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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>
2024-03-20Make Cpu/Gpu/Ref scalar/vectoral S32 division consistentGunes Bayir
- Neon(TM) implementation converts integers to float and performs the division because there is no vector integer division instructions. However, leftover loop still uses integer division, which makes results inconsistent depending on where we are in the tensor. - SVE path does it in integer domain. - OpenCL(TM) does it similar to Neon(TM) vector path. - Reference implementation does it in integer domain. These differences cause intermittent mismatches. This patch ensures all follow the same logic. On the other hand, the provided Neon(TM) implementation is faster than the Fp32 converted version. Resolves: COMPMID-6925 Change-Id: Ia12606d57f40a7d331b9b698f87fd4321496b275 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11316 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>
2024-03-20Increase tolerance_num of Cpu RNNLayer testsGunes Bayir
Instead of increasing the tolerance amount, we increase the number of elements we tolerate to 0.02 % of the whole tensor. This ensures we do not affect the tolerance for smaller tests. This amount is set according to the number of elements above the threshold. it was 1 over 512 elements, 1/512 ~ 0.02 %. Resolves: COMPMID-6932 Change-Id: I9d3ce29a3972aa8b9daea5288005a0a41a266328 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11321 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2024-03-19Increase MatMul and DilatedConv test Q8 thresholds to 1Gunes Bayir
Tolerance for quantized tests is better to be 1 due to possible rounding differences between the Acl and reference implementations. Resolves: COMPMID-6929 Change-Id: I6f317631322b702e6a9579593befff65bbf46151 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11319 Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2024-03-14Fix validation in pool2d assembly wrapperPablo Marquez Tello
* Validate output shape in CpuPool2dAssemblyWrapperKernel * Resolves ARMCL-625 Change-Id: I4fd91c1b15ecb17efc39fd3e82a92210e4f182b2 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11290 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>
2024-03-11Prefer indirect Gemm vs. Direct convolution if supportedGunes Bayir
Indirect GEMM uses optimized assembly path while Direct Conv uses the fallback Acl kernel for convolution. In certain cases, where the input tensor is large and filter size is greater than 7 (e.g. 9x9 filters), heuristics fall back to Direct Conv algorithm where it could still prefer the assembly path if the data layout is NHWC. This is more important when SME2 kernels are present. Resolves: COMPMID-6900 Change-Id: Ia611c975eee0423615113fcaeaa8f9eef0421456 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11254 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Anitha Raj <Anitha.Raj@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2024-03-11Set int8 test tolerance in FullyConnected to int8Gunes Bayir
Int8 data types should be compared with Int8 tolerances. Same holds for UInt8 as well. O/w the differences between reference and target can be larger than it is because of casting. Resolves: COMPMID-6930 Change-Id: I4940d821b7fecc21cf6b167e161dffceb764b909 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11269 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: <felixjohnny.thomasmathibalan@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2024-02-20Requantization cases for offset changes onlyMohammed Suhail Munshi
Resolves: [COMPMID-6681] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I325b9d478dd1d04a45533bb7708cf76e98ee0cee Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11058 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>
2024-02-15Fix linker errors in validation suite for WoAPablo Marquez Tello
* Cleaned up the ActivationLayerFixture and removed the context becuase it was causing compiler errors with clang-cl * The runtime context is an experimental feature that is only tested in the ActivationLayerFixture and not used anywhere else in the codebase * Resolves MLCE-1209 Change-Id: Id0ca71d60e78772dccbd02db407f87c94a087eb1 Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11145 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>
2024-02-15Fix validation suite on WoAPablo Marquez Tello
* The missing parser option caused a segfault in the validation tests. * Resolves MLCE-1209 Change-Id: I59621241bb66f300c0c581741727f3abf0dbe43e Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11139 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2024-02-14[QTest] Use dynamic output quantization in Depthwise Conv testsOmar Al Khatib
Resolves: COMPMID-6483 Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Change-Id: I512102f5e27743098168101b5e02382f4ad4a22a Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11068 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>
2024-02-12Disable some DirectConv2d tests in Dynamic FusionGunes Bayir
There is a potential implementation issue in DirectConv2d CKW kernel. It's been revealed when we moved from template writer to compute kernel writer. This patch disables the offending tests. It also disables tests for an unimplemented operator. Relates to: COMPMID-6715 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I40e6256cf377ebf8b1c0d0d0c4788de19ec410e4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11123 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>
2024-02-09Add support for QSYMM8 in ClCastKernelPablo Marquez Tello
* Resolves ARMCL-1123 Change-Id: I4f8432ba41fa50bf787fb068c3672ac06b858bdd Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11117 Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2024-02-09Remove CKW prototype and Template WriterGunes Bayir
