def evaluate(self, x, y, batch_size=32, verbose=1, sample_weight=None):
        # validate user data
        x, y, sample_weights = self._standardize_user_data(x, y,
                                                           sample_weight=sample_weight,
                                                           check_batch_dim=False,
                                                           batch_size=batch_size)
        # prepare inputs, delegate logic to _test_loop
        if self.uses_learning_phase:
            ins = x + y + sample_weights + [0.]
        else:
            ins = x + y + sample_weights
        self._make_test_function()
        f = self.test_function
        return self._test_loop(f, ins,
                               batch_size=batch_size,
                               verbose=verbose)
Returns the loss value and metrics values for the model
dataset/ETHPy150Open fchollet/keras/keras/engine/training.py/Model.evaluate