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Unblock CI for branch-23.10 #5561

Merged
merged 18 commits into from
Sep 13, 2023
Merged

Unblock CI for branch-23.10 #5561

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b417bfd
Pin container image for clang-tidy CI check to CUDA 11.8.
csadorf Aug 25, 2023
804cfa7
Update .github/workflows/pr.yaml
csadorf Aug 25, 2023
e73f07d
Increase the numerical tolerance for test_pairwise_distances tests.
csadorf Aug 25, 2023
20a147d
increase tolerance further
csadorf Aug 28, 2023
721aed0
Decrease compare precision to 2 decimal points.
csadorf Aug 30, 2023
f70f198
Reduce precision only for nan_euclidean metric.
csadorf Aug 30, 2023
1112522
Reduce general precision to 4 decimals.
csadorf Aug 31, 2023
c6b5bca
pick new RAFT targets
divyegala Sep 1, 2023
6efac97
fix typo
divyegala Sep 1, 2023
2b52f32
fix target name
divyegala Sep 1, 2023
2d2a649
no such thing as raft::raft_static
divyegala Sep 1, 2023
22476cd
bump
divyegala Sep 2, 2023
ce368d1
Propagate RAFT_COMPILED_LIB to correct scope
robertmaynard Sep 5, 2023
9658aa5
remove unnecessary variable setting
divyegala Sep 5, 2023
eaaba1a
Merge remote-tracking branch 'upstream/pull-request/5572' into ci-pin…
csadorf Sep 8, 2023
b46e087
Use conda mambabuild not mamba mambabuild.
bdice Sep 8, 2023
b4c34ef
Merge remote-tracking branch 'upstream/pull-request/5575' into ci-pin…
csadorf Sep 8, 2023
ed1040d
Fix _extract_partitions function.
csadorf Sep 12, 2023
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2 changes: 1 addition & 1 deletion .github/workflows/pr.yaml
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Expand Up @@ -38,7 +38,7 @@ jobs:
build_type: pull-request
node_type: "cpu8"
arch: "amd64"
container_image: "rapidsai/ci:latest"
container_image: "rapidsai/ci:cuda11.8.0-ubuntu22.04-py3.10"
run_script: "ci/run_clang_tidy.sh"
conda-cpp-build:
needs: checks
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3 changes: 1 addition & 2 deletions python/cuml/tests/test_metrics.py
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Expand Up @@ -1030,8 +1030,7 @@ def test_pairwise_distances(metric: str, matrix_size, is_col_major):
# Test the pairwise_distance helper function.
rng = np.random.RandomState(0)

# For fp64, compare at 13 decimals, (2 places less than the ~15 max)
compare_precision = 6
compare_precision = 3

# Compare to sklearn, single input
X = prep_dense_array(
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