Sparse TSNE #3293
Sparse TSNE #3293
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divyegala
added
2 - In Progress
Codecov Report
@@ Coverage Diff @@
## branch-0.18 #3293 +/- ##
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+ Coverage 71.48% 71.55% +0.06%
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Files 207 207
Lines 16750 16787 +37
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+ Hits 11974 12012 +38
+ Misses 4776 4775 -1
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rerun tests |
divyegala
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3 - Ready for Review
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Really glad to see this change coming in!
Most of the feedback is minor, however adding this feature required that I also parametrize the remaining functions in UMAP so that updating from int64_t and float is straightforward. We should use a parametrized type instead of value_t where possible.
divyegala
added
4 - Waiting on Reviewer
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@cjnolet leaving this comment as a reference for post-vacation. I updated this PR with your latest review feedback |
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rerun tests |
| @@ -208,14 +208,16 @@ def extract_knn_graph(knn_graph, convert_dtype=True): | |||
| knn_indices = knn_graph.col | |||
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| if knn_indices is not None: | |||
| convert_to_dtype = None | |||
| if convert_dtype: | |||
| convert_to_dtype = np.int32 if sparse else np.int64 | |||
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It's going to be important to change this when FAISS is updated (and the indices are 32-bit). Referencing relevant issue: #2821
cjnolet
added
6 - Okay to Auto-Merge
and removed
4 - Waiting on Reviewer
This PR allows TSNE to accept sparse inputs.
It also removes long-standing warnings
ptxas warning : Value of threads per SM for entry _ZN2ML4TSNE17IntegrationKernelEfffPfS1_PKfS3_S3_S3_S1_S1_S1_S1_S3_i is out of range. .minnctapersm will be ignored ptxas warning : Value of threads per SM for entry _ZN2ML4TSNE15RepulsionKernelEffPKiS2_PKfS4_S4_PfS5_S5_fiiiS4_S2_ is out of range. .minnctapersm will be ignored ptxas warning : Value of threads per SM for entry _ZN2ML4TSNE18TreeBuildingKernelEPiPKfS3_iiS1_S1_S3_ is out of range. .minnctapersm will be ignored ptxas warning : Value of threads per SM for entry _ZN2ML4TSNE17BoundingBoxKernelEPiS1_PfS2_S2_S2_S2_S2_S2_iiiPjS2_ is out of range. .minnctapersm will be ignoredfrom cuml builds which were caused by invalid parameters to__launch_bounds__in TSNE kernels.Furthermore, I also created a class
TSNE_runnerto handle running separate components of the algorithm as well as to ensure the proper use of RAII buffers and their de-allocation once their use is done, without explicitly deleting those buffers.closes #2751