Added Stride to Subscript and Slice Kernel

[5had3z]

Category:

New Features

Description:

Added striding to subscript operator by implementing step in slice kernel and adding parameters.

Additional information:

Affected modules and functionalities:

Slice operator and kernels are the main changes as well as the test suite.

Key points relevant for the review:

Removed dimension flattening and pre-anchoring of slice kernel as this would futher complicate logic or result in more duplicated "specialised" kernels. I would conjecture that for a memory-bandwidth limited kenel such as rearranging/copying data, a little more interger logic should't have too much of an adverse effect.

Check if the test_constant_ranges has sufficient coverage of stride permutations, rather than focusing of the logic in subscript.h (maybe I should've looked at numpy's source code for their range conditions, but I seem to match it on final value).

All the "formatting" changes were done with clang-format and black.

Tests:

Added tests with different start : end : step in operator_2.test_subscript and checked for parity with numpy on both gpu and cpu mats. All operator_2 tests pass.

• Existing tests apply
• New tests added
  • Python tests
  • GTests
  • Benchmark
  • Other
• N/A

Checklist

Documentation

• Existing documentation applies
• Documentation updated
  • Docstring
  • Doxygen
  • RST
  • Jupyter
  • Other
• N/A

DALI team only

Requirements

• Implements new requirements
• Affects existing requirements
• N/A

REQ IDs: N/A

JIRA TASK: N/A

[5had3z]

If there are performance concerns with the simplification of the gpu kernel, could you please instruct me how to efficiently use nsight to analyse kernels in this project?

[mzient]

Hello @5had3z
Thank you for your contribution!
I have one request regarding this PR - please separate the concerns and create a standalone PR with the .devcontainer. This will streamline the review process.

[5had3z]

Done, reverted all changes not pertaining to striding/stepping, will open new one for devcontainer.

[jantonguirao]

Looks good to me. Thank you very much for your contribution!

[dali-automaton]

CI MESSAGE: [9465267]: BUILD STARTED

[dali-automaton]

CI MESSAGE: [9465267]: BUILD FAILED

[mzient]

The tests fail due to incorrectly initialized step.

[mzient]

@5had3z Failing tests aside, could you also rebase your branch on latest main?

[jantonguirao]

@5had3z to reproduce the test failures, you can run:

./dali/python/nvidia/dali/test/dali_kernel_test.bin --gtest_filter=*SliceGPU*

Thanks

[5had3z]

@mzient I realised that UnitCubeShape wasn't actually a thing after I tried to pull and build so I added TensorShape<>::filled_shape (and changed ::empty_shape to call it with value=0). I don't want to break the remote by syncrhonising my local, so I'm re-cloning, making the changes and pushing again. Will take a while to rebuild and test.

[mzient]

@mzient I realised that UnitCubeShape wasn't actually a thing after I tried to pull and build so I added TensorShape<>::filled_shape (and changed ::empty_shape to call it with value=0). I don't want to break the remote by syncrhonising my local, so I'm re-cloning, making the changes and pushing again. Will take a while to rebuild and test.

If you don't have new local changes, you can get the latest remote by doing:

# assuming that your fork's remote name is 5had3z
git fetch 5had3z
# assuming that your current branch is feat/strided-slice
git reset --hard 5had3z/feat/strided-slice

It's easier than re-cloning and won't trigger quite as lengthy rebuilds.

[5had3z]

@mzient I realised that UnitCubeShape wasn't actually a thing after I tried to pull and build so I added TensorShape<>::filled_shape (and changed ::empty_shape to call it with value=0). I don't want to break the remote by syncrhonising my local, so I'm re-cloning, making the changes and pushing again. Will take a while to rebuild and test.

If you don't have new local changes, you can get the latest remote by doing:

# assuming that your fork's remote name is 5had3z
git fetch 5had3z
# assuming that your current branch is feat/strided-slice
git reset --hard 5had3z/feat/strided-slice

It's easier than re-cloning and won't trigger quite as lengthy rebuilds.

Its alright, I'm trying to watch sopranos at the same time 😂. Build isn't too bad on 5950X if you restrict nvcc to sm86. Running tests now.

[5had3z]

if you restrict nvcc to sm86

Speaking of, upping cmake to >1.24 to take advantage of easily switching between cuda arch "all" and "native" could be useful.
https://cmake.org/cmake/help/latest/prop_tgt/CUDA_ARCHITECTURES.html

[mzient]

if you restrict nvcc to sm86

Speaking of, upping cmake to >1.24 to take advantage of easily switching between cuda arch "all" and "native" could be useful. https://cmake.org/cmake/help/latest/prop_tgt/CUDA_ARCHITECTURES.html

We already do have a CMake switch for it, e.g. -DCUDA_TARGET_ARCHS="75;80". AFAIK we populate a native CMake argument based on that list, with -real for all listed and -virtual for the oldest one.

[dali-automaton]

CI MESSAGE: [9467364]: BUILD FAILED

[mzient]

Please remove this comment. Firstly, TensorShape does have begin and end, as clearly indicated by the following ranged for. Secondly, at least in my opinion, assigning elements in a ranged for reads better than the very verbose call to std::fill (STL ranges change that but we're not there yet with the standard support).

[5had3z]

My bad, LSP complained it didn't exist and I wasn't thinking carefully (classic 1am moment).
I plan to play with trying to compile with cxx_std_23 later.

[mzient]

@5had3z Sorry, you've touched a very fundamental header (tensor_shape.h) so the changes need to be made very carefully. On the bright side, I've discovered some long-standing bugs and we have an opportunity to fix them now.

[dali-automaton]

CI MESSAGE: [9479881]: BUILD STARTED

[dali-automaton]

CI MESSAGE: [9479881]: BUILD FAILED

[dali-automaton]

CI MESSAGE: [9482171]: BUILD STARTED

[dali-automaton]

CI MESSAGE: [9482171]: BUILD PASSED

[dali-automaton]

CI MESSAGE: [9484228]: BUILD STARTED

[dali-automaton]

CI MESSAGE: [9484655]: BUILD STARTED

[dali-automaton]

CI MESSAGE: [9484655]: BUILD PASSED