fix(dpmodel): preserve nopbc batch semantics

[hcustc]

Summary

• translate the legacy non-periodic default_mesh encodings (sizes 0 and 1) to the canonical model input box=None
• preserve periodic boxes for both standard-type and mixed-type batches
• add regression coverage for the batch boundary and a real temporary nopbc NPY system

Root cause

DeepmdDataSystem represents a valid non-periodic system with an empty or single-element default_mesh and an all-zero box placeholder. normalize_batch() dropped the mesh metadata but retained the placeholder, so downstream code treated the non-None box as periodic and attempted to invert a singular cell.

The fix performs the semantic conversion before the metadata is discarded, without mutating the input batch.

Fixes #6002.

Testing

• .venv/bin/python -m pytest source/tests/common/test_batch_nopbc.py source/tests/common/test_batch_charge_state.py -q (10 passed, 10 subtests passed)
• .venv/bin/ruff check .
• .venv/bin/ruff format --check .
• git diff --check

Summary by CodeRabbit

• Bug Fixes

  • Improved handling of non-periodic systems during batch normalization.
  • Non-periodic data now correctly omits placeholder box information.
  • Periodic systems continue to retain their box data.
  • Model inputs now correctly receive no box for valid non-periodic systems.

• Tests

  • Added coverage for legacy mesh metadata and non-periodic data system behavior.

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: Repository UI

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Run ID: 9855518d-6803-47db-88dd-c900b31aa152

📥 Commits

Reviewing files that changed from the base of the PR and between 1dcebad and 4399883.

📒 Files selected for processing (2)

• deepmd/dpmodel/utils/batch.py
• source/tests/common/test_batch_nopbc.py

🚧 Files skipped from review as they are similar to previous changes (1)

• deepmd/dpmodel/utils/batch.py

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📝 Walkthrough

Walkthrough

normalize_batch now converts non-periodic default_mesh encodings to a None model input box. Tests cover periodic preservation, missing metadata, absent boxes, and nopbc NPY integration.

Changes

Non-periodic batch normalization

Layer / File(s)	Summary
Normalize non-periodic batch boxes deepmd/dpmodel/utils/batch.py	normalize_batch detects non-periodic default_mesh values and sets an existing box to None before removing the metadata.
Validate normalization and data-system integration source/tests/common/test_batch_nopbc.py	Tests cover non-periodic and periodic boxes, missing default_mesh, batches without box, and nopbc NPY data-system inputs.

Estimated code review effort: 2 (Simple) | ~10 minutes

Merge Risk: ⚪ Minimal · up to 43998

This change converts legacy non-periodic batch placeholders to the canonical non-periodic representation while preserving periodic batches. No actionable merge-blocking risk remains after normal checks and review.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 14.29% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 7 functions across 2 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly summarizes the primary change: preserving non-periodic batch semantics in dpmodel.
Linked Issues check	✅ Passed	The implementation translates non-periodic default_mesh encodings to box=None before metadata removal. The tests cover non-periodic and periodic batches, missing metadata, and a temporary nopbc system…
Out of Scope Changes check	✅ Passed	The code and test changes directly support the linked issue. No unrelated changes are identified.

Full details: Linked Issues check

Explanation

The implementation translates non-periodic default_mesh encodings to box=None before metadata removal. The tests cover non-periodic and periodic batches, missing metadata, and a temporary nopbc system, satisfying issue #6002.

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[Copilot]

Pull request overview

This PR fixes loss of non-periodic (nopbc) semantics during DeepmdDataSystem batch normalization in deepmd.dpmodel.utils.batch.normalize_batch(). It translates the legacy default_mesh encoding for non-periodic systems (mesh sizes 0/1) into the canonical model input form (box=None), preventing downstream periodic-only code paths from attempting to invert the all-zero placeholder cell.

Changes:

• Convert non-periodic default_mesh encodings (size 0 or 1) to box=None during normalize_batch() (before default_mesh is dropped).
• Preserve periodic boxes unchanged for both standard-type and mixed-type batches.
• Add regression tests covering (a) the mesh-size boundary behavior and (b) a real temporary nopbc NPY system with a zero-box placeholder.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
deepmd/dpmodel/utils/batch.py	Implements non-periodic semantic conversion (default_mesh size 0/1 ⇒ box=None) while keeping periodic boxes intact.
source/tests/common/test_batch_nopbc.py	Adds regression coverage for legacy mesh encodings and an end-to-end nopbc system batch ensuring inputs["box"] is None.

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[Copilot]

Pull request overview

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

[njzjz-bot]

Reviewed the non-periodic batch-normalization path and its coverage. The legacy mesh-size 0/1 encodings are translated before metadata is dropped, periodic encodings remain intact, and the input batch is not mutated. I found no blocking issues.

Coding agent: Codex
Codex version: codex-cli 0.151.0
Model: gpt-5.6-sol
Reasoning effort: xhigh

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 78.84%. Comparing base (8cfd46e) to head (1dcebad).
⚠️ Report is 3 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #6003      +/-   ##
==========================================
- Coverage   79.10%   78.84%   -0.26%     
==========================================
  Files        1105     1105              
  Lines      130981   130985       +4     
  Branches     4771     4771              
==========================================
- Hits       103609   103272     -337     
- Misses      25686    26029     +343     
+ Partials     1686     1684       -2     

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[wanghan-iapcm]

The diagnosis is right and the fix is correct. The layer is right too, which is worth recording: doing this at the producer instead — if not self.pbc: b_data["box"] = None in DeepmdDataSystem.get_batch_standard/get_batch_mixed — would break TensorFlow and JAX training on nopbc systems, since get_batch() is shared with backends that require box to be an array. normalize_batch is the first point downstream of that contract.

Two notes, neither blocking.