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author | Francesco Petrogalli <francesco.petrogalli@arm.com> | 2022-06-30 10:22:01 +0000 |
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committer | Francesco Petrogalli <francesco.petrogalli@arm.com> | 2022-07-19 09:26:27 +0000 |
commit | 553f6953fe3bdfad53c11c25f305a16d79d83b24 (patch) | |
tree | 73642b948b79662096f593458c6138d2f7f48ec6 /src/cpu/operators/CpuGemmConv2d.h | |
parent | 99c46475daf277aa53e6747f9e41209f418fed33 (diff) | |
download | ComputeLibrary-553f6953fe3bdfad53c11c25f305a16d79d83b24.tar.gz |
[ONCPUML-951] Variable weight support for Convolution.
API changes for NEGEMMConvolutionLayer and CpuGemmConv2d
Built with:
scons neon=1 opencl=0 os=linux arch=armv8.2-a multi_isa=1 \
build=native -j32 Werror=false validation_tests=1 build_dir=opt \
standalone=1 asserts=1 experimental_fixed_format_kernels=1 .
Tested with:
./build/opt/tests/arm_compute_validation
Hardware where the test executable was run:
Neoverse N1
Test coverage:
* NEGEMMConvolutionLayer, CpuGemmConv2d
* NHWC (the only one supported by the fixed-format kernels)
* F16, F32
* Shapes: RunSmall
Change-Id: I4fd3e495a7cbf61210ea02d37440ba9652934e99
Signed-off-by: Francesco Petrogalli <francesco.petrogalli@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7632
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/cpu/operators/CpuGemmConv2d.h')
-rw-r--r-- | src/cpu/operators/CpuGemmConv2d.h | 24 |
1 files changed, 22 insertions, 2 deletions
diff --git a/src/cpu/operators/CpuGemmConv2d.h b/src/cpu/operators/CpuGemmConv2d.h index aec4a2ffa5..f8f0bce048 100644 --- a/src/cpu/operators/CpuGemmConv2d.h +++ b/src/cpu/operators/CpuGemmConv2d.h @@ -117,6 +117,17 @@ public: const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false, unsigned int num_groups = 1); + /** Indicates whether or not there is an optimal assembly implementation that can be used to process the given parameters. + * + * The paramter list is the same as @ref NEGEMMConvolutionLayer::has_opt_impl + * + * @return a status. + */ + static Status has_opt_impl(arm_gemm::WeightFormat &expected_weight_format, const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, + const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), + const bool enable_fast_math = false); + // Inherited methods overridden: void run(ITensorPack &tensors) override; void prepare(ITensorPack &tensors) override; @@ -135,9 +146,11 @@ private: * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation * available which may introduce a drop of accuracy as well. Default is false * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) + * @param[in] fixed_format (Optional) Select GEMM execution with variable weights. + * @param[in] weight_format (Optional) The layout to be used for the weights tensor when running GEMM with variable weights. */ void configure_mm(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo(), - bool enable_fast_math = false, int gemm_3d_depth = 1); + bool enable_fast_math = false, int gemm_3d_depth = 1, bool fixed_format = false, arm_gemm::WeightFormat weight_format = arm_gemm::WeightFormat::UNSPECIFIED); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer matrix multiply routines * * @param[in] src Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32. @@ -151,11 +164,13 @@ private: * available which may introduce a drop of accuracy as well. Default is false * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1) * @param[in] skip_im2col (Optional) Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. (Default to false) + * @param[in] fixed_format (Optional) Select GEMM execution with variable weights. + * @param[in] weight_format (Optional) The layout to be used for the weights tensor when running GEMM with variable weights. * * @return a status */ static Status validate_mm(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const ActivationLayerInfo &act_info = ActivationLayerInfo(), - bool enable_fast_math = false, int gemm_3d_depth = 1, bool skip_im2col = false); + bool enable_fast_math = false, int gemm_3d_depth = 1, bool skip_im2col = false, bool fixed_format = false, arm_gemm::WeightFormat weight_format = arm_gemm::WeightFormat::UNSPECIFIED); /** Static function to check if GEMM3D is supported in @ref NEGEMM or in @ref CpuGemmMLowpMatrixMultiplyCore * * @param[in] src Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32. @@ -187,6 +202,11 @@ private: static SkipInfo skip_im_col_info(const ITensorInfo *src, const ITensorInfo *weights, const PadStrideInfo &conv_info, const Size2D &dilation, const ActivationLayerInfo &act_info); + /** Indicates if the convolution executes in variable weights mode. + * + * Similar to @ref CpuGemm::isVarWeightsKernel + */ + bool isVarWeightsKernel() const; enum AuxTensorIdx { // CpuGemmLowpMatrixMultiplyCore has up to 8 internal tensors |