5619b6770675a7fedd85cbc5ab19773a3ba94e13,autokeras/supervised.py,SingleModelSupervised,predict,#SingleModelSupervised#Any#,336

Before Change

        model = self.graph.produce_model()
        model.eval()

        outputs = []
        with torch.no_grad():
            for index, inputs in enumerate(test_loader):
                outputs.append(model(inputs).numpy())
        output = reduce(lambda x, y: np.concatenate((x, y)), outputs)
        return self.inverse_transform_y(output)

    def evaluate(self, x_test, y_test):
        Return the accuracy score between predict value and `y_test`.

After Change

        model = self.graph.produce_model()
        model.eval()

        output = Backend.predict(model, test_loader)
        return self.inverse_transform_y(output)

    def evaluate(self, x_test, y_test):
        Return the accuracy score between predict value and `y_test`.

Instances