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feat(pt): add Mean absolute percentage error (MAPE) loss for prop. pred. #4854
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feat(pt): add Mean absolute percentage error (MAPE) loss for prop. pred. #4854
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📝 WalkthroughWalkthroughSupport for the "mape" (Mean Absolute Percentage Error) loss function and metric is added to the Changes
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Actionable comments posted: 2
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📒 Files selected for processing (1)
deepmd/pt/loss/property.py(3 hunks)
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deepmd/pt/loss/property.py (1)
deepmd/driver.py (1)
label(42-75)
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deepmd/pt/loss/property.py
192-192: f-string without any placeholders
Remove extraneous f prefix
(F541)
🔇 Additional comments (1)
deepmd/pt/loss/property.py (1)
45-45: LGTM!The documentation correctly includes "mape" as a supported loss function option.
Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## devel #4854 +/- ##
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- Coverage 84.76% 84.76% -0.01%
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Files 699 699
Lines 68077 68080 +3
Branches 3541 3542 +1
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+ Hits 57708 57710 +2
- Misses 9235 9237 +2
+ Partials 1134 1133 -1 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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…ed. (deepmodeling#4854) feat: add Mean absolute percentage error (MAPE) loss for property prediction <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Added support for the Mean Absolute Percentage Error (MAPE) as a selectable loss function and metric. * **Documentation** * Updated user-facing documentation to include "mape" as an option for loss function selection. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
feat: add Mean absolute percentage error (MAPE) loss for property prediction
Summary by CodeRabbit
New Features
Documentation