Gpu code in dynamic fusion is now written by stable CKW. We do not need CKW protoype and the older writer implementation, i.e. TemplateWriter. It also removes the need for the flag -DACL_INTERNAL_TEST_CKW_IN_DF to compile and test dynamic fusion operator. Resolves: COMPMID-6715 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I9f9453311e79d9be612bd4754240d832f98503e8 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11116 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2024-02-08Fix the bug in GpuTanh operator in dynamic fusionGunes Bayir
Tanh in dynamic fusion is a simple operator with no A and B coefficients, as its public interface implies. Tanh operator follows the TOSA specification. Customization of tanh calculation with a and b can be achieved via fusion as below: out = a * tanh(b *in) --> x = b * in y = tanh(x) out = a * y; Resolves: COMPMID-6873 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I818765192f631ae82c2094b0fc376fb87bae4fa4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11109 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>
2024-02-06Disable FP16 tests compilation on Multi-Isa v8aMohammed Suhail Munshi
Resolves: [COMPMID-6791] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Idae6ddb0e9655ec096f25917f0a44eb57aaef908 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11076 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
2024-02-01Use the stable CKW API in the GPU dynamic fusion backendGunes Bayir
- Refactor all kernels to work with the CKW stable API - Add support for sub-tile in the op_load/op_store CKW operator - Fix mismatch in resize - Add comments in all kernels written with CKW to help developers understand the structure of the code - Add texture image support in depthwise convolution written with CKW - Add support for different block sizes in depthwise convolution - Remove the use of the dynamic fusion helper functions. - Add support for floor in the op_unary() of CKW Resolves: COMPMID-6708, COMPMID-6743, COMPMID-6530 Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Change-Id: I8104ce4d04a3138a1aeb0b84940e1f1c89e76069 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10914 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2024-01-24Fix tolerance issue in BF16 MatMul testsGunes Bayir
BF16 kernels are not expected to have the same tolerance/accuracy standards as full float kernels. The reference implementation is a standard floating point implementation, thus resulting in small mismatches. We increase the tolerance of the MatMul BF16 tests, and add more tests to cover more shapes. Previously, the only tested bf16 kernel was a64_hybrid_fp32bf16fp32_mmla_4x24. With the inclusion of new shapes, heuristics also choose a64_hybrid_fp32bf16fp32_mmla_6x16 and stress this kernel as well, covering every implementation. Resolves: COMPMID-6654 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Change-Id: I15342606912013c123b94c7e0ea2e6bbb25680d7 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11014 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
2024-01-23Make GpuWorkloadContext own all tensor info objectsViet-Hoa Do
* The tensor info objects created by calling create_tensor_info is now solely owned by the context object. The user only receives pointers to those objects. - Internally pointers to tensor info objects are used in various places. It's safer for dynamic fusion to manage these objects directly rather than relying on the users. - The validation test is updated to use the modified API. * Make various changes in dynamic fusion API to make it more friendly (e.g. making some of the objects moveable). Partially resolves: COMPMID-6707 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: Ifee70e53c05f8e7b72bf9ef123701ff291c5ee80 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10990 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>
2024-01-11Fix test compilation error on GCC 13.2Jakub Sujak
Remove a std::move flagged by -Wpessimizing-move Resolves: COMPMID-6777 Change-Id: Ie082dc2eab0cb11e9a29f6f6fc98866306fd2cfa Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10957 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@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>
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>
2023-12-22Add Mali™-G720 and Mali™-G620 as GpuTargetsGunes Bayir
This patch adds adds the latest Gpus as Gpu Target and sets up kernel selection heuristics for MatMul to address some nightly issues. Resolves: COMPMID-6766 Change-Id: I29dbb08c5ecfb3fcd63230b0b1675ab557074aca Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10902 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-12-14Fix Run Example in Validate TestsMohammed Suhail Munshi
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Icee8b38db1f219d66ac22a6e0980f4325fd21fbd Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10868 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: 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>
2023-11-23Remove the legacy core libraryJakub Sujak
Stop building and linking to the legacy libarm_compute_core artifact. This library is an artifact of Compute Library's legacy library architecture and no longer serves any purpose. Users should link only to the main libarm_compute library for core functionality. Resolves: COMPMID-6329 Change-Id: Ife9d2c25d275e7c676deb09632ae461f697efde9 Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10728 Reviewed-by: Anitha Raj <Anitha.Raj@arm.com> Reviewed-by: Sang Won Ha <sangwon.ha@arm.com> Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-11-14Update comments to suppress doxygen warnings.Anitha Raj
Resolved COMPMID-6367 Signed-off-by: Anitha Raj <anitha.raj@arm.com> Change-Id: I96f244811a81a4e278f0c5e47d5014229cad3a25 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10727 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: 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>
