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For our use case we are executing basic ONNX models e.g. LinearClassifier millions of times.
And so the overhead of Tract is our biggest performance impact.

This PR aims to "front-load" more work during the plan stage.

Based on benchmarks we see a ~3x performance improvement.

@kali
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kali commented Jan 8, 2026

Wow, ok, this one may be more tricky than the new ops in onnx/ml :)
First question, can we split it into two PR to discuss the plan side and the symbols side separately or are they strongly coupled one way or the other ?

@threeseed threeseed changed the title Precompute more metadata during plan + add symbol cache Precompute more metadata during plan Jan 9, 2026
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On further testing the symbol cache isn't going to be beneficial for most users so will leave it out.

This is just the precompute piece.

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3 participants