Comments (4)
I would be happy to take a look at this!
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NVTabular's pytorch dataloader (which is built on Dask) may be agood reference here. I'll be happy to help advise on this work and clarify what NVTabular is (and isn't) doing.
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Thank you, @rjzamora !
from cucim.
Unfortunately, I have come across some issues with the cuCIM codebase that are blocking this Dask-based DataLoading solution.
For example, while the array transformation in the cuCIM transform image_rotate_90()
should be compatible with a Dask Array input, there is an explicit Type-Check here that throws a TypeError whenever trying to apply cuCIM transforms to a Dask Array.
In order to allow Dask to schedule cuCIM operations - we will likely want to make this "check" more of a duck-type check, that checks for the necessary API interface, as Dask Arrays should be able to pass those checks.
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Related Issues (20)
- [BUG] fix isolated test failure in `test_cache_hit_miss` HOT 2
- Using `rapids-cmake`
- Changing default CMake build mode to release (instead of debug)
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- Cleanup old build files
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- Slowness seen using PiecewiseAffineTransform compared to scikit-image version HOT 2
- Enable `libcufile` on `linux_aarch64` (w/CUDA 12.2+) HOT 1
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