Hi,
These benchmark are a very good example for what is the overhead of our framework. All these operations require no compute at all. So here you just measure how long it takes to go all the way down the stack and back up.
Unfortunately, because we support more hardware, layouts, and feature such as autograd, it is very hard to be as lean as numpy.
Hopefully for large enough operations, this overhead should be small enough to not be a problem in practical neural network operations.