NXP backend: Enable Neg with new Neutron flow#20451
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20451
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| tflite_input_preprocess=ToChannelLastPreprocess(), | ||
| tflite_output_preprocess=ToChannelFirstPreprocess(), | ||
| ) | ||
| class TestNeg: |
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You removed tests with multiple different input shapes, and left only 2, both with multiples of num_macs. Why don't you test with more shapes?
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I was inspired by Exp operator. As the op is internally Sub, I considered it tested with various shapes there. Do you think I should add them back?
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Personally I would definitely test with a similar coverage of shapes as we do for other similar operators. We never know what sort of edge case it might uncover. Or if we ever decide to support the operator some other way (e.g. we decide Mul(x, -1) is more efficient or whatever), relying on the tests of some other operator may be invalid.
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MartinPavella
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Please add more shapes to the tests. Otherwise, LGTM 👍🏻
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Summary
Add tests verifying correct support for
negby the Neutron backend using the new Neutron MLIR flow.Test plan
Unit tests provided.
cc @robert-kalmar @JakeStevens @digantdesai @rascani