aboutsummaryrefslogtreecommitdiff
path: root/arm_compute/runtime/NEON/functions
AgeCommit message (Collapse)Author
2024-04-15Add s8f32 kernels and dynamic QuantizationInfoJonathan Deakin
- Add support for QASYMM_SIGNED*QASYMM8_SIGNED->F32 in CpuGemmLowpMatrixMultiplyCore - Add s8f32 kernel using existing s8->s32 kernels with a new DequantizeFloat OutputStage, the structure is similar to Requantize32 but the opposite way around. - Add SME s8f32 kernels with integrated support for DequantizeFloat. - Add scale to CpuGemmLowpOffsetContributionKernel. - Add virtual dequantize scale to gemm_common, only implemented for gemm_interleaved. - Update year to 2024 in generate_build_files. - Add dynamic flag to QuantizationInfo which signals to operators that it can change after configuration - Add support for dynamic quantization in NEGEMMLowpMatrixMultiplyCore - Add dynamic quantization fixture by extending GEMMLowpGenericMatrixMultiplyCoreValidationFixture - Add GEMMLowpDequantizedMatrixMultiplyValidationFixture - Store k (number of cols of A) rather than k_offset in the offset contribution kernels so that we can recompute it when the other offsets change relates to: ONCPUML-1444 MLINFSW-439 Co-authored-by: Milos Puzovic <Milos.Puzovic@arm.com> Co-authored-by: David Mansell <David.Mansell@arm.com> Change-Id: I58a3acf2c09289a303e52eea6b336a696a5bc8da Signed-off-by: Jonathan Deakin <jonathan.deakin@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11022 Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2024-03-21[ONCPUML-1451] Add matmul kernel to enable bf16 to bf16 operations via ↵Renato Arantes
PyTorch® autocast() function The full range of tests must be added with [MLINFSW-482] epic due to the lack of reordering kernels implemented in Acl. Co-Authored-By: David Mansell <David.Mansell@arm.com> Change-Id: I820d316295a1ec94fdc89c37e4144a268f914c36 Signed-off-by: Renato Arantes <renato.arantes@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11169 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>
2023-12-07Optimize CPU depth-to-spaceViet-Hoa Do
Resolves: COMPMID-6622 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Ibac276618bdda125dcbb9c851c547f12739b15b4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10749 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>
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>
2023-10-10Optimize NEStackLayerGunes Bayir
Optimize the stack operation in Cpu by leveraging block memcpy. Resolves: COMPMID-6498 Change-Id: I49d79d179f0375a73d654edd59fb33072112569b Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10451 Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-10-02Optimize CL and Neon Winograd testsGunes Bayir
Several test optimizations have been introduced into Winograd tests for Gpu and Cpu backends. The testing strategy has been detailed as a comment header in the test design files. In summary - Very large shapes in the nightly are made smaller - If the underlying kernel is the same for different data types, we only need to stress some key aspects of the kernels (e.g. read/write lengths in case of fp32/fp16). - In case the underlying kernel is the same (OpenCL), Fp16 is tested on a subset of the shapes - In Cpu, there is no need to test every combination for both NCHW and NHWC as we just permute the inputs and use NHWC kernels anyways - All activations does not need to be tested for each and every shape Resolves: COMPMID-6464 Change-Id: Ie25fded85c65b9c7386dc21b23f9b695b1e77b07 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10393 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: 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>
2023-09-27Implement tflite compliant reverse for CPUAdnan AlSinan
- Add support for negative axis values. - Add option to use opposite ACL convention for dimension addressing. - Add validation tests for the mentioned additions. Resolves COMPMID-6497 Change-Id: I9174b201c3adc070766cc6cffcbe4ec1fe5ec1c3 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10335 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-08-08Add support for S64 output in NEArgMinMaxLayerPablo Marquez Tello
* NEArgMinMaxLayer uses NEReductionOperation to compute its result in S32 * We need to call NECast to convert from S32 to S64 * Resolves MLCE-1089 Change-Id: I6fded869b6076d7af1b9b3e70eb384f4ee82fd8a Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10054 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@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>
2023-06-16Add Fused Activation to OpenCL MatMulMohammed Suhail Munshi
- Added fused activation to MatMul function interface - Added fused activation to CL backend - Includes tests for supported Activation Functions in MatMul Resolves: [COMPMID-6192] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Ie103212b600b60699eaf6a6394d609e6e1f5aba6 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/522465 Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9714 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: 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>
2023-06-09Reorder destructor in srcDavid Svantesson
