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| author | Georgios Pinitas <georgios.pinitas@arm.com> | 2021-07-16 16:16:43 +0100 |
|---|---|---|
| committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2021-07-22 02:25:50 +0000 |
| commit | 4ee8b1599dbaf7634d25607fa5ac96ba3dc6b0f2 (patch) | |
| tree | 2f8362d33cdad4212f4b96995681c68184c759e1 /src/runtime/cpu/operators/CpuGemmConvolution.cpp | |
| parent | 59fd7a722e5bc7e85309d6200bc37a772721a719 (diff) | |
| download | ComputeLibrary-4ee8b1599dbaf7634d25607fa5ac96ba3dc6b0f2.tar.gz | |
Update GEMM assembly kernels
- Introduce Fp32 kernels with internal calculations in Bfloat16 when
fast_mode is enabled
- Improve kernel selection heuristics
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I68a9e7e862b6fd2721b46e0d7cc791091c4ab279
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5965
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/runtime/cpu/operators/CpuGemmConvolution.cpp')
| -rw-r--r-- | src/runtime/cpu/operators/CpuGemmConvolution.cpp | 9 |
1 files changed, 5 insertions, 4 deletions
diff --git a/src/runtime/cpu/operators/CpuGemmConvolution.cpp b/src/runtime/cpu/operators/CpuGemmConvolution.cpp index a0424b1c63..fcdf8aa8f6 100644 --- a/src/runtime/cpu/operators/CpuGemmConvolution.cpp +++ b/src/runtime/cpu/operators/CpuGemmConvolution.cpp @@ -66,7 +66,7 @@ void CpuGemmConvolution::configure_mm(const ITensorInfo *src, const ITensorInfo // Create GEMMInfo structure const GEMMInfo &gemm_info = GEMMInfo(false, false, true /* Reshape weights only for the first run */, gemm_3d_depth, _skip_im2col /* Reinterpret the input as 3D if im2col is skipped */, - false, GEMMLowpOutputStageInfo(), false, false, act_info); + false, GEMMLowpOutputStageInfo(), false, false, false, act_info); // Supported activations in GEMM const std::set<ActivationLayerInfo::ActivationFunction> supported_acts = { ActivationLayerInfo::ActivationFunction::RELU, @@ -115,7 +115,7 @@ void CpuGemmConvolution::configure_mm(const ITensorInfo *src, const ITensorInfo quantization::calculate_quantized_multipliers(iqinfo, wqinfo, oqinfo, output_info); _mm_gemmlowp = std::make_unique<CpuGemmLowpMatrixMultiplyCore>(); - _mm_gemmlowp->configure(&tmp_src, &tmp_weights, biases, dst, GEMMInfo(false, false, true, gemm_3d_depth, _skip_im2col, false, output_info, false, false, act_info)); + _mm_gemmlowp->configure(&tmp_src, &tmp_weights, biases, dst, GEMMInfo(false, false, true, gemm_3d_depth, _skip_im2col, false, output_info, false, false, false, act_info)); auto mm_mem_req = _mm_gemmlowp->workspace(); for(unsigned int cont = 0; cont < mm_mem_req.size(); ++cont) @@ -146,7 +146,7 @@ Status CpuGemmConvolution::validate_mm(const ITensorInfo *src, const ITensorInfo // Create GEMMInfo structure const GEMMInfo gemm_info = GEMMInfo(false, false, true /* Reshape weights only for the first run */, gemm_3d_depth, skip_im2col /* Reinterpret the input as 3D if im2col is skipped */, - false, GEMMLowpOutputStageInfo(), false, false, act_info); + false, GEMMLowpOutputStageInfo(), false, false, false, act_info); if(is_quantized) { @@ -186,7 +186,8 @@ Status CpuGemmConvolution::validate_mm(const ITensorInfo *src, const ITensorInfo std::unique_ptr<ITensorInfo> weights_qa = weights->clone(); input_qa->set_quantization_info(QuantizationInfo(iqinfo.uniform().scale, -iqinfo.uniform().offset)); weights_qa->set_quantization_info(QuantizationInfo(wqinfo.uniform().scale, -wqinfo.uniform().offset)); - return CpuGemmLowpMatrixMultiplyCore::validate(input_qa.get(), weights_qa.get(), biases, dst, GEMMInfo(false, false, true, gemm_3d_depth, skip_im2col, false, output_info, false, false, act_info)); + return CpuGemmLowpMatrixMultiplyCore::validate(input_qa.get(), weights_qa.get(), biases, dst, GEMMInfo(false, false, true, gemm_3d_depth, skip_im2col, false, output_info, false, false, false, + act_info)); } else { |