1. 15 Mar, 2023 1 commit
    • rocking5566's avatar
      gemm/Conv xdlops + dlops quantization (#625) · 16dc18e0
      rocking5566 authored
      
      
      * Add conv perlayer quantization
      
      * Add gemm_dlops quantization
      
      * Support int8 for innerproduct
      
      * Refine gemm dlops int8 kernel parameter
      
      * Support gfx908(MI100) and gfx90a(MI200)
      
      * clang-format
      
      * Rename example number
      
      * Support different layout for d tensor
      
      * Add conv dlops perchannel quantization example
      
      * Move to example 40
      
      * Extract the common code for different platform (dlops and xdlops)
      
      * Move ot subfolder. Prepare to add other op of quantization
      
      * Refine the quantization instance library
      
      * Add conv dl instances and client example
      
      * Remove unnecessary type
      
      * Add gemm quantization instance
      
      * Add external api and client example
      
      * Refine num_bytes
      
      * Separete different layout to different cpp
      
      * Add more xdl instances
      
      * Revert "Remove unnecessary type"
      
      This reverts commit 820869182f6a8f62b2c9004101ba6bf76b96be14.
      
      * Remove CShuffleDataType in dlops
      Let acc and CShuffleDataType be the same in xdlops
      
      ---------
      Co-authored-by: default avatarzjing14 <zhangjing14@gmail.com>
      16dc18e0
  2. 30 Nov, 2022 1 commit
    • rocking5566's avatar
      gemm, conv perchannel quantization (#503) · ad541ad6
      rocking5566 authored
      * Use gemm_multiple_D instead
      
      * Add gemm bias relu quantization example
      
      * Add pure gemm quantization example
      
      * Add quantization of perchannel conv + bias + relu example
      
      * Refine the code
      
      * Rename multiplier to requant_scale
      
      * Rename the folder
      
      * Remove redundant comment
      
      * Rename the file. Prepare to add perchannel
      
      * Add conv perchannel instance
      
      * Move to quantization folder
      
      * Add conv perchannel client example
      
      * Apply Rangify constructor of HostTensorDescriptor & Tensor<>
      
      * Fix merge error
      ad541ad6