code: def forward(self, **kwargs):
          
          for k, v in kwargs.items():
              if not isinstance(v, np.ndarray):
                  raise ValueError("Expect numpy ndarray as input")
              v = np.asarray(v, dtype=np.float32, order='C')
              _check_call(_LIB.MXPredSetInput(
                  self.handle, c_str(k),
                  v.ctypes.data_as(mx_float_p),
                  mx_uint(v.size)))
          _check_call(_LIB.MXPredForward(self.handle))
docs: Perform forward to get the output.
  
          Parameters
          ----------
          **kwargs
              Keyword arguments of input variable name to data.
  
          Examples
          --------
          >>> predictor.forward(data=mydata)
          >>> out = predictor.get_output(0)