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CI: tidy test-matrix nightly; add arm64 gh200; bump torch to 2.12.1
- ci/test-matrix.yml: move per-row MODE/TORCH_VER/TORCH_CUDA into the ENV map (rides the existing matrix-env injection step). Add a nightly-standard arm64 gh200 row. Bump latest-PyTorch rows from 2.11.0 to 2.12.1; 2.9.1 rows untouched. - .github/workflows/ci-nightly.yml: matrix_filter selectors now key on .ENV.MODE. - .github/workflows/test-wheel-{linux,windows}.yml: job-name format strings read TORCH_VER/MODE from matrix.ENV; TORCH_CUDA also rendered in the name (e.g. ", 2.12.1+cu126"). Drop the now-redundant TORCH_VER/TORCH_CUDA lines from the pytorch step's env block.
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Lines changed: 34 additions & 35 deletions

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‎.github/workflows/ci-nightly.yml‎

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -98,7 +98,7 @@ jobs:
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run-id: ${{ needs.find-wheels.outputs.RUN_ID }}
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sha: ${{ needs.find-wheels.outputs.HEAD_SHA }}
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test-mode: nightly-pytorch
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matrix_filter: 'map(select(.MODE == "nightly-pytorch"))'
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matrix_filter: 'map(select(.ENV.MODE == "nightly-pytorch"))'
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test-pytorch-linux-aarch64:
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name: "Nightly PyTorch (linux-aarch64)"
@@ -116,7 +116,7 @@ jobs:
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run-id: ${{ needs.find-wheels.outputs.RUN_ID }}
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sha: ${{ needs.find-wheels.outputs.HEAD_SHA }}
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test-mode: nightly-pytorch
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matrix_filter: 'map(select(.MODE == "nightly-pytorch"))'
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matrix_filter: 'map(select(.ENV.MODE == "nightly-pytorch"))'
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test-pytorch-windows:
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name: "Nightly PyTorch (win-64)"
@@ -134,7 +134,7 @@ jobs:
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run-id: ${{ needs.find-wheels.outputs.RUN_ID }}
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sha: ${{ needs.find-wheels.outputs.HEAD_SHA }}
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test-mode: nightly-pytorch
137-
matrix_filter: 'map(select(.MODE == "nightly-pytorch"))'
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matrix_filter: 'map(select(.ENV.MODE == "nightly-pytorch"))'
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# ── numba-cuda tests ──
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@@ -154,7 +154,7 @@ jobs:
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run-id: ${{ needs.find-wheels.outputs.RUN_ID }}
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sha: ${{ needs.find-wheels.outputs.HEAD_SHA }}
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test-mode: nightly-numba-cuda
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matrix_filter: 'map(select(.MODE == "nightly-numba-cuda"))'
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matrix_filter: 'map(select(.ENV.MODE == "nightly-numba-cuda"))'
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test-numba-cuda-linux-aarch64:
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name: "Nightly numba-cuda (linux-aarch64)"
@@ -172,7 +172,7 @@ jobs:
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run-id: ${{ needs.find-wheels.outputs.RUN_ID }}
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sha: ${{ needs.find-wheels.outputs.HEAD_SHA }}
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test-mode: nightly-numba-cuda
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matrix_filter: 'map(select(.MODE == "nightly-numba-cuda"))'
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matrix_filter: 'map(select(.ENV.MODE == "nightly-numba-cuda"))'
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test-numba-cuda-windows:
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name: "Nightly numba-cuda (win-64)"
@@ -190,7 +190,7 @@ jobs:
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run-id: ${{ needs.find-wheels.outputs.RUN_ID }}
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sha: ${{ needs.find-wheels.outputs.HEAD_SHA }}
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test-mode: nightly-numba-cuda
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matrix_filter: 'map(select(.MODE == "nightly-numba-cuda"))'
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matrix_filter: 'map(select(.ENV.MODE == "nightly-numba-cuda"))'
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# ── Standard tests on nightly-only runners ──
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@@ -210,7 +210,7 @@ jobs:
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run-id: ${{ needs.find-wheels.outputs.RUN_ID }}
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sha: ${{ needs.find-wheels.outputs.HEAD_SHA }}
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test-mode: standard
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matrix_filter: 'map(select(.MODE == "nightly-standard"))'
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matrix_filter: 'map(select(.ENV.MODE == "nightly-standard"))'
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# ── Status check ──
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‎.github/workflows/test-wheel-linux.yml‎

