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JanFSchulte
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Nov 6, 2024
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| def config_from_onnx_model( | ||
| model, granularity='name', backend=None, default_precision='ap_fixed<16,6>', default_reuse_factor=1 | ||
| model, granularity='name', backend=None, default_precision='fixed<16,6>', default_reuse_factor=1, max_precision=None |
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Out of curiosity, why this change of removing the ap_? Should I do the same in #1112?
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This part is backend-agnostic, so there's no reason to put ap_ or ac_. (I think the ones without a prefix follow the ap_style, though, with regard to signedness, using uint/ufixed instead of false being passed as an argument.) The right type should be produced based on the backend, since it will internally go to the FixedPrecisionType. I think all thee styles are supported, those with either prefix, or without a prefix, regardless of the backend (i.e. there's no reason to change this when you switch backends).
JanFSchulte
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Nov 11, 2024
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Description
This is analogous to PR #1112 but for for ONNX. For ONNX, auto was the default, but max_precision was not set. This copies what we have for the Keras parser.
Type of change
Tests
We should make sure that this doesn't break anything, but truthfully, I am not sure if we have tests to test the max_precision behavior for any frontend, including Keras. Should we add such tests?
Checklist
pre-commiton the files I edited or added.