Function sample

examples/GAN/ConditionalGAN-mnist.py:115–129

(model_path)

def sample(model_path):
    pred = PredictConfig(
        session_init=SmartInit(model_path),
        model=Model(),
        input_names=['label', 'z'],
        output_names=['gen/gen'])

    ds = MapData(RandomZData((100, 100)),
                 lambda dp: [np.arange(100) % 10, dp[0]])
    pred = SimpleDatasetPredictor(pred, ds)
    for o in pred.get_result():
        o = o[0] * 255.0
        viz = stack_patches(o, nr_row=10, nr_col=10)
        viz = cv2.resize(viz, (800, 800))
        interactive_imshow(viz)


if __name__ == '__main__':