def METHOD_NAME(self, output_shape, trans_a, trans_b, alpha=1):
    if not self.transform_data:
        if trans_a:
            x_data = np.around(
                np.random.randn(self.k, self.m).astype("float32"), 2)
        else:
            x_data = np.around(
                np.random.randn(self.m, self.k).astype("float32"), 2)
        if trans_b:
            y_data = np.around(
                np.random.randn(self.n, self.k).astype("float32"), 2)
        else:
            y_data = np.around(
                np.random.randn(self.k, self.n).astype("float32"), 2)
        x = runtime.cinn_buffer_t(x_data, runtime.cinn_x86_device)
        y = runtime.cinn_buffer_t(y_data, runtime.cinn_x86_device)
        out = runtime.cinn_buffer_t(
            np.zeros(output_shape).astype("float32"),
            runtime.cinn_x86_device)
        out1 = runtime.cinn_buffer_t(
            np.zeros(output_shape).astype("float32"),
            runtime.cinn_x86_device)
        self.transform_data = [
            x_data, y_data, x, y, out,
            runtime.cinn_pod_value_t(x),
            runtime.cinn_pod_value_t(y),
            runtime.cinn_pod_value_t(out),
            runtime.cinn_pod_value_t(out1)
        ]
    return self.transform_data