A generative adversarial network device and a training method thereof. The generative adversarial network device includes a generator and a discriminator. The generator is configured to generate a first sample according to an input data; the discriminator is coupled to the generator, and is configured to receive the first sample and be trained based on the first sample; the generator includes a first memristor array serving as a first weight array. The generative adversarial network device can omit a process of adding noise to fake samples generated by the generator, thereby saving training time, reducing resource consumption and improving training speed of the generative adversarial network.