[BYOC-DNNL] Support DNNL optimal layout#10421
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| // infer weight's shape for group convolution | ||
| wshape = {{param->groups, indexdiv(param->channels, param->groups), | ||
| indexdiv(dshape_nchw[1], param->groups), param->kernel_size[0], | ||
| param->kernel_size[1]}}; |
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I'm pretty sure we already support group convolution and this one looks unusual. If this is DNNL specific, can you come up with a better name than is_group?
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DNNL prefer to use GOIHWxg layout for group conv's weights. It seems that the layout cannot be transformed from OIHW to GOIHWxg directly. Because the dims are not matched for this two layout. Have this kind of transformation already been supported? If not, how about use is_dnnl_group_conv instead of is_group?
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I don't think such transform is possible now. Yeah, is_dnnl_group_conv sounds better.
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* enable dnnl optimal layout for supported ops * verfied cv models with onednnv1.7 * rebase to the latest main branch * fix format related comments * remove unnecessary layout transformation * change deconv into conv_transpose * rename some variables and functions * simplify query_layout * add checkes for query_layout * fix lint * move partition_for_dnnl from dnnl.py to test_dnnl.py * remove unnecessary model test * add more dnnl layout * rename flag in convolution.cc * enhance dnnl layout
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* enable dnnl optimal layout for supported ops * verfied cv models with onednnv1.7 * rebase to the latest main branch * fix format related comments * remove unnecessary layout transformation * change deconv into conv_transpose * rename some variables and functions * simplify query_layout * add checkes for query_layout * fix lint * move partition_for_dnnl from dnnl.py to test_dnnl.py * remove unnecessary model test * add more dnnl layout * rename flag in convolution.cc * enhance dnnl layout
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This PR aims to support BYOC-DNNL run in the dnnl optimal layout. There are two changes needed to be noticed.
GOIHWfirst, so that it can run in optimal dnnl layout like HWOIG16g. Changes inConvolution.ccis needed to enable group conv run in GOIHW layout.get_optimal_layout_for_convandget_optimal_layout_for_deconvfunctions are registered intvm.relay.contribto query the optimal dnnl layout.The related test cases has been added as well.