def sgrad_minibatch(self, data_x, data_y, prediction = False):
        if prediction:
            loss = self.f_loss(data_x, data_y)
            acc = np.mean(np.equal(np.argmax(self.f_y(data_x), axis=1), data_y))
        else:
            loss = 0.0
            acc = 1.0

        # compute gradient
        gradients = self.f_g_loss(data_x, data_y)

        return loss, acc, gradients
Find nothing without anything
dataset/ETHPy150Open UFAL-DSG/cloud-asr/cloudasr/worker/vad/tffnn.py/TheanoFFNN.sgrad_minibatch--crossover with--dataset/ETHPy150Open pypa/pip/tests/unit/test_finder.py/test_find_all_candidates_nothing