[Arm backend] Fix for TOSA BI clamp ops#3092
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Min/max range values need to be on quantized form. Change-Id: I68d091306890f0a500d829ce20fc337e6cbe9dba Signed-off-by: Fredrik Knutsson <fredrik.knutsson@arm.com>
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/3092
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit ef71c6d with merge base 73599f4 ( BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Change-Id: Ie59881824d76d5a9c30e95a8024dbbb11055577b
| reference_output, | ||
| quantization_scale, | ||
| ) = self._calculate_reference_output( | ||
| (reference_output, quantization_scale,) = self._calculate_reference_output( |
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lintrunner did this
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hmm, the CI lintrunner seem to think differently than my local one
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Weird. I use the same version, 0.11.0, as mandated by the contribution guidelines. I had to re-run lintrunner init to get the same result. I'll push the update soon...
| atol=atol, | ||
| rtol=rtol, | ||
| ), ( | ||
| assert torch.allclose(model, ref, atol=atol, rtol=rtol,), ( |
Change-Id: Ia773c04d17f24bd155365a412b3e96c3b3d9aa63
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CI failures not related to this PR. |
| scale, zp = get_quant_node_args(node.all_input_nodes[0]) | ||
| # Convert to quantized representation | ||
| clamp_min_qs = round((inputs[1].number / scale) + zp) | ||
| clamp_min_qs = max(clamp_min_qs, -128) |
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we should get qmin/qmax from the quant node
Change-Id: I9dee9bec58e51fcef57ebb287dbad62016c221d1
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@digantdesai merged this pull request in b0a400c. |
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Min/max range values need to be on quantized form.