fix(pt): optimize createNlistTensor

[njzjz]

Summary by CodeRabbit

• New Features

  • Enhanced tensor creation process for improved performance and efficiency.

• Bug Fixes

  • Improved error handling for PyTorch-related exceptions, providing clearer error messages.

Copilot wasn't able to review any files in this pull request.

Files not reviewed (2)

• source/api_cc/src/DeepPotPT.cc: Language not supported
• source/api_cc/src/DeepSpinPT.cc: Language not supported

[coderabbitai]

📝 Walkthrough

Walkthrough

The changes in this pull request involve significant refactoring of the tensor creation logic and error handling in the DeepPotPT and DeepSpinPT classes. The createNlistTensor and createNlistTensor2 functions have been updated to eliminate intermediate tensor structures, allowing for direct tensor creation from flattened input data. Additionally, the translate_error methods in both classes have been enhanced to catch specific PyTorch exceptions and rethrow them as deepmd::deepmd_exception with detailed messages. Overall, the modifications streamline tensor operations and improve error reporting.

Changes

File	Change Summary
source/api_cc/src/DeepPotPT.cc	Refactored createNlistTensor to create a tensor directly from a flattened vector of integers. Enhanced translate_error to catch specific PyTorch exceptions and rethrow them as deepmd::deepmd_exception.
source/api_cc/src/DeepSpinPT.cc	Refactored createNlistTensor2 to flatten input data for tensor creation. Updated translate_error for improved exception handling similar to DeepPotPT.

Possibly related PRs

• fix(cc): fix message passing when nghost is 0 and send list is empty #4237: The changes in this PR also involve modifications to the translate_error method in the DeepPotPT class, enhancing error handling similar to the main PR's updates. Additionally, both PRs refactor tensor creation logic, indicating a direct relationship in their focus on improving the DeepPotPT class functionality.

Suggested labels

C++, LAMMPS

Suggested reviewers

• wanghan-iapcm

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[coderabbitai]

Actionable comments posted: 1

🧹 Outside diff range and nitpick comments (1)

source/api_cc/src/DeepPotPT.cc (1)

38-42: Consider pre-allocating the flat_data vector with reserve.

While the current implementation uses reserve, it could be more efficient to pre-allocate the exact size since we already know it.

-  flat_data.reserve(total_size);
+  flat_data.resize(total_size);
+  size_t offset = 0;
   for (const auto& row : data) {
-    flat_data.insert(flat_data.end(), row.begin(), row.end());
+    std::copy(row.begin(), row.end(), flat_data.begin() + offset);
+    offset += row.size();
   }

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL

📥 Commits

Reviewing files that changed from the base of the PR and between d1712c9 and 190d1e6.

📒 Files selected for processing (2)

• source/api_cc/src/DeepPotPT.cc (1 hunks)
• source/api_cc/src/DeepSpinPT.cc (1 hunks)

🔇 Additional comments (2)

source/api_cc/src/DeepPotPT.cc (2)

Line range hint 15-31: LGTM! Improved error handling with specific PyTorch exception types.

The error handling implementation is well-structured and provides clear error messages for different types of PyTorch exceptions.

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34-47: LGTM! Efficient tensor creation implementation.

The implementation efficiently creates tensors by flattening the data first and then reshaping, which eliminates intermediate tensor structures.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 84.59%. Comparing base (d1712c9) to head (190d1e6).
Report is 7 commits behind head on devel.

Additional details and impacted files

@@           Coverage Diff           @@
##            devel    #4403   +/-   ##
=======================================
  Coverage   84.59%   84.59%           
=======================================
  Files         614      614           
  Lines       57009    57012    +3     
  Branches     3486     3486           
=======================================
+ Hits        48224    48227    +3     
+ Misses       7660     7659    -1     
- Partials     1125     1126    +1     

☔ View full report in Codecov by Sentry.
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