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2024-01-04Implement dynamic quantization for GEMMLowp testsSiCong Li
This patch calculates the output quantization info based on the inputs' quantization information. The previous approach was using the same quantization information for input, weights and output. Remove QSYMM8_PER_CHANNEL path from the fixture as there are no related tests Remove repeated shapes from the dataset now that we get rid of the quantization info from the dataset. Combine signed and unsigned SmallGEMMLowpFusedBatchedMatMulDataset into one as they become identical Resolves COMPMID-6481, COMPMID-6634 Change-Id: I9f5a20f4bb45c3e5adab388564135ae8a5c0a9ea Signed-off-by: SiCong Li <sicong.li@arm.com> Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10680 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-12-08Adjust NEReduceMean test toleranceSiCong Li
Resolves COMPMID-6728 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: Ic0682550a09db9aa420057a90ee65386e16e6034 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10853 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>
2023-12-05Optimize CpuSoftmaxKernel for axis=0Gunes Bayir
Implement a single kernel instead of having two consecutive ones. In the previous setup, one kernel was calculating the maximum value in the axis, and this maximum was being subtracted from each data while calculating the softmax, i.e. softmax(x_i) = exp(x_i - max) / sum_i( exp(x_i - max) ) This patch integrates these two stages into a single kernel for Neon™ for all data types. This will save some memory because we don't need to hold the max values in a separate auxiliary tensor. It also introduces some other optimizations that will ease memory pressure when the data type is float/half, by using the dst tensor as temporary storage for already exponentiated inputs. It removes the references to SVE and SVE2 implementations, and most of the associated files; but, it leaves the implementations as these may be used in the future. Resolves: COMPMID-6500 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: Icff9976d1214c4c6cbe15a62ca60b8a77d3784cc Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10688 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>
2023-11-08Optimize 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>
2023-11-03Add Dynamic Quantization tests to Fully Connected LayerMohammed Suhail Munshi
This patch calculates the output quantization info based on the inputs' quantization information. The previous approach was using the same quantization information for input, weights and output. This implementation does not cover the cases where we have fused activation function. Resolves: [COMPMID-6484] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Ib58143165191e82ae8547e661ac7c8d077bda200 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10539 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>
2023-10-31Use dynamic quantization in Convolution and Dilated Convolution testsGunes Bayir
This patch calculates the output quantization info based on the inputs' quantization information. The previous approach was using the same quantization information for input, weights and output. This implementation does not cover the cases where we have fused activation function. Resolves: COMPMID-6482 Change-Id: I4a9d87cfef8ad18ef241d457d23f44c8519a1389 Signed-off-by: SiCong Li <sicong.li@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10541 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>
2023-10-17Fix memory Error in Reverse Fixture.Adnan AlSinan
Resolves: COMPMID-6581 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I0a634e064377e54b9190241c01fc75c212522ba7 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10481 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>
2023-10-10Optimize 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>
2023-10-10Optimize CL and Neon depthwise convolution testsGunes Bayir
Resolves: COMPMID-6465 Change-Id: I5bbf4596dd5e34e806dc51de9be14df9b6fa320a Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10452 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-10-04NEDeconvolutionLayer validation fixPablo Marquez Tello
* Added a new test to make sure we support the following configuration: NCHW InputInfo=Shape=2,2 WeightsInfo=Shape=3,3 OutputInfo=Shape=4,4, PadStrideInfo=1,1;0,0,0,0' * Fixed the validate() method to allow this configuration * Resolves MLCE-1120 Change-Id: I6874ad57bb81384185984741b983bf5e19ba150c Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10417 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>
2023-10-02Optimize 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>
2023-09-27Implement 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>
2023-09-15Remove deprecated support for BF16 in CpuCastAdnan AlSinan
Resolves : [COMPMID-6212] Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I29bbd9a3d96af462faf7f0ee13b9849f75e05356 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10319 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
2023-09-04Make zip and combine variadicViet-Hoa Do
* Illustrate the benefit by writing CPU MatMul test dataset in a more readable way. Part of: COMPMID-6353 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Id5dbc13a051709237bbcc4dd88716d0b24ecfd5d Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10227 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-08-30Disable NEArgMinMaxLayer RunSmall_F32_S64 for armv7aPablo Marquez Tello
* When the output is S64 the function NEArgMinMaxLayer uses CpuCast to convert the output to S64 and this is only supported on aarch64. * Disable this test case for non aarch64 builds * Resolves COMPMID-6536 Change-Id: I554c21ce9a029af086e9137b5369b7951b779997 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10212 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-08-22Optimize CpuReshapeKernelAnitha Raj