Signed-off-by: David Svantesson <david.svantesson@arm.com> Change-Id: Iaed0933d665bd98829be49b9df11653d4d74081c Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9746 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-05-10Remove inclusion of NEReorderKernel header from NEReorderLayerRamy Elgammal
Resolves: COMPMID-6235 Change-Id: I7a094a23244286090415ee2788632cfa7bd6c037 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9608 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-05-05Connect CLMatMul function to quantized kernels and resolve NE BatchMatMul ↵Jakub Sujak
int_8 failures * Adapt the CLMatMul function and ClMatMul operator to use quantized kernels. * Add function-level tests. Resolves: COMPMID-5929 and COMPMID-5811 Change-Id: I5348cdcf07b8074c138e04dfef0a73399377accd Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9575 Reviewed-by: Mohmun02 <MohammedSuhail.Munshi@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-05-05Make NECast::validate take args by const pointerMatthew Bentham
Change-Id: I5d343e959942cb2ce48442d95d7c62aecd6a34d0 Signed-off-by: Matthew Bentham <Matthew.Bentham@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9573 Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-05-03Guards to make NEReorder aarch64 onlyDavid Svantesson
Resolves COMPMID-6151 Signed-off-by: David Svantesson <david.svantesson@arm.com> Change-Id: I0e8c957f3460633c32ef57be0cdc44a53b8c3e88 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9553 Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-04-28Reorder addedDavid Svantesson
Adds Reorder kernel exposing blocking reorders from arm_gemm Resolves ONCPUML-1232 Change-Id: I42bf4166311fe1771565134d3ed7039fc8e30230 Signed-off-by: David Svantesson <david.svantesson@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9500 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-04-28Fix the gather layer indices checkViet-Hoa Do
* If the index is out-of-bound, both CPU and GPU implementations of the gather layer will output 0. Resolves: COMPMID-5964 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Ib029b3acfb31452f2097c8c75448fb2697cfa332 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9487 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-04-13Implement MatMul Function and Operator with Floating Point support for CPUMohammed Suhail Munshi
- Implements MatMul function and operator for floating point datatype FP16/FP32 - Includes support for transposing dynamic tensors prior to matrix multiplication. - Adds tests for 2D/3D/4D+ tensors in MatMul with F32/F16 datatype (with all combinations of transposed/not-transposed tensors) - Updates fixture to allow for testing fused activation in MatMul - Adds tests for matmul with and without fused activation Resolved: [COMPMID-5898] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Iefa84b26dd723c9a51e6c3f91023152c6c31ace2 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9411 Reviewed-by: SiCong Li <sicong.li@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-03-30Add cropping support to NEBatchToSpaceSiCong Li
- Deprecate dynamic block shape interface - Iterate over output window instead of input window for simpler implementation and better performance - Add cropping support and cropping tests Resolves COMPMID-5918 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: Ifea0f5f7760ffd0f4d5d4f3a5ae8d14d0b98b790 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9378 Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-03-14Add CropInfo to BatchToSpace reference and fixtureSiCong Li
Partially resolves COMPMID-5918, COMPMID-5865 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: Ib3b01e7dc1c944184a4c038045bf0469fbb9ff45 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9321 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-03-03Add weights_info as optional input for NEDeconvolutionLayerAnnop Wongwathanarat
This is so that we can leverage fixed format kernel when using gemm convolution method. Partially resolves: [ONCPUML-1129] Change-Id: I61ffa74f5cd9d75579dbc1f9aa187371f855e932 Signed-off-by: Annop Wongwathanarat <annop.wongwathanarat@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9248 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-02-01Add new operator AddMulAdd for Neon™ backend for Float/Quantized typesGunes Bayir
This is a fused operator that merges Add + Mul + Add [+ Relu-based-Activation] layers and have an intermediate output after the first Add. It's supported for FP16/32/QASYMM8/QASYMM8_SIGNED data types. The subsequent Add and Mul are intended for scaling and the coefficients only have one dimension (per channel). The inputs are - input1 : nD tensor [X, Y, Z, W, ..] - input2 : nD tensor [X, Y, Z, W, ..] - add_coef : 1D tensor [X] - mul_coef : 1D tensor [X] The outputs are - out1 : nD tensor (intermediate output) [X, Y, Z, W, ..] - out2 : nD tensor (final output) [X, Y, Z, W, ..] The operation can be summarized as follows: out1 <- input1 + input2 out2 <- Act(out1 * mul_coef + add_coef) The activation function can be Identity, Relu, Bounded Relu or Lower/Upper Bounded Relu. The intermediate output can be skipped by providing a nullptr. The reason of providing this operator is to be able to fuse in case of Residual network patterns and save computations by reducing memory back and forward. Resolves: COMPMID-5463 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I8ef577aa623b036e9a9f655cc088493fd19a6109 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9055 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Tested-by: 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>
