[AutoTVM] Fix hang/crash issues on feature extraction #3689
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cc @cbalint13 @eqy |
vinx13
reviewed
Aug 2, 2019
| feature_len = None | ||
| for idx in indexes: | ||
| if fea_cache[idx] is not None: | ||
| feature_len = fea_cache[idx].shape[-1] |
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Is fea_cache[idx].shape[-1] the same for all non-None element in fea_cache?
Is break missing here?
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Good catch. A break is missing.
All non-None elements should have the same length, otherwise it will raise error in L324
vinx13
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Aug 2, 2019
wweic
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Aug 9, 2019
* [AutoTVM] Fix hang/crash issues on feature extraction * Update xgboost_cost_model.py * fix lint
wweic
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to neo-ai/tvm
that referenced
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Sep 6, 2019
* [AutoTVM] Fix hang/crash issues on feature extraction * Update xgboost_cost_model.py * fix lint
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Currently, if a schedule is invalid and makes tvm crashes during
tvm.lower(e.g. failed tensorization), then it will make the XGBTuner withfeature_type="itervar"crashes or hangs.This pr fixes it and enables the tuners to tolerate these invalid schedules.