Ci/multiprocessing dataloader tests#29
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Production defaults use num_workers=4 with spawn multiprocessing, but all CI jobs and tests forced num_workers=0. Add coverage for both layers: - New test (test_dataloader_multiprocessing.py): verifies the Stim inference datapipe is pickle-safe and produces correct results with num_workers=2 across X, Z, and mixed bases. Runs on CPU in a dedicated ci.yml job. - New ci-gpu.yml step: re-runs inference with PREDECODER_INFERENCE_NUM_WORKERS=2 after the existing smoke run, exercising the full logical_error_rate.py pipeline (multi-worker DataLoader → model forward → PyMatching → LER check). Signed-off-by: kvmto <kmato@nvidia.com>
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Production defaults use num_workers=4 with spawn multiprocessing, but all CI jobs and tests forced num_workers=0. Add coverage for both layers: - New test (test_dataloader_multiprocessing.py): verifies the Stim inference datapipe is pickle-safe and produces correct results with num_workers=2 across X, Z, and mixed bases. Runs on CPU in a dedicated ci.yml job. - New ci-gpu.yml step: re-runs inference with PREDECODER_INFERENCE_NUM_WORKERS=2 after the existing smoke run, exercising the full logical_error_rate.py pipeline (multi-worker DataLoader → model forward → PyMatching → LER check). Signed-off-by: kvmto <kmato@nvidia.com>
ivanbasov
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Apr 10, 2026
Production defaults use num_workers=4 with spawn multiprocessing, but all CI jobs and tests forced num_workers=0. Add coverage for both layers: - New test (test_dataloader_multiprocessing.py): verifies the Stim inference datapipe is pickle-safe and produces correct results with num_workers=2 across X, Z, and mixed bases. Runs on CPU in a dedicated ci.yml job. - New ci-gpu.yml step: re-runs inference with PREDECODER_INFERENCE_NUM_WORKERS=2 after the existing smoke run, exercising the full logical_error_rate.py pipeline (multi-worker DataLoader → model forward → PyMatching → LER check). Signed-off-by: kvmto <kmato@nvidia.com>
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Summary
test_dataloader_multiprocessing.py: verifies the Stim inference datapipe works withnum_workers=2and spawn multiprocessing (X, Z, mixed bases). CPU-only.multiprocessing-dataloaderjob toci.ymlto run the above on every push/PR.ci-gpu.ymlgpu-teststhat re-runs withPREDECODER_INFERENCE_NUM_WORKERS=2, exercising the fulllogical_error_rate.pypipeline with multi-worker loading.Production defaults use
num_workers=4, but all CI and tests previously forcednum_workers=0.Test plan
multiprocessing-dataloaderjob passesgpu-testsmulti-worker inference step passes