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[2/17] Add shared ONNX model saving for DLA surgeries - #2939
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| Layer / File(s) | Summary |
|---|---|
Inline and external save modes modelopt/onnx/graph_surgery/utils/graph_utils.py, tests/unit/onnx/graph_surgery/test_graph_utils.py |
Exports save_onnx_model with inline and external-data options. Storage metadata is restored after inline saves. Tests cover payload round trips and rejection of partially unloaded external tensors. |
Sidecar destination validation modelopt/onnx/graph_surgery/utils/graph_utils.py, tests/unit/onnx/graph_surgery/test_graph_utils.py |
Validates sidecar paths and rejects tested path aliases, symlinks, non-files, and multiply hard-linked files. Tests check that rejected destinations leave existing files and caller tensors unchanged. |
Staged save and recovery modelopt/onnx/graph_surgery/utils/graph_utils.py, tests/unit/onnx/graph_surgery/test_graph_utils.py |
Stages the model and sidecar before installation. On failures, the code restores existing files or removes newly installed weights and restores tensor metadata. Tests cover write, read, and replacement failures, plus retries. |
Priority:
Estimated code review effort: 4 (Complex) | ~45 minutes
Change: Feature
Sequence Diagram(s)
sequenceDiagram
participant Caller
participant save_onnx_model
participant Staging
participant OutputFiles
Caller->>save_onnx_model: Request model save
save_onnx_model->>Staging: Write staged model and weights
Staging->>OutputFiles: Install sidecar and replace model
OutputFiles-->>save_onnx_model: Report replacement failure
save_onnx_model->>OutputFiles: Restore backup or remove new weights
save_onnx_model-->>Caller: Return save result
Possibly related PRs
- NVIDIA/Model-Optimizer#2831: Creates and exports the
graph_utils.pymodule extended by this PR. - NVIDIA/Model-Optimizer#2816: Updates the ONNX version on Windows for external tensor writes, which this PR also handles.
Merge Risk: 
6a8a2
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This adds a shared ONNX save helper that stages files and restores caller state when a save fails. No unresolved merge-blocking defect remains. The repeated-save failure in the working directory is avoided because the conversion step no longer sees the final sidecar name.
Pre-merge checks: 
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Check name Status Explanation Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title accurately identifies the main change: adding shared ONNX model-saving support for DLA surgeries. It is concise and specific. Docstring Coverage Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within survi… Linked Issues check Check skipped because no linked issues were found for this pull request. Out of Scope Changes check Check skipped because no linked issues were found for this pull request. Security Anti-Patterns PASS. The pull request changes only graph_utils.pyand its unit tests. The changed Python files contain notorch.load(..., weights_only=False),numpy.load(..., allow_pickle=True), hardcoded `tru…Full details: Docstring Coverage
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Explanation
Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Documentation-only edits and deletions within surviving functions are included; unchanged diff context and fully deleted functions are excluded. Analyzed 19 functions across 2 files.
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Explanation
PASS. The pull request changes only
graph_utils.pyand its unit tests. The changed Python files contain notorch.load(..., weights_only=False),numpy.load(..., allow_pickle=True), hardcodedtrust_remote_code=True,eval,exec, or# nosec. The pull request adds nopyproject.tomlor requirements dependency changes.
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Inline comments:
Review comments at @modelopt/onnx/graph_surgery/utils/graph_utils.py:
- Around line 145-146: Update the replacement flow around
os.replace(staged_weights, destination) and os.replace(staged_model,
output_path) so the existing sidecar remains intact until the model replacement
succeeds; if model replacement fails, restore the previous sidecar before
propagating the failure.
- Line 168: Update _save_external_weights to preserve the caller’s tensor data
and metadata if either os.replace operation fails, by externalizing a copy or
restoring the original tensor state on failure. Keep the documented mutation on
successful saves.
- Around line 143-145: Before os.replace in the sidecar destination flow,
resolve the output directory and destination parent and reject destinations
whose resolved parent is outside the resolved output directory; keep the
replacement for destinations that remain contained.
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Additional details and impacted files@@ Coverage Diff @@
## main #2939 +/- ##
==========================================
- Coverage 79.97% 77.21% -2.77%
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Files 661 661
Lines 75419 75531 +112
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- Hits 60315 58319 -1996
- Misses 15104 17212 +2108
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Inline comments:
Review comments at @modelopt/onnx/graph_surgery/utils/graph_utils.py:
- Around line 226-231: In the payload restoration loop over payloads, read each
payload into a temporary value and verify its length matches the recorded length
before assigning tensor.raw_data. Raise a clear error on a short read so
truncated data is never treated as successfully restored.
