[Experimental] Enable kleidi AI examples to run on graviton3

[akote123]

Enable kleidi AI int4 experimental features to run in graviton3.

cc: @metascroy

[pytorch-bot]

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[metascroy]

Hi @akote123, thanks for the PR!

Can you tell me more about which kernels you're trying to run on graviton3?

[akote123]

Hi @akote123, thanks for the PR!

Can you tell me more about which kernels you're trying to run on graviton3?

@metascroy ,
I wanted to use torch ao experimental features to quantize the model with int4 kleidi kernels and run quantized model in pytorch.

[metascroy]

Hi @akote123, thanks for the PR!
Can you tell me more about which kernels you're trying to run on graviton3?

@metascroy , I wanted to use torch ao experimental features to quantize the model with int4 kleidi kernels and run quantized model in pytorch.

Hi @akote123, so there are two kinds of KleidiAI int4 kernels available. One kind is availble in PyTorch itself and models with it can be quantized like this: https://github.com/pytorch/ao/blob/main/torchao/experimental/tests/test_packed_linear_int8_dynamic_activation_intx_weight_layout_target_aten.py#L48-L60

The other belongs in torchao experimental kernels (#1826) and can be built by running:

USE_CPP=1 TORCHAO_BUILD_CPU_AARCH64=1 TORCHAO_BUILD_KLEIDIAI=1 pip install .

from the ao directory (Note that TORCHAO_BUILD_CPU_AARCH64 is automatically set on Arm-based Mac machines).

You can see how to quantize a model using these kernels here: https://github.com/pytorch/ao/blob/main/torchao/experimental/tests/test_int8_dynamic_activation_intx_weight.py#L62-L72 (KleidiAI kernels will only be used with int4, has_weight_zeros=false; otherwise our "universal" kernels will be used. If you build with TORCHAO_BUILD_KLEIDIAI=0, our universal kernels will be used instead of KleidiAI for int4/has_weight_zeros=false, too).