Training all-optical neural networks in itself remains an unresolved problem, and the challenges compound when the problem is turned into the hardware implementations. In this paper, we propose a nonlinear activation function based on optical bistability within a micro-ring resonator (MRR), achieving threshold control without external modulation. Furthermore, a convolutional neural network similar to the Le-Net-5 architecture is designed, in which all nonlinear activation functions are composed of optical bistable hysteresis loop. The numerical simulation results demonstrate that the recognition rate on the Fashion-MNIST dataset can achieve 91.3%, which means that the optical neuromorphic computation can be implemented by utilizing the nonlinear optical effects themselves in the all-optical hardware. Such a scheme promises access to the all-optical neural network training in the optical hardware environment compared to numerical activation functions. © 2024 Elsevier B.V.