2023-11-06Fix Elementwise Division Dynamic Shape testsAnitha Raj
- Enable use_dynamic_shape ArithmeticDivisionDynamicShapeValidationFixture Signed-off-by: Anitha Raj <anitha.raj@arm.com> Change-Id: I42ddf5b604d728eda91fa45b239abf8caf2cda0f Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10586 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: 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>
2023-11-01Increase tolerance for MatMul in FP16Sangwon Ha
Resolves: COMPMID-6585 Change-Id: Ibfc5412ab23f10026c872eab99a056eb682d77a1 Signed-off-by: Sangwon Ha <sangwon.ha@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10577 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-10-31[GPU] Update Reverse layer to allow negative axis and reversed axis orderAdnan AlSinan
- Adds option to use negative axis and inverted axis. - Adds validation tests for the above. Resolves COMPMID-6459 Change-Id: I88afd845d078f92c82ec8529ce7241fccd4c417e Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10523 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-10-31Fix clang-tidy errorsJakub Sujak
Resolve the following clang-tidy errors: * use of undeclared identifier 'ARM_COMPUTE_ASSERT' * no template named 'AbsoluteTolerance' * no template named 'RelativeTolerance' These errors are a result of missing include headers in test fixtures. Resolves: COMPMID-6604 Change-Id: I8058c5848bb52a44925b2f99c9e8edf84dc79acc Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10561 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>
2023-10-31Use 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>
2023-10-31Extend CKW MatMul with nt_tAdnan AlSinan
- Add the kernel variant: (nt_t) to GpuCKWMatMul. - Extend CKW MatMul validation test with nt_t. - Fixes a bug in CKW where z-dim = 1. Resolves: COMPMID-6435 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I4c5e8791e55f21ffff3c11eca7802c51a4259977 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10525 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-10-30Use dynamic quantization in OpenCL™ Direct 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. Note that no Neon™ tests are changed since there were not any quantized Neon Direct Convolution tests. Resolves: COMPMID-6485 Change-Id: Id32241320acae0b58552546d6d6f665cd5c63044 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10470 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@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>
2023-10-12Remove padding from CL comparison operatorViet-Hoa Do
* Add support for processing left-over vector to comparison kernel. * Combine native and quantized versions of CL comparison. Resolves: COMPMID-6424 Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com> Change-Id: I31d43bdf0eab999cee6fa8144b5d8e921a1093e8 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10467 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: 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 CLDeconvolutionLayer testsGunes Bayir
Resolves: COMPMID-6466 Change-Id: I916871c9d7880107985337782e2cfd280a62cdeb Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10458 Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: 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>
2023-10-05Optimize CLTranspose operatorJakub Sujak
* Transpose higher dimensional tensors (>2D) by collapsing higher dimensions into the third dimension thus avoiding multiple dispatches of the CL kernel * Maximize tile size without register spilling Resolves: COMPMID-6448 Change-Id: Iac094b8c428bdf319d9c28a8334cb55d58e2d14b Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10443 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>
2023-10-05Change MatMul Native MMUL Kernel tests tolerance valueAdnan AlSinan
- Resolves COMPMID-6560 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I5778a0d620bed3fea05d868c0a775fbaa6dcc9dd Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10442 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>
2023-10-04Port DepthwiseConv2d operator to Ckwramy.elgammal@arm.com
- Only support 1x1 blocks, i.e. n0=1, m0=1. - Dilation not supported yet. Resolves: COMPMID-6258 Signed-off-by: ramy.elgammal@arm.com <ramy.elgammal@arm.com> Change-Id: I1dcfd7640fb40e112736dedc81847f7b1b50dba2 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10411 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: 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>
2023-10-03Fix nightly NEON Reverse reference failureAdnan AlSinan
- Fix the reference axis vector to be the right size. - Update typos in the error messages. Resolves COMPMID-6574 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I9572365b8173b92d0fffd557e4db261b2969109c Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10423 Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com>
2023-10-03Fix MacOS compilation errorJakub Sujak
The linker option '-noall_load' is obsolete. Resolves: COMPMID-6578 Change-Id: I2d386c25b50705a25600dd612406470e1d3871be Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10421 Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
2023-10-02Fix Nightly failing validation tests in NEON ReverseAdnan AlSinan
Resolves COMPMID-6574 Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com> Change-Id: I6b23e2a2f7b2839f038dad538dfc5ebda62891a6 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10412 Benchmark: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Anitha Raj <Anitha.Raj@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>
2023-09-29Implement Quantized Matmul T/T and T/Nt kernels using MMUL extensionGunes Bayir
Resolves: COMPMID-6476, COMPMID-6477 Change-Id: Ied37c269d5a108ff72f70e3ad932cf372bda5562 Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10346 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>
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-03 00:18:33 +0000