Interesting. Thanks for your reply. Doesn’t this mean that the worker will always perform the same sequence of random transforms, each time on different data?
To be clear with what I mean:

the sampler won’t use the same seed

means that the sample distribution across workers is randomised.
But at the same time:

the worker seed would be the same

means that any random transformations performed by the worker will be the same.
I guess this is not problematic, since workers will rarely be used with a very low number of samples to augment, but it is unexpected.