Hi,
I am reading into torchserve and from my understanding it provides a system for clients to send inference requests to a trained model.
Is it possible to use a model which needs to perform gradient ascent to predict values with torchserve, using a partially trained model?
If not, what alternatives could one use?
Thanks
Could you elaborate what you mean by gradient ascent on a partially trained model? If your intent is to perform an inference on a pretrained model then that should work as is with torchserve,
If your intent is to retrain a model based on the result of some inference then you can deploy pretrained model, get inference, replace via a new model - see https://github.com/pytorch/serve/blob/master/docs/management_api.md for more information