perf: skip bincount if unnecessary #4773
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Pull Request Overview
The PR aims to optimize performance by skipping the costly bincount operation when it is unnecessary. Key changes include adding a conditional to determine whether to compute torch.bincount, updating the logic to adjust the output tensor shape based on available information, and overriding num_owner in specific cases.
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deepmd/pt/model/network/utils.py:40
- Overriding 'num_owner' with bin_count.shape[0] in the else branch may ignore a user-provided value when average is True. Please confirm if this behavior is intentional and update the docstring if needed for clarity.
else:
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📝 Walkthrough""" WalkthroughThe Changes
Sequence Diagram(s)sequenceDiagram
participant Caller
participant aggregate
Caller->>aggregate: Call aggregate(src, index, num_owner, avg)
alt num_owner is None or avg is True
aggregate->>aggregate: Compute bin_count
alt num_owner specified and larger
aggregate->>aggregate: Extend bin_count with ones
end
aggregate->>aggregate: Replace zero bin_count with ones
else
aggregate->>aggregate: Skip bin_count computation
end
aggregate->>aggregate: Initialize output tensor with zeros
aggregate->>aggregate: Perform index_add_ aggregation
alt avg is True
aggregate->>aggregate: Divide output by bin_count
end
aggregate-->>Caller: Return aggregated output
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## devel #4773 +/- ##
=======================================
Coverage 84.79% 84.79%
=======================================
Files 698 698
Lines 67734 67750 +16
Branches 3540 3540
=======================================
+ Hits 57432 57449 +17
Misses 9171 9171
+ Partials 1131 1130 -1 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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iProzd
approved these changes
May 30, 2025
6 tasks
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