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@@ -100,7 +100,7 @@ jobs:
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echo "OLD_BRANCH=${OLD_BRANCH}" >> "$GITHUB_OUTPUT"
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test:
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name: Python ${{ matrix.PY_VER }}, CUDA ${{ matrix.CUDA_VER }} (${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}), GPU ${{ matrix.GPU }}${{ matrix.GPU_COUNT != '1' && format(' (x{0})', matrix.GPU_COUNT) || '' }}${{ matrix.FLAVOR && format(', {0}', matrix.FLAVOR) || '' }}${{ matrix.TORCH_VER && format(', {0}', matrix.TORCH_VER) || '' }}${{ matrix.MODE == 'nightly-numba-cuda' && ', latest' || '' }}
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name: Python ${{ matrix.PY_VER }}, CUDA ${{ matrix.CUDA_VER }} (${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}), GPU ${{ matrix.GPU }}${{ matrix.GPU_COUNT != '1' && format(' (x{0})', matrix.GPU_COUNT) || '' }}${{ matrix.FLAVOR && format(', {0}', matrix.FLAVOR) || '' }}${{ matrix.ENV.TORCH_VER && format(', {0}+{1}', matrix.ENV.TORCH_VER, matrix.ENV.TORCH_CUDA) || '' }}${{ matrix.ENV.MODE == 'nightly-numba-cuda' && ', latest' || '' }}
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timeout-minutes: 60
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needs: compute-matrix
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strategy:
@@ -400,8 +400,6 @@ jobs:
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env:
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CUDA_VER: ${{ matrix.CUDA_VER }}
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LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
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TORCH_VER: ${{ matrix.TORCH_VER }}
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TORCH_CUDA: ${{ matrix.TORCH_CUDA }}
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run: run-tests nightly-pytorch
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- name: Install cuda-python wheels + numba-cuda

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

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@@ -90,7 +90,7 @@ jobs:
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echo "MATRIX=${MATRIX}" | tee --append "${GITHUB_OUTPUT}"
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test:
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name: Python ${{ matrix.PY_VER }}, CUDA ${{ matrix.CUDA_VER }} (${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}), GPU ${{ matrix.GPU }}${{ matrix.GPU_COUNT != '1' && format(' (x{0})', matrix.GPU_COUNT) || '' }} (${{ matrix.DRIVER_MODE }})${{ matrix.TORCH_VER && format(', {0}', matrix.TORCH_VER) || '' }}${{ matrix.MODE == 'nightly-numba-cuda' && ', latest' || '' }}
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name: Python ${{ matrix.PY_VER }}, CUDA ${{ matrix.CUDA_VER }} (${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}), GPU ${{ matrix.GPU }}${{ matrix.GPU_COUNT != '1' && format(' (x{0})', matrix.GPU_COUNT) || '' }} (${{ matrix.DRIVER_MODE }})${{ matrix.ENV.TORCH_VER && format(', {0}+{1}', matrix.ENV.TORCH_VER, matrix.ENV.TORCH_CUDA) || '' }}${{ matrix.ENV.MODE == 'nightly-numba-cuda' && ', latest' || '' }}
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timeout-minutes: 60
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# The build stage could fail but we want the CI to keep moving.
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needs: compute-matrix
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env:
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CUDA_VER: ${{ matrix.CUDA_VER }}
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LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
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TORCH_VER: ${{ matrix.TORCH_VER }}
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TORCH_CUDA: ${{ matrix.TORCH_CUDA }}
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shell: bash --noprofile --norc -xeuo pipefail {0}
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run: run-tests nightly-pytorch
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‎ci/test-matrix.yml‎