Resolves COMPMID-5279 Change-Id: Id9b007eed62c200702bbfcc83b94dab7b5de1714 Signed-off-by: Anitha Raj <anitha.raj@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9962 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@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>
2023-08-08Fix failure in MeanReduce layerViet-Hoa Do
Resolves: COMPMID-6423 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I9cec051a7d1a2956218f8a6d8263bd5424f6d389 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10072 Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-08-01Improved testing for ArgMinMaxPablo Marquez Tello
* ArgMinMax output was fixed to S32, this patch makes the changes required to allow other output types like U64/S64 * Made changes to the ArgMinMax fixture and tests to allow specifying output data type. * Made changes to the reference reduction_operation to allow specifying the output type * Added tests case to output S64 for the CL backend. * Added missing test cases in the neon backend. * Partially resolves MLCE-1089 Change-Id: I6f1cbc7093669d12c2a3aff6974cf19d83b2ecda Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10003 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>
2023-07-19Add support for input S64/U64 in CpuCastKernelPablo Marquez Tello
* The kernel now supports the following conversions: S64 -> F32 U64 -> F32 * Resolves MLCE-1089 Change-Id: I277cf58b78d919fde25947520d2056e1412c7f82 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9935 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>
2023-07-18Break up core/Utils.h to reduce unused code being included everywhereMatthew Bentham
Makes a small difference to compile times and opens up other opportunities to simplify code. Change-Id: I232876910bbe4fa9719f4a0ce4a54c090faeb5ef Signed-off-by: Matthew Bentham <Matthew.Bentham@arm.com> Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/532429 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Pablo Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9856 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-07-07Enable transpose convolution with non-square kernelsViet-Hoa Do
Resolves: COMPMID-6319 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I49a17ff973efc88b7ce0334c47ecf076c03f4cc3 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9829 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>
2023-06-12Refactor activation LUT computationPablo Marquez Tello
* Moving the code out of Types.h will help with the compilation time. * Added LUT support for all other activation functions. * Resolves COMPMID-6292 Change-Id: I1b5f0b21f03237447163276b8796b2aeb3fdd45c Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9749 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-05-15Raise tolerance number for NEDeconvolutionLayer fp16 testsSiCong Li
Tolerance number was too strict for fp16 Resolves COMPMID-6254 Signed-off-by: SiCong Li <sicong.li@arm.com> Change-Id: I42a5df21c2545c38ea7234497effd232b43aabf8 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9635 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Omar Al Khatib <omar.alkhatib@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: 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>
2023-05-10Fix validation issue with CPU scale on FP16Viet-Hoa Do
* In multi-isa build with v8a base arch, FP16 is only available in SVE kernels, hence the support for FP16 depends on runtime environment. * To simplify the test, the data type test is disable on FP16 if the base arch doesn't have FP16 support. Resolves: COMPMID-6232 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Iee6179e1b87d3e7f4349e228479ff170285e4841 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9599 Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: 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>
2023-04-26Only define validation test tolerance for quantized types in case of aarch64 ↵Ramy Elgammal
for Neon™ Matmul Partially Resovles: COMPMID-6026 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Change-Id: I273b213abba275f1609eae33058e3acbee2a7146 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9489 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>
2023-04-24Disable Neon/MatMul/Quantized for armv7aRamy Elgammal
- All the GeMM CPU assembly kernels for integer datatypes require aarch64 Resolves: COMPMID-6026 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Change-Id: I34bb0d5ca5cc3684b996df851227fcd0ad452586 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9481 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Mohmun02 <MohammedSuhail.Munshi@arm.com>
2023-04-19Add quantized support for CPU MatMulViet-Hoa Do
Resolves: COMPMID-5899 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I89d96e292c3492ba9b1900a3e5683f9dcd11dfc6 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9440 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>
2023-04-17Fix unhandled case in ElementwiseUnaryRamy Elgammal
- Case: when the dequantized float value < 0.f the unary op was not called if operator is not LOG or RSQRT Resolves: COMPMID-5994 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Change-Id: I24d69db22042701f506188ace91ea4ab3dafeccf Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9437 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
2023-04-14Fix dynamic weights for CPU connected layerViet-Hoa Do
Resolves: COMPMID-5995 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I707b8918bebee7e70d4de5207ef555c806e7a305 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9405 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-04-13Increase tolerance for SME kernelsViet-Hoa Do
