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CI: pin numpy<2.5 (mlir) and pytest<9.1 (cuda-core released tests)
Two nightly failure fixups after the first green iteration: nightly-numba-cuda-mlir: numba-cuda-mlir 0.4.0 has an inverted guard that registers an overload of np.row_stack on NumPy 2.x, and NumPy 2.5 removed that name entirely, so test collection fails with "AttributeError: module 'numpy' has no attribute 'row_stack'". Cap numpy to <2.5. See NVIDIA/numba-cuda-mlir#154. nightly-cuda-core: released cuda-core v1.0.1's test suite uses a parametrize argvalues pattern that pytest 9.1 rejects ("in parametrize the number of names (1)... must be equal to the number of values (3)"). The main-side fix was #2212 but it has not shipped in a cuda-core release yet. Cap pytest to <9.1 for the released-cuda-core test run only.
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.github/workflows/test-wheel-linux.yml

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# that cuda-core version shipped with.
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pip install --upgrade "pip>=25.1"
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pip install --group "${CUDA_CORE_TEST_GROUP}"
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# Cap pytest below 9.1: released cuda-core <=1.0.1 has parametrize
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# patterns that pytest 9.1 rejects; the main-side fix (#2212) has
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# not yet shipped in a cuda-core release.
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pip install "pytest<9.1"
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pytest -rxXs -v --durations=0 --randomly-dont-reorganize tests/
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popd

.github/workflows/test-wheel-windows.yml

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pushd cuda-core-released/cuda_core
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pip install --upgrade "pip>=25.1"
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pip install --group "${CUDA_CORE_TEST_GROUP}"
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# Cap pytest below 9.1 — released cuda-core <=1.0.1 has parametrize
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# patterns that pytest 9.1 rejects (see #2212).
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pip install "pytest<9.1"
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pytest -rxXs -v --durations=0 --randomly-dont-reorganize tests/
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popd

ci/tools/run-tests

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@@ -163,7 +163,9 @@ elif [[ "${test_module}" == "core" || "${test_module}" == nightly-* ]]; then
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)
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elif [[ "${test_module}" == "nightly-numba-cuda-mlir" ]]; then
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echo "Installing pathfinder + bindings + core + numba-cuda-mlir"
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PIP_ARGS+=("numba-cuda-mlir[cu${TEST_CUDA_MAJOR}]")
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# numpy<2.5: numba-cuda-mlir 0.4.0 registers np.row_stack, which was
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# removed in NumPy 2.5. See NVIDIA/numba-cuda-mlir#154.
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PIP_ARGS+=("numba-cuda-mlir[cu${TEST_CUDA_MAJOR}]" "numpy<2.5")
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fi
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pip install "${PIP_ARGS[@]}"

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