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Prepare SKaiNET for TurboQuant with refactoring #451

@michalharakal

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@michalharakal

SKaiNET is close to TurboQuant-readiness, but core refactoring is needed first.

  • separate logical dtype from physical encoding/layout
  • introduce buffer/storage abstractions
  • add explicit placement and memory-domain modeling
  • reduce copy-heavy materialization/loading paths
  • unify packed quantized tensor storage

TODOs

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