def evaluate_generator(self, generator, val_samples, max_q_size=10, **kwargs):
        if self.model is None:
            raise Exception('The model needs to be compiled before being used.')
        if 'show_accuracy' in kwargs:
            kwargs.pop('show_accuracy')
            warnings.warn('The "show_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 'verbose' in kwargs:
            kwargs.pop('verbose')
            warnings.warn('The "verbose" argument is deprecated.')
        if kwargs:
            raise Exception('Received unknown keyword arguments: ' +
                            str(kwargs))
        return self.model.evaluate_generator(generator,
                                             val_samples,
                                             max_q_size=max_q_size)
Evaluates the model on a data generator. The generator should
dataset/ETHPy150Open fchollet/keras/keras/models.py/Sequential.evaluate_generator