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[TKW] CI: Install GPU deps in separate step #377

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[TKW] CI: Install GPU deps in separate step #377

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8 changes: 5 additions & 3 deletions .github/workflows/ci-tk.yaml
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Expand Up @@ -63,24 +63,26 @@ jobs:
run: |
pytest -n 4 --capture=tee-sys -vv ./tests/kernel/wave/

- name: Test TKW runtime related stack on amdgpu
- name: Install GPU deps
if: "contains(matrix.os, 'amdgpu') && !cancelled()"
run: |
pip install --no-compile -r pytorch-rocm-requirements.txt
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We should probably be working within a venv, especially on persistent self-hosted runners 🤔

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I thought we already do, but yeah, I can look into it

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Sample PR: nod-ai/shark-ai#640

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BTW, as an potential alternative I was using setup-miniconda action in the past https://github.com/numba/numba-mlir/blob/main/.github/workflows/build.yml#L52 and was quite happy with it


- name: Test TKW runtime related stack on amdgpu
if: "contains(matrix.os, 'amdgpu') && !cancelled()"
run: |
export export WAVE_CACHE_DIR=$PWD/.wave
rm -rf ./.wave
WAVE_CACHE_ON=1 pytest --capture=tee-sys -vv --run-e2e ./tests/kernel/wave/runtime

- name: Run e2e tests on AMD GPU MI300
if: "contains(matrix.os, 'mi300') && !cancelled()"
run: |
pip install --no-compile -r pytorch-rocm-requirements.txt
WAVE_CACHE_ON=0 pytest -n 8 --capture=tee-sys -vv --run-e2e --gpu-distribute 8 ./tests/kernel/wave/

- name: Run e2e tests on AMD GPU MI250
if: "contains(matrix.os, 'mi250') && !cancelled()"
run: |
pip install --no-compile -r pytorch-rocm-requirements.txt
WAVE_CACHE_ON=0 pytest -n 2 --capture=tee-sys --run-e2e -vv ./tests/kernel/wave/

- name: Run LIT tests
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