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Run TorchTitan GraphTrainer AutoParallel CI #452

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21 changes: 21 additions & 0 deletions .github/workflows/test_torchtitan.yml
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Expand Up @@ -51,3 +51,24 @@ jobs:
# Check that AutoParallel and TorchTitan DeepSeek V3 produce matching
# distributed loss and gradient norms for the same 4-GPU debug shape.
torchrun --standalone --nproc-per-node 4 ../tests/torchtitan_dsv3_equivalence.py

# Run TorchTitan GraphTrainer AutoParallel integration tests.
rm -rf /tmp/graph_trainer_autoparallel_tests
mkdir -p /tmp/graph_trainer_autoparallel_tests
trap 'rm -rf /tmp/graph_trainer_autoparallel_tests' EXIT
python -m torchtitan.experiments.graph_trainer.tests.integration_tests \
/tmp/graph_trainer_autoparallel_tests/llama3 \
--test_suite graph_trainer_autoparallel \
--test_name autoparallel_llama3_fsdp_tp \
--gpu_arch_type cuda \
--ngpu 4
NCCL_NVLS_ENABLE=0 python -m torchtitan.experiments.graph_trainer.tests.integration_tests \
/tmp/graph_trainer_autoparallel_tests/deepseek_v3 \
--test_suite graph_trainer_autoparallel_h100 \
--test_name autoparallel_deepseek_v3_efsdp_ep \
--gpu_arch_type cuda \
--ngpu 4

# Run TorchTitan GraphTrainer AutoParallel numerics tests.
pytest torchtitan/experiments/graph_trainer/tests/test_numerics.py::TestGraphTrainerAutoParallelNumerics::test_llama3_aot_fx_trace_autoparallel_vs_eager -v
NCCL_NVLS_ENABLE=0 pytest torchtitan/experiments/graph_trainer/tests/test_numerics.py::TestGraphTrainerAutoParallelNumerics::test_deepseek_v3_aot_fx_trace_autoparallel_vs_eager -v
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