aboutsummaryrefslogtreecommitdiff
path: root/src/cpu/operators/CpuFullyConnected.h
AgeCommit message (Collapse)Author
2023-11-08Optimize CpuGemmConv2d start-up timeSiCong Li
When weight has no holes, we can replace CpuWeightsReshapeKernel with: - Collapse by reinterpreting weight's 3 spatial dimensions - Perform CpuTranspose For more details see the documentation in src/cpu/operators/CpuGemmConv2d.cpp This is one optimization since the CpuTranspose is better performing than CpuWeightsReshapeKernel A second optimization is to fuse this transpose with other weight transformations (e.g. pretranspose_B_array in CpuGemmAssemblyDispatch) However this second optimization depends on how the underlying gemm methods (the fall back path: CpuGemmMatrixMultiplyKernel or the assembly path: CpuGemmAssemblyDispatch) chooses to fuse the transpose. Therefore, this patch moves the transpose down from CpuGemmConv2d, to the individual gemm operators where the fusion decision needs to be made, by passing an extra "transpose_b" flag to CpuGemm New transpose_b flag in different scopes (they are all the same, but with different names because pretranspose_b has a different meaning in GemmAssemblyDispatch): GEMMInfo::pretranspose_B -> AsmGemmInfo::transpose_b New auxilliary tensors holding the transposed b result: - CpuGemm optimized path: CpuGemmAssemblyDispatch::PrePretransposedB - CpuGemm fallback path: CpuGemm::PreTransposedRHS Note that this patch does not yet have the second optimization (COMPMID-6595), but it prepares for it. Relates to COMPMID-6595 Resolves COMPMID-6499 Change-Id: I999a2da9da4b2b15369a3cc06d7872c86e0190ea Signed-off-by: SiCong Li <sicong.li@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10526 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Anitha Raj <Anitha.Raj@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-09-28Apply clang-format on repositoryFelix Thomasmathibalan
Code is formatted as per a revised clang format configuration file(not part of this delivery). Version 14.0.6 is used. Exclusion List: - files with .cl extension - files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...) And the following directories - compute_kernel_writer/validation/ - tests/ - include/ - src/core/NEON/kernels/convolution/ - src/core/NEON/kernels/arm_gemm/ - src/core/NEON/kernels/arm_conv/ - data/ There will be a follow up for formatting of .cl files and the files under tests/ and compute_kernel_writer/validation/. Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
2023-07-28Retain back-compatibility for arm_compute/core/Types.hSiCong Li
* Some symbols have been moved from core/Types.h. This patch retains back compatibility so that the user can still include this header for those symbols * A new header core/CoreTypes.h is created to avoid circular dependency. This header includes essential small types that are used across functions * Move all function info types into function_info folder for easier tracking Resolves COMPMID-6330 Related to https://review.mlplatform.org/c/ml/ComputeLibrary/+/9757 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: I4739175c2d4d184a9bc8e28b881b497fab03ca60 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9979 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-06-15Break up arm_compute/core/Types.h a bitMatthew Bentham
Split some of the larger types with inlined code into their own header files, so that the implementation of them needn't be included everywhere. Change-Id: Id3ec2d42efbd33cedb55705a5a24e1b90c8b7a01 Signed-off-by: Matthew Bentham <Matthew.Bentham@arm.com> Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/524782 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9757 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-03-21Add dynamic weights for CPU fully connected layerViet-Hoa Do
Resolves: COMPMID-5917 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I073067b490f2a1b96b81a037ea431c9a2e5c7503 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9322 Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-02-01Remove fixed format strides hackJonathan Deakin
- Remove hack in CpuGemmAssemblyDispatch.cpp which tried to guess strides for fixed format kernels. Instead, expect that strides will have been correctly set on weights externally - Update fixed format test fixtures to set the strides - If the fixed format uses fast math mode, then weights should be of type BFLOAT16. Change the validation logic to accept this. Resolves: [ONCPUML-1131] Co-authored-by: Milos Puzovic <Milos.Puzovic@arm.com> Change-Id: I0f18d8b86b0f639be25fd122fa06a591e90645f2 Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8985 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2022-08-03[ONCPUML-968] Fixed format kernel support in additional APIsMilos Puzovic
Implements required plumbing in order to be able to ask and execute fixed format kernels from NEFullyConnected, NEGEMM and NEGEMMConv2d. These APIs are used to accelerate oneDNN primitives (inner product, matrix multiplication and indirect GEMM respectively) and without changes it would not be possible to call fixed format kernels from those oneDNN primitives. Change-Id: I27534f0491ce28d0ccb98c19f318bd33dcdf2ff5 Signed-off-by: Milos Puzovic <milos.puzovic@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7999 Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2021-11-09Enable fast_math in CpuFullyConnectedcfRod
ONCPUML-529 * Add support for passing fast_math for fullyconnected layers via fc_info. * Add support for passing fast_math to run ACL benchmark graphs. * Add validation test and accuracy tests (updated fixtures). Note: abs and rel. tolerance for fast math mode are set based on experimental data. Signed-off-by: cfRod <crefeda.rodrigues@arm.com> change-Id: Ib107d6264d3ae5e36555334f39a13e678f8618df Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6521 Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2021-08-25Move CPU/GPU files from Core/Runtime to the respective backend foldersGeorgios Pinitas
Legacy structure contained two libraries core/runtime with two backends in each. We reduce the core/runtime libraries to a single library thus merging the backend files Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com> Change-Id: I69545765fe7a730368105cdbd067d3135ec7a174 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6155 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>