How relation parameters is updated about pytorch-biggraph HOT 2 CLOSED

Roughly speaking, the code you copied is just "registering" each model parameter with the parameter server. The model parameters are the ones that don't depend on the entity types or on the bucket that is currently being trained on. So these parameters are always "present", from the beginning to the end (as opposed to the entity embeddings, which are loaded and unloaded as needed).

When a parameter is "registered" with the parameter server, a "pointer" to it is recorded (the "memory address" to its data, if you prefer). Then, there is a client-side thread (which is started by the parameter_sharer upon creation) which at regular intervals loops over all the registered parameters and sends their new values to the parameter server. (In fact, this loop lives in a separate subprocess, in order to get around Python's GIL's limitations; all the parameters live in shared memory so this isn't a problem).

I hope this clarifies the inner workings of the parameter server.

from pytorch-biggraph.

Closing due to inactivity. Please reopen if you still have questions.

from pytorch-biggraph.