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# job. Every key/value pair is written to GITHUB_ENV after the standard
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# environment-variable setup step, so the variables are visible to all
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# subsequent steps (including the cuda.bindings and cuda.core test
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# steps). Example:
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# steps). Nightly rows also use ENV.MODE as a matrix-filter tag (see
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# ci-nightly.yml). Examples:
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# ENV: { CUDA_PYTHON_PER_THREAD_DEFAULT_STREAM: '1' }
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# ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu126' }
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linux:
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pull-request:
@@ -81,22 +83,23 @@ linux:
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'rtx4090', GPU_COUNT: '1', DRIVER: 'latest', FLAVOR: 'wsl' }
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nightly:
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# nightly-pytorch
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.11.0', TORCH_CUDA: 'cu126' }
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.11.0', TORCH_CUDA: 'cu130' }
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu126' }
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu130' }
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- { MODE: 'nightly-pytorch', ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.11.0', TORCH_CUDA: 'cu126' }
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- { MODE: 'nightly-pytorch', ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.11.0', TORCH_CUDA: 'cu130' }
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- { MODE: 'nightly-pytorch', ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu126' }
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- { MODE: 'nightly-pytorch', ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu130' }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu126' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu130' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu126' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu130' } }
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- { ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu126' } }
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- { ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu130' } }
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- { ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu126' } }
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- { ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu130' } }
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# nightly-numba-cuda
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- { MODE: 'nightly-numba-cuda', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest' }
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- { MODE: 'nightly-numba-cuda', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: '580.65.06' }
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- { MODE: 'nightly-numba-cuda', ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest' }
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- { MODE: 'nightly-numba-cuda', ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest' }
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# nightly-standard (arm64 l4×2 — nightly-only per runner team request)
98-
- { MODE: 'nightly-standard', ARCH: 'arm64', PY_VER: '3.14', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4', GPU_COUNT: '2', DRIVER: 'latest' }
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- { MODE: 'nightly-standard', ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4', GPU_COUNT: '2', DRIVER: 'latest' }
95+
- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-numba-cuda' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: '580.65.06', ENV: { MODE: 'nightly-numba-cuda' } }
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- { ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-numba-cuda' } }
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- { ARCH: 'arm64', PY_VER: '3.12', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-numba-cuda' } }
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# nightly-standard (arm64 nightly-only runners — per runner team request)
100+
- { ARCH: 'arm64', PY_VER: '3.14', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'gh200', GPU_COUNT: '1', DRIVER: 'latest', ENV: { MODE: 'nightly-standard' } }
101+
- { ARCH: 'arm64', PY_VER: '3.14', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4', GPU_COUNT: '2', DRIVER: 'latest', ENV: { MODE: 'nightly-standard' } }
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- { ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4', GPU_COUNT: '2', DRIVER: 'latest', ENV: { MODE: 'nightly-standard' } }
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windows:
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pull-request:
@@ -124,10 +127,10 @@ windows:
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- { ARCH: 'amd64', PY_VER: '3.14', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'h100', GPU_COUNT: '2', DRIVER: 'latest', DRIVER_MODE: 'MCDM' }
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nightly:
126129
# nightly-pytorch
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', TORCH_VER: '2.11.0', TORCH_CUDA: 'cu126' }
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', TORCH_VER: '2.11.0', TORCH_CUDA: 'cu130' }
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu126' }
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- { MODE: 'nightly-pytorch', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu130' }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu126' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu130' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu126' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1', TORCH_CUDA: 'cu130' } }
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# nightly-numba-cuda
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- { MODE: 'nightly-numba-cuda', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC' }
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- { MODE: 'nightly-numba-cuda', ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: '596.36', DRIVER_MODE: 'TCC' }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: 'latest', DRIVER_MODE: 'TCC', ENV: { MODE: 'nightly-numba-cuda' } }
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- { ARCH: 'amd64', PY_VER: '3.12', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4', GPU_COUNT: '1', DRIVER: '596.36', DRIVER_MODE: 'TCC', ENV: { MODE: 'nightly-numba-cuda' } }

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