Add an implementation an NHWC implementation of convolution to avoid transposes #26834
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…transposes * Modification to the CPU EP to specify channels_last when data format is NWHC * Added a FusedNhwcConv kernel * Implementation of the kernel in mlas * Added compiler guards so it is inly used with KleidiAi (for now, can be removed if needed) * Added unittests Signed-off-by: Orlaith Monahan <orlaith.monahan@arm.com>
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@microsoft-github-policy-service agree company="Arm" |
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Feedback appreciated as this PR makes quite a lot of changes to the codebase well outside of the normal KleidiAI scope. |
Signed-off-by: Orlaith Monahan <orlaith.monahan@arm.com>
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Hi @orlmon01, I imagine that avoiding transposes also improves performance. |
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Description
Currently OnnxRT supports NCHW as a default datalayout. For optimisations and kernels that operate better in NHWC layout, or where the datalayout is NHWC in the first place Transposes are added around the layers. This patch seeks to eliminate them in cases of convolutions where it would cause a performance decrease.
Motivation and Context
KleidiAi specific implementation of this feature. Only supports convolutions, DepthWise to follow. Currently a little strict with the filters as a result.