != len(input):
          raise ValueError(
              "Unexpected Input Size: Op_Type = {0}, Expected = {1}, Received = {2}".format(
                  node.op_type, len(node.input), len(input)
              )
          )
  
      for i in range(len(input)):
          input_tensors.append(
              helper.make_tensor_value_info(
                  node.input[i], TensorProto.FLOAT, input[i].shape
              )
          )
  
      onnx_graph = helper.make_graph(
          [node], "test_{}".format(node.op_type), input_tensors, []
      )
      onnx_model = helper.make_model(onnx_graph)
      return CNTKBackend.run_model(onnx_model, input, device)
  
file_path: CNTK/bindings/python/onnx_cntk/backend.py
imports: import cntk
  import numpy
  from onnx import helper, TensorProto
  from onnx.backend.base import Backend
  from onnx.backend.base import BackendRep
label_desc: Use image node_id 2 for calling the CNTKBackend obj's underlying member method code with example usage: obj.run_node(cls, node, input, device) and returns: CNTKBackend