'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)'

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.ascontiguousarray(v, dtype=np.float32)
        _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))