Resolves: COMPMID-5904 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I03bc51a7c5b05cca5db16a39f95e92d72240ab3a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9420 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@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>
2023-04-11Enable quantized data types for CpuElementwiseUnary on Armv7aRamy Elgammal
- Adding fallback functions neon_qasymm8_signed_elementwise_unary() and neon_qasymm8_elementwise_unary() - They would be called in case target is not aarch64 Resolves: COMPMID-5994 Change-Id: Id0db1e7cb0fe92f1eaef0b3a9ed2bea01b3f2a15 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9416 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>
2023-03-30Add 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>
2023-03-29Fix GCC13 compiler errorsPablo Marquez Tello
* Removed namespace arm_compute::utils::requires to fix the build error ‘requires’ is a keyword in C++20 [-Wc++20-compat] * Added missing includes for cstdint.h * Resolves MLCE-1040 Change-Id: I08842a273a4422f8e9b10daded680f521efe26e0 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9388 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-03-29Add additional FP16 guards to Convolution LayerNathan John Sircombe
Adds additional ARM_COMPUTE_ENABLE_FP16 guards to Convolution layer testing to ensure that validation suite passes on armv8a hardware when built with arch=armv8a, and multi_isa=0. Partially resolves ONCPUML-1209 Change-Id: Ib485502e534df1fa91c5c2d7b222ea08a354cc54 Signed-off-by: Nathan John Sircombe <nathan.sircombe@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9383 Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-03-29Add quantized support for unary elementwise in CPUViet-Hoa Do
* Add quantized unary elementwise in CPU using LUT. * Widen the input data range of the test suite. - Fix CPU exponential function overflow/underflow range. - Fix saturation issue of CL round operator. Resolves: COMPMID-5763 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I41445de2b4a33ec6b01e0ab701516c240c852d0b Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9367 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-03-21Add 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>
2023-03-01Add support for kernel indices in MaxpoolAdnan AlSinan
- Add a max pooling implementation that returns kernel indices. - Add a parameter in pooling info object to pick kernel indices impl. - Add validation tests. Resolves: [ONCPUML-1187] Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I485ef1604f676ee14d5f7f62d33699e49c38e4d3 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9192 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>
2023-02-24Fixes for CMake and Bazel builds, tests failing in sconsDavid Svantesson
- Fix 4 failing tests for multi_isa builds when experimental_fixed_format_kernels=1 - Fixes for CMake and Bazel builds to pass validation tests - Update documentation, remove “-DCPPTHREADS=1” flag from CMake build example Partially resolves: ONCPUML-1181 Signed-off-by: David Svantesson <david.svantesson@arm.com> Change-Id: I7101676260a0adcb7b6ff6f4342ae36f921e7120 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9189 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>
2023-02-10Fix DeconvolutionLayer tolerance issues in FP16 testsGunes Bayir
This patch increases the tolerance value used for FP16 tests in Neon(TM) backend. The tolerance number means 0.01f means it is ok to have 1% mismatch in the resulting tensor between the reference and the target. The value adopts a slightly stricter threshold compared to ConvolutionLayer (which is currently at 7%). This increase makes sense because Deconvolution layer uses convolution under the hood. Resolves: COMPMID-5841 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: Ie0ebf5cce1e9753dc641a947d84128dd6da402d4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9120 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-by: Sang Won Ha Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-02-03Disable AddMulAdd armv7a testsGunes Bayir
The AddMulAdd assembly kernels only support aarch64. This patch disables the tests associated in case the build is not for aarch64. Resolves: COMPMID-5850 Change-Id: Ib2768fd6bf2497420ff224daa243027d0a69c76b Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9076 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2023-02-01Fix GEMMLowp/Batched MatMul mismatches on CPUMohammed Suhail Munshi
- Fixes Column Offset matrix is not being iterated through in y dimension Resolves : COMPMID-5795 Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I0190474be404b4f0e171855739cfd0a48cbed5bc Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9020 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-by: SiCong Li <sicong.li@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>
2023-01-17Fix ClGemm crashes on unsupported data typesSiCong Li
Resolves COMPMID-5814 Change-Id: I09b206374cf3844c09aebd3c664daec9c2335e6d Signed-off-by: SiCong Li <sicong.li@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8953 Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-01-11Deprecated BF16 support in DepthConvertPablo Marquez Tello
* Removed BF16 validation tests for DepthConvert * Revert back to using inline assembly to convert to/from BF16 * Resolves COMPMID-5800 Change-Id: I803b2ad19ead297417f780c97c5b724cca6b394c Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8929 Reviewed-by: Jakub Sujak <jakub.sujak@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> Tested-by: Arm Jenkins <bsgcomp@arm.com>
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-01 06:32:11 +0000