'Saving and loading tensorflow model as .npy vs. Checkpoints

I am working with this this github repo. They ask us to download and save a pre_trained vgg16 model in nets folder. For this I saved the checkpoints of a pretrained vgg16. Then in the code I noticed they are loading the model this way:

if vgg16_npy_path is None:
            vgg16_npy_path = './nets/vgg16.npy'
self.data_dict = np.load(vgg16_npy_path, encoding='latin1').item()

I read a bit about how to save weights of a tensorflow model as .npy but it seemed overly complicated. Is it possible to just save the checkpoints and load it instead of the numpy format. Does it affect anything later?

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'Saving and loading tensorflow model as .npy vs. Checkpoints

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