pyspark/bigdl/nn/layer.py
def forward(self, input):
        """
        NB: It's for debug only, please use optimizer.optimize() in production.
        Takes an input object, and computes the corresponding output of the module

        :param input: ndarray or list of ndarray
        :param input: ndarray or list of ndarray or JTensor or list of JTensor.
        :return: ndarray or list of ndarray
        """
        jinput, input_is_table = self.check_input(input)
        output = callBigDlFunc(self.bigdl_type,
                               "modelForward",
                               self.value,
                               jinput,
                               input_is_table)
        return self.convert_output(output)
def forward(self, input):
        """
        NB: It's for debug only, please use optimizer.optimize() in production.
        Takes an input object, and computes the corresponding output of the module

        :param input: ndarray or list of ndarray
        :param input: ndarray or list of ndarray or JTensor or list of JTensor.
        :return: ndarray or list of ndarray
        """
        jinput, input_is_table = self.check_input(input)
        output = callBigDlFunc(self.bigdl_type,
                               "modelForward",
                               self.value,
                               jinput,
                               input_is_table)
        return self.convert_output(output)
NB: It's for debug only, please use optimizer.optimize() in production.
        Takes an input object, and computes the corresponding output of the module

        :param input: ndarray or list of ndarray
        :param input: ndarray or list of ndarray or JTensor or list of JTensor.
        :return: ndarray or list of ndarray