2023-01-30Skip upsampling for deconvolution when not neededAnnop Wongwathanarat
If the input tensor's stride is 1 and the kernel size is 1x1, skip upsampling step and pass the input tensor pointer for convolution directly. Partially resolve: [ONCPUML-1137] Change-Id: I9de9444ff99cf35d44a51ccbe0fa6facc1035d27 Signed-off-by: Annop Wongwathanarat <annop.wongwathanarat@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8994 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-01-20Add enable_fast_math for NEDeconvolutionLayerAnnop Wongwathanarat
Resolves: [ONCPUML-1128] Signed-off-by: Annop Wongwathanarat <annop.wongwathanarat@arm.com> Change-Id: I287a71222d3f0289d8cccfcb15383b0a930a55e6 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8952 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>
2023-01-18Add broadcast batched matmul validation casesSiCong Li
Related to: COMPMID-5660 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: I2314c8b21acc638402c77080d59db2f3fed58fe2 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8911 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Mohmun02 <MohammedSuhail.Munshi@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2022-12-21Optimize MeanReduce by integer acc. and removing upfront dequant.Omar Al Khatib
Resolves: [COMPMID-5466] Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Change-Id: I68af0bb54580bebd2ace1fba30aa73f7f68a4dbb Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8804 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2022-09-16Optimize Quantized/Integer Bilinear Scale for Neon™Gunes Bayir
This patch introduces several performance optimizations regarding the Bilinear Scale operator with REPLICATE Border mode. Changes apply only to NHWC. This patch - Reduces the memory footprint by disabling precomputation of indices and weights when they're not used - Rewrites the kernels for QASYMM8/QASYMM8_SIGNED/U8(Uint8) - Adds S8(Int8) Bilinear Scale for Border mode REPLICATE - Removes Bilinear Scale SVE kernels for Quantized and Integer types and adjust the heuristics to choose the Neon™ implementation - Adds new test cases where the input and output of the Bilinear Scale operator have different quantization scale and offset Resolves: COMPMID-5453, COMPMID-5454 Change-Id: I3d251e76e0c6978fd5a0a1795ec62ab536bec93c Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8250 Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@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>
2022-07-26Fix for inclusion of "arm_gemm" from src into "Types.h" from coreRamy Elgammal
- Added arm_compute::WeightFormat and converted to/from arm_gemm::WeightFormat when needed through two map function. - Moved to_string(WeightFormat) to TypePrinter.h Resolves: COMPMID-5415 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Change-Id: I65f7942100bcd4dbf2c5cf6c07f26c8e1e3bf86e Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/438511 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Pablo Tello <pablo.tello@arm.com> Reviewed-by: Sicong Li <sicong.li@arm.com> Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7985 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2022-07-19[ONCPUML-951] Variable weight support for Convolution.Francesco Petrogalli
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>
2022-07-14Integrate new winograd APIs from MLTechramelg01
Resolves: COMPMID-5400 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Change-Id: Ib4428436dd7a6e40d8b2d8a2f8dac1b079154551 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7894 Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2022-06-13Add support for 2d and 3d indices for axis 1Pablo Marquez Tello
* Resolves COMPMID-5055 Change-Id: I2d14de29d3ec913d20c971bc8bbc9ad71e2d998f Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7547 Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2022-04-13Add support for int8 CpuPool3dAdnan AlSinan
- Add implementation for the CPU pooling 3d layer. - NDHWC data layout support. - Support QASYMM8/QASYMM8_SIGNED. - Add Pooling helper file for Pool3d/2d common functions. Resolves COMPMID-4668 Change-Id: Iadf042036b076099c2353d6e2fe9fc623bc263d8 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7387 Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2022-04-01Add CPU Pool3d FP16/32 implementationAdnan AlSinan
- Add implementation for the CPU pooling 3d layer. - NDHWC data layout support - Support FP32/FP16. - Add Pool3d to the operator list. - Fix CL Pool3d kernel comments to generate the operator list. Resolves: COMPMID-4671 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I92478a154beb12541525b648ed3dd5a58c8f27fa Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7311 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Giorgio Arena <giorgio.arena@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> (cherry picked from commit 572659a0e5dd1086b1c7d16fe331ff73d2acd93a)
