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Fix constant_fold cleanup for shared get_attr targets #12871

Fix constant_fold cleanup for shared get_attr targets

Fix constant_fold cleanup for shared get_attr targets #12871

Workflow file for this run

name: Run 1xH100 Tests
on:
push:
branches:
- main
- 'gh/**'
pull_request:
branches:
- main
- 'gh/**'
concurrency:
group: 1xH100_tests-${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_number || github.ref }}
cancel-in-progress: true
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
jobs:
test:
strategy:
fail-fast: false
matrix:
include:
- name: H100
runs-on: mt-l-x86iamx-22-225-h100
torch-spec: '--pre torch torchvision torchaudio mslk --index-url https://download.pytorch.org/whl/nightly/cu130'
gpu-arch-type: "cuda"
gpu-arch-version: "13.0"
permissions:
id-token: write
contents: read
uses: pytorch/test-infra/.github/workflows/linux_job_v3.yml@main
with:
timeout: 90
runner: ${{ matrix.runs-on }}
gpu-arch-type: ${{ matrix.gpu-arch-type }}
gpu-arch-version: ${{ matrix.gpu-arch-version }}
submodules: recursive
script: |
conda create -n venv python=3.10 -y
conda activate venv
export PATH=/opt/rh/devtoolset-10/root/usr/bin/:$PATH
python -m pip install --upgrade pip
pip install uv
# Pre-install torch/vision's pure-python deps from the in-cluster pypi-cache for speed.
#
# spmd-types is appended on purpose: the torch nightly hard-depends on it, but the pytorch
# index only re-links to files.pythonhosted.org, which the OSDC H100 pool can't reach.
# Installing it now via the reachable cache means the cache-bypassing torch install below
# (--index-url only) never has to fetch it.
#
# Also affects release_model/run_microbenchmarks/dashboard_perf_test; only the H100 test
# workflows are patched for now since they are the ones failing.
#
# TODO: remove once the OSDC pool can reach files.pythonhosted.org (or spmd-types is
# mirrored on download.pytorch.org). Egress owned by PyTorch dev infra.
pip install filelock typing-extensions "setuptools<82" sympy networkx jinja2 fsspec numpy pillow spmd-types
# Clear PIP_EXTRA_INDEX_URL (the runner's default cpu /whl/cpu/) so it can't supply a
# +cpu torch; the torch-spec's --index-url makes the literal nightly cu130 index the only source.
PIP_EXTRA_INDEX_URL= pip install ${{ matrix.torch-spec }}
pip install -U --pre flashinfer-python --index-url https://flashinfer.ai/whl/nightly/ --no-deps
pip install apache-tvm-ffi
pip install nvidia-ml-py
uv pip install -r dev-requirements.txt
pip install . --no-build-isolation -vv
pytest test/integration --verbose -s
pytest test/dtypes/test_affine_quantized_float.py --verbose -s
pytest test/quantization/quantize_/workflows/float8 --verbose -s
python test/quantization/quantize_/workflows/int4/test_int4_tensor.py
python test/quantization/quantize_/workflows/int4/test_int4_preshuffled_tensor.py
./test/float8/test_everything_single_gpu.sh
pytest test/prototype/mx_formats/ --verbose -s
pytest test/prototype/moe_training/test_fp8_grouped_mm.py --verbose -s
pytest test/prototype/moe_training/test_mxfp8_grouped_mm.py --verbose -s
pytest test/prototype/moe_training/test_training.py --verbose -s
pytest test/prototype/gptq/ --verbose -s