def METHOD_NAME(self, filename, inputs, labels):
    dill.load_session(filename)
    self.batch_size = len(inputs)
    self.forward_pass(inputs)
    a = self.layers[self.num_layers - 1].activations
    num_classes = 10
    targets = np.array([a]).reshape(-1)
    a = np.asarray(a)
    one_hot_labels = np.eye(num_classes)[a.astype(int)]
    total = 0
    correct = 0
    for i in range(len(a)):
        total += 1
        if np.equal(one_hot_labels[i], labels[i]).all():
            correct += 1
    print("Accuracy: ", correct * 100 / total)