Arm backend: Add support for amax/max/amin/min #8829
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Max/min can be decomposed as for example max(x) = (amax(x), argmax(x)) For MI, an operator support check is added to support max-ops for which the argmax is not used. For BI, the int64 dtype returned by argmax is currently not supported by the arm_quantizer, and the program will crash. This is the same behaviour as before the patch, but with an improved error message. - Adds op_amax/op_amin node visitors. - Renames op_max/min->op_maximum/minimum to clearly separate the two ops. - Adds convert_minmax_pass to make min/max/amin/amax TOSA-compatible. - Adds unittests Util updates: - Updates analyze_output_utils to support rank 0. - Adds quantization to OpNotSupportedPipeline Change-Id: I0a7ff126696a9b46568787c40cdf128f0c00f631 Signed-off-by: Adrian Lundell <[email protected]>
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/8829
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 Cancelled Job, 1 Unrelated FailureAs of commit 25e6802 with merge base 4df0ade ( CANCELLED JOB - The following job was cancelled. Please retry:
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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Max/min can be decomposed as for example
max(x) = (amax(x), argmax(x))
For MI, an operator support check is added to support max-ops for which the argmax is not used. For BI, the int64 dtype returned by argmax is currently not supported by the arm_quantizer, and the program will crash. This is the same behaviour as before the patch, but with an improved error message.
Util updates:
cc @digantdesai @freddan80 @per @zingo @oscarandersson8218