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Clamp max_iter in OOC KMeans test #2256

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Clamp max_iter in OOC KMeans test #2256

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tarang-jain Jun 22, 2026
a84501d
limit iterations
tarang-jain Jun 23, 2026
c3372d0
Merge branch 'main' into tolerance
tarang-jain Jun 23, 2026
1a42257
revert debug statements
tarang-jain Jun 23, 2026
0f495f4
Merge branch 'tolerance' of https://github.com/tarang-jain/cuvs into …
tarang-jain Jun 23, 2026
0d47620
fix param reset
tarang-jain Jun 23, 2026
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6 changes: 4 additions & 2 deletions cpp/tests/cluster/kmeans.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -381,6 +381,9 @@ class KmeansFitBatchedTest : public ::testing::TestWithParam<KmeansBatchedInputs
params.tol = testparams.tol;
params.rng_state.seed = 1;
params.oversampling_factor = 0;
// Limit the number of iterations to ensure same number of iterations for reference and batched
// code paths.
params.max_iter = 3;
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@cjnolet cjnolet Jun 23, 2026

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This fix doesn't seem particularly robust, and appears to me like it'll reduce the coverage for the tests, right? Default max_iters for k-means is much higher. How do we test in a way where we can validate its ability to stop early without having to reduce the max-iters to the point where we are essentially not testing the early stopping at all?

@tarang-jain tarang-jain Jun 23, 2026

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I think the point of the test when we are bit matching centroids is to ensure that the accumulation of partial sums in the OOC setting in a single iteration matches the in-memory setting. The test fails when there is an edge case -- the variation due to floating point precision in the arithmetic is just enough to push the difference in centroids between consecutive iterations to fall below the convergence criteria -- in-memory converges one iteration sooner in than OOC.


auto stream = raft::resource::get_cuda_stream(handle);

Expand All @@ -402,8 +405,7 @@ class KmeansFitBatchedTest : public ::testing::TestWithParam<KmeansBatchedInputs

auto d_sw = d_sw_view();

params.init = cuvs::cluster::kmeans::params::Array;
params.max_iter = 20;
params.init = cuvs::cluster::kmeans::params::Array;

T ref_inertia = 0;
int ref_n_iter = 0;
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