- Line 133: Update the validation around _validate_external_data_destination to
compare the resolved destination with the resolved output model path and reject
a match. Preserve the existing check that external data stays inside
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Review comments at @modelopt/onnx/graph_surgery/utils/graph_utils.py:
- Around line 210-214: Update the external-data tensor handling around the
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rather than silently skipping them; raise an error before conversion or
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Local fixes and regression evidence are recorded in the updated Testing section. The custom writer is replaced by the fixed ONNX helper, with staging and caller-state safeguards retained. |
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Rebased this PR and the dependent series onto main 35922f1. The Windows ONNX 1.23.2 requirement is now inherited from main, so pyproject.toml is absent from this PR’s diff. The remaining change provides the shared save helper and its regression coverage.
Add a shared graph-surgery saver with staged output replacement and binary external-weight writing to avoid ONNX 1.21 Windows trailing-0x1A corruption. Cover FP16, FP32, and INT8 payloads, repeated saves, nested paths, and invalid-location refusal. Preserve the existing dtype converter and public surgery implementations. Signed-off-by: mgohil <mgohil@nvidia.com>
Validate resolved sidecar paths and reject symbolic or multiply linked files. Preserve existing output weights and restore caller tensor data and metadata when replacement fails, while retaining successful-save mutation and avoiding a full weight copy. Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
Signed-off-by: mgohil <mgohil@nvidia.com>
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Updated on main 35922f1 at 6a8a2ba. Rebased this PR and the dependent series onto main 35922f1. The Windows ONNX 1.23.2 requirement is now inherited from main, so pyproject.toml is absent from this PR’s diff. The remaining change provides the shared save helper and its regression coverage. 1,586 integration tests pass. The save helper continues to delegate payload writes to ONNX while preserving staged replacement, rollback and caller-state checks. Signed histories verify; full review requested for this head. |
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Withdrawn as requested: the DLA pipeline now saves directly with onnx.save, matching existing graph surgeries and using the Windows ONNX fix already present on main. The custom save wrapper and its tests are removed from the active series. Remaining PR numbers are retained; #2955 now starts the remaining series directly on main. |
What does this PR do?
Type of change: new feature
Add
save_onnx_model, a shared save helper for the upcoming DLA pipeline. It supports inline weights or a configurable external sidecar while retaining the model's IR version. Use ONNX's external-data writer rather than maintaining a custom binary writer. The Windows ONNX~=1.23.2dependency and binary-mode fix are inherited from main after #2816; this PR adds no dependency change.Inline saves embed loaded payloads even when tensors retain
EXTERNALmetadata. ONNX performs the inline conversion, and a shared metadata-only journal restores the caller infinally, including on write failures. Tensor payloads are not copied into a second model. Inline serialization is staged in the destination directory beforeos.replace, so partial writes and replacement failures preserve an existing model file.Validate loaded tensor payloads and sidecar destinations before mutation. External data must remain inside the output directory, stay distinct from the model, and satisfy ONNX's file-link restrictions. Stage the files and preserve the previous sidecar until model replacement succeeds; replacement failures restore the sidecar and the caller's tensor bytes and storage metadata. Short restoration reads raise an explicit error. Successful external saves retain the documented storage-metadata mutation. Caller payloads remain intact until every ONNX sidecar write and close succeeds; a failed buffered write or close restores metadata without trying to recover bytes from an incomplete sidecar.
Use separate model and payload staging roots so filename aliases cannot overwrite staged weights. Check filesystem identity after installing the sidecar and roll back an alias before writing the model. Reject NTFS alternate data streams before filesystem changes.
Repeated saves also work when the output directory is the working directory. Conversion uses a temporary location; the final sidecar name is assigned while writing the staged payloads. Existing converters and public surgeries retain their implementations.
Usage
Rebased this PR and the dependent series onto main 35922f1. The Windows ONNX 1.23.2 requirement is now inherited from main, so pyproject.toml is absent from this PR’s diff. The remaining change provides the shared save helper and its regression coverage.
Testing
Windows CPU: Python 3.11.18, ONNX 1.23.2, ONNX Runtime 1.22.0. 1,586 tests pass across the complete restacked graph-surgery and public-compatibility suite on main 35922f1. The save helper continues to delegate payload writes to ONNX while preserving staged replacement, rollback and caller-state checks.
The actual final package is validated with the original save and initializer-conversion implementations. Required hooks pass with Linux CI typing semantics and all commits are signed. The default Windows mypy invocation reports an unchanged upstream os.sched_getaffinity attribute error in prepare_megatron_data_blend.py; the temporary local platform setting retains all other repository typing options. GPU execution, DLA compilation and the complete Linux suite were not run locally; GitHub CI runs separately.
Before your PR is "Ready for review"
Backward compatible: yes; existing converters and surgeries retain their behavior.
Third-party code/new runtime dependencies: no new runtime dependency; contribution and security guidance reviewed.
Necessary tests: included, with regression cases verified before and after each fix.
Changelog: public DLA integration is documented in part 16.
Commits: signed off and SSH-signed. New helper and test functions have docstrings.
Claude approval: pending for the current commits.
Additional Information
Part 2/17, after PR1 #2831 (merged). The next slice is PR3 #2955. Merge the stack from the bottom upward; public API/CLI integration follows in part 16.
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