2022-03-29NEQLSTM: Add support for QASYMM8_SIGNED for input_to_forget_weightsPablo Marquez Tello
* QLSTM only supports QSYMM8 for the argument input_to_forget_weights * We add support for QASYMM8_SIGNED by dequantizing and requantizing to QSYMM8 * Resolves COMPMID-5184 Change-Id: I1cae18d81dafdb7ae722b520a1354cf4a56b9606 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7321 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> (cherry picked from commit 187a041dedf8e9db0c9e0652f13f8639dca880f3)
2022-02-14Port MaxUnpoolingLayer kernel and add KernelSelect vaidation testDana Zlotnik
Resolves COMPMID-4958 Change-Id: Ibed5155f2e3ece46635f6ea9617bf11cefc402b1 Signed-off-by: Dana Zlotnik <dana.zlotnik@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7028 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Giorgio Arena <giorgio.arena@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2022-02-09Remove deprecated remap functions.Adnan AlSinan
- Remove CLRemapKernel. - Remove NERemapKernel. Partially resolves COMPMID-4984 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: Ia61f9ac7447695d81178701cf0e9b7625a91eccc Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7056 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2021-12-25Add tests for FP Cpu Pooling where pool region is completely outside the inputSiCongLi
* Add floating point validation tests for this configuration * Fix reference implementation to return -inf for this configuration * Prohibit this config in Cl, as well as non-float cases in Cpu * Direct this config to non-asm path Resolves COMPMID-4998 Change-Id: If88025c51b14ea337aea2441c548f858e95e5819 Signed-off-by: SiCongLi <sicong.li@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6857 Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2021-10-22Add uint8/int8 support to cpu conv3dFreddie Liardet
Add support for qasymm8/qasymm8_signed in cpu conv3d. Resolves: COMPMID-4665 Signed-off-by: Freddie Liardet <frederick.liardet@arm.com> Change-Id: I2450bb6f24969745c8b936f4b657bd406b788c57 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6478 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Giorgio Arena <giorgio.arena@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2021-10-18DirectConv3d support refineSheri Zhang
- Decouple data support of CpuDirectConv3dKernel - Update documentation for Conv3d Signed-off-by: Sheri Zhang <sheri.zhang@arm.com> Change-Id: I1d94aa28f821f45a1a3d39cc3335c8faeee89f0d Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6453 Reviewed-by: Giorgio Arena <giorgio.arena@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2021-10-15Conv3d supportSheri Zhang
* Add CpuDirectConv3d support for fp32 and fp16 * Dilation is not supported * Need decouple Partially resolve: COMPMID-4661 Signed-off-by: Sheri Zhang <sheri.zhang@arm.com> Change-Id: Ib1865b9ff328b684d131512b1baf77bc2f10318f Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6430 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
2021-09-03List OpenCL kernels in Android.bp scriptMichele Di Giorgio
Also add NHWC as supported data layout for the ChannelShuffle operator. Change-Id: I8487d0dfd1fdbc6350ef8b902a23fac6ac83407d Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6204 Reviewed-by: Giorgio Arena <giorgio.arena@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2021-08-20Rename [Cl|Cpu]GemmConvolution to [Cl|Gpu]GemmConv2dGeorgios Pinitas
Renaming the gemm-based convolution operators to accomodate for new operators with higher convolution dimensonality Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com> Change-Id: Id2f2cf11404221f0e87baa0e5d08ad5d63eaf78e Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6113 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2021-08-04Remove 21.08 deprecated codeFreddie Liardet
Also correct some deprecation macros Signed-off-by: Freddie Liardet <frederick.liardet@arm.com> Change-Id: Ib28d42571f55d7b01563a0877b92b8f3128831ba Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6036 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2021-07-29Port NEConvolutionLayerMichalis Spyrou
Resolves: COMPMID-4507 Change-Id: I9557026ec0052b5585994f7a1300a14565c976d0 Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5964 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
2021-07-28Reduce binary footprint of CpuConvertFullyConnectedWeightsKernelMichele Di Giorgio
Binary size reduction for this kernel is almost 50%. Also remove unused NEConvertFullyConnectedWeightsManaged. Change-Id: Ia46a1342a0737397b4aac2578d963c2ebb7446e3 Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6011 Reviewed-by: Giorgio Arena <giorgio.arena@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2021-07-23Port NEFullyConnectedLayer to memory injecting interfaceMichele Di Giorgio
Resolves: COMPMID-4501 Change-Id: Ib61b3d06974009e501b3fb86467735427e13a94a Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5931 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-19 17:43:41 +0000