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

        :param input: ndarray or list of ndarray
        :param target: ndarray or list of ndarray
        :return: value of loss
        """
        jinput, input_is_table = Layer.check_input(input)
        jtarget, target_is_table = Layer.check_input(target)
        output = callBigDlFunc(self.bigdl_type,
                               "criterionForward",
                               self.value,
                               jinput,
                               input_is_table,
                               jtarget,
                               target_is_table)
        return output
def forward(self, input, target):
        """
        NB: It's for debug only, please use optimizer.optimize() in production.
        Takes an input object, and computes the corresponding loss of the criterion,
        compared with `target`

        :param input: ndarray or list of ndarray
        :param target: ndarray or list of ndarray
        :return: value of loss
        """
        jinput, input_is_table = Layer.check_input(input)
        jtarget, target_is_table = Layer.check_input(target)
        output = callBigDlFunc(self.bigdl_type,
                               "criterionForward",
                               self.value,
                               jinput,
                               input_is_table,
                               jtarget,
                               target_is_table)
        return output
NB: It's for debug only, please use optimizer.optimize() in production.
        Takes an input object, and computes the corresponding loss of the criterion,
        compared with `target`

        :param input: ndarray or list of ndarray
        :param target: ndarray or list of ndarray
        :return: value of loss