def train_on_batch(self, x, y, class_weight=None,
                       sample_weight=None, **kwargs):
        if 'accuracy' in kwargs:
            kwargs.pop('accuracy')
            warnings.warn('The "accuracy" argument is deprecated, '
                          'instead you should pass the "accuracy" metric to '
                          'the model at compile time:\n'
                          '`model.compile(optimizer, loss, '
                          'metrics=["accuracy"])`')
        if kwargs:
            raise Exception('Received unknown keyword arguments: ' +
                            str(kwargs))
        return self.model.train_on_batch(x, y,
                                         sample_weight=sample_weight,
                                         class_weight=class_weight)
Single gradient update over one batch of samples.
dataset/ETHPy150Open fchollet/keras/keras/models.py/Sequential.train_on_batch