Tensorflow, google cloud ML: how to use previous checkpoint to train new images?

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I am working with image classification and Tensorflow on Google Cloud Machine Learning. Everytime I train a new project, It works perfectly, but everytime I have an update on my dataset (upload new images to database) I have to retrain everything. Is there a way to retrain from the last checkpoint, how should I do that in the cloud?

Thanks everyone!

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Tensorflow will continue training from the previous checkpoint. Make sure to specify a cloud storage location as the output directory​ when you create the model.