Arm backend: Make INT+FP default for vgf-backend#16176
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zingo merged 1 commit intopytorch:mainfrom Dec 10, 2025
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Make INT+FP default for vgf. With INT+FP, the following issues were solved: - Make sure that pow.Tensor_Scalar is not replaced by pow.Tensor_Tensor during transform_for_annotation. - Make sure that Scalar-ops that also maps to table ops are not replaced by Tensor ops when quantized. - Fix a bug in tosa_supported_operators where nodes with integer outputs were considered ok for partitioning when they shouldn't be. Signed-off-by: Oscar Andersson <oscar.andersson@arm.com> Change-Id: I53c992422b80fd7e93da9d1b07256dccd7115025
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zingo
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### Summary Make INT+FP default for vgf. With INT+FP supported, the following issues were solved: - Make sure that pow.Tensor_Scalar is not replaced by pow.Tensor_Tensor during transform_for_annotation. - Make sure that Scalar-ops that also maps to table ops are not replaced by Tensor ops when quantized. - Fix a bug in tosa_supported_operators where nodes with integer outputs were considered ok for partitioning when they shouldn't be. ### Test plan The plan is to move most of the vgf-tests to lower with both INT and FP support. We can then test both the quantized and non-quantized flows. Signed-off-by: Oscar Andersson <oscar.andersson@arm.com>
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Summary
Make INT+FP default for vgf. With INT+FP supported, the following issues were solved:
Test plan
The plan is to move most of the vgf-tests to lower with both INT and FP support. We can then test both the quantized and non-quantized flows.
cc @freddan80 @per @zingo @digantdesai