ci(mlx): instrument exec_gather_mm/qmm for kernel-input dump #10
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| name: MLX PR check (fork) | |
| # Fait tourner les tests MLX pertinents pour la PR #20685 sur un runner | |
| # macOS Apple Silicon GRATUIT (macos-14 = M1, arm64, illimité sur dépôt public). | |
| # | |
| # Pourquoi ce fichier et pas .github/workflows/mlx.yml : le workflow officiel | |
| # demande `runner: macos-14-xlarge`, un "larger runner" réservé à l'org pytorch. | |
| # Sur un fork perso, ce label ne résout pas et le job reste en attente | |
| # indéfiniment. Ici on cible `macos-14`, le runner standard gratuit. | |
| # | |
| # INSTALLATION : | |
| # 1. Sur ton fork, onglet Actions -> activer les workflows (désactivés par | |
| # défaut sur les forks). | |
| # 2. Vérifier que le fork est PUBLIC (le gratuit illimité ne vaut que pour | |
| # les dépôts publics). | |
| # 3. Placer ce fichier en .github/workflows/mlx-fork-check.yml sur la branche | |
| # ci-mlx-check (jamais sur la branche PR), commit + push. | |
| # 4. Actions -> "MLX PR check (fork)" -> Run workflow. | |
| # | |
| # NE PAS inclure ce fichier dans la PR upstream : il est là pour ta validation | |
| # locale uniquement. Le supprimer avant le push final vers pytorch/executorch. | |
| on: | |
| workflow_dispatch: | |
| push: | |
| branches: | |
| - ci-mlx-check | |
| paths-ignore: | |
| - mlx_gather_mm_repro.py | |
| - .github/workflows/mlx-only-repro.yml | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.ref }} | |
| # false: a repro-only push must not cancel an in-flight ExecuTorch build | |
| cancel-in-progress: false | |
| permissions: | |
| contents: read | |
| jobs: | |
| test-mlx-moe: | |
| # Runner GitHub-hosted standard : M1, 3 vCPU, 7 Go RAM, 14 Go disque. | |
| # Gratuit et illimité sur les dépôts publics. | |
| runs-on: macos-14 | |
| timeout-minutes: 300 | |
| steps: | |
| - name: Checkout | |
| uses: actions/checkout@v4 | |
| with: | |
| submodules: recursive | |
| - name: Setup Python 3.12 | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: "3.12" | |
| - name: Diagnostics machine (avant build) | |
| run: | | |
| set -eux | |
| uname -m # doit afficher arm64 | |
| sysctl -n machdep.cpu.brand_string | |
| sysctl -n hw.ncpu | |
| df -h / | |
| xcodebuild -version || true | |
| - name: Install ExecuTorch | |
| run: | | |
| set -eux | |
| python -m pip install --upgrade pip | |
| python install_executorch.py | |
| - name: Configure (preset mlx-release) | |
| run: | | |
| set -eux | |
| cmake --preset mlx-release \ | |
| -DEXECUTORCH_BUILD_TESTS=ON \ | |
| -DEXECUTORCH_MLX_ENABLE_SANITIZERS=OFF | |
| - name: Build op_test_runner | |
| id: build | |
| run: | | |
| set -eux | |
| # -j2 volontairement bas : 7 Go de RAM seulement, l'édition de liens | |
| # d'ExecuTorch est gourmande. Monter à $(sysctl -n hw.ncpu) si OK. | |
| cmake --build cmake-out --target op_test_runner -j2 | |
| df -h / | |
| # Isolates mx.gather_mm(sorted_indices=True) from ExecuTorch. If this | |
| # diverges, the bug is upstream MLX — not the PR. | |
| # continue-on-error: never block the Vid-vs-literal A/B behind this. | |
| - name: Repro MLX pur — gather_mm sorted_indices | |
| if: always() | |
| continue-on-error: true | |
| run: | | |
| set -eux | |
| # C++ links the mlx submodule; the Python import may still need PyPI. | |
| pip install -q mlx numpy | |
| python -c "import mlx.core as mx; print('mlx', mx.__version__)" | |
| python mlx_gather_mm_repro.py | |
| # Instrumentation dump: shapes/strides/indices + Y(sorted) vs Y(false). | |
| # ET_MLX_DUMP_GATHER=1 enables stderr dumps in exec_gather_mm/qmm. | |
| - name: Dump gather_mm / gather_qmm (instrumented) | |
| if: steps.build.outcome == 'success' | |
| continue-on-error: true | |
| env: | |
| ET_MLX_DUMP_GATHER: "1" | |
| run: | | |
| set -eux | |
| python -m executorch.backends.mlx.test.run_all_tests \ | |
| gather_mm_e4_i64_o128 \ | |
| gather_mm_e4_i64_o128_sorted \ | |
| gather_mm_e4_i64_o128_sorted_literal \ | |
| gather_qmm_e4_i64_o128_g32_sorted \ | |
| -v --clean-after | |
| # A/B: Vid path (ItemIntNode) vs literal flag — isolates resolve_int chain. | |
| - name: Op tests — gather_mm sorted Vid vs literal | |
| if: steps.build.outcome == 'success' | |
| continue-on-error: true | |
| run: | | |
| set -eux | |
| python -m executorch.backends.mlx.test.run_all_tests \ | |
| gather_mm_e4_i64_o128_sorted \ | |
| gather_mm_e4_i64_o128_sorted_literal \ | |
| -v --clean-after | |
| # Le cœur de la validation : uniquement les ops touchées par la PR. | |
| # run_all_tests.py accepte des noms de tests en positionnel, ce qui évite | |
| # de faire tourner la suite complète (trop lourde pour le runner gratuit). | |
| # continue-on-error: recover MoE + pytest results even if gather is red. | |
| - name: Op tests — gather_mm / gather_qmm (chemin sorted_indices Optional) | |
| if: steps.build.outcome == 'success' | |
| continue-on-error: true | |
| run: | | |
| set -eux | |
| python -m executorch.backends.mlx.test.run_all_tests \ | |
| gather_mm gather_qmm -v --clean-after | |
| - name: Op tests — moe_gather_inputs / moe_scatter_outputs (feature #20554) | |
| if: steps.build.outcome == 'success' | |
| continue-on-error: true | |
| run: | | |
| set -eux | |
| python -m executorch.backends.mlx.test.run_all_tests \ | |
| moe_gather_inputs moe_scatter_outputs -v --clean-after | |
| # Utile pour recalibrer expected_node_counts si un assert échoue : | |
| # la sortie -v liste les nœuds réellement émis. | |
| - name: Liste des configs de test disponibles (debug) | |
| if: always() | |
| run: | | |
| python -m executorch.backends.mlx.test.run_all_tests --list || true | |
| - name: Tests Python du backend (non-runtime) | |
| if: steps.build.outcome == 'success' | |
| continue-on-error: true | |
| run: | | |
| set -eux | |
| python -m pytest \ | |
| backends/mlx/test/test_passes.py \ | |
| backends/mlx/test/test_partitioner.py \ | |
| backends/mlx/test/test_serialization_dedup.py \ | |
| -v | |
| - name: Diagnostics machine (après) | |
| if: always() | |
| run: df -h / |