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* Changes in filelist.json: moved fp16 code from common to fp16
* Replaced the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
with ENABLE_FP16_KERNELS.
* Resolves COMPMID-6755
Change-Id: I4da1c53d3f9e4734e5e67125265ab4e3fc0dcbe4
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10865
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>
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* Both macros ARM_COMPUTE_ENABLE_FP16 and ENABLE_FP16_KERNELS
must be declared to enable FP16
* The failure was caused by not compiling the validation suite with the same
definitions used to compile the library. ARM_COMPUTE_ENABLE_FP16 was missing
and the call from the test into error_on_unsupported_cpu_fp16() failed.
* Resolves COMPMID-6727
Change-Id: I278c813aef799d9d0e21e5323b2b8e9e45252d6c
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10848
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>
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The graph example has fixed quantization information given for certain layers, and some of the offsets exceed the 8-bit range for Int8 data type.
This shouldn't have been the case and the offsets should respect the 8-bit quantization specification laid out here: https://www.tensorflow.org/lite/performance/quantization_spec
However, the mechanism added in the helper function introduces robustness in case of such irregularities with little/no cost; and therefore added as a fix.
Resolves: COMPMID-6748
Change-Id: If39bf323382f109fa100ee2b87ce63cc7bc89759
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10858
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>
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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>
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The function pointer for clImportMemoryARM should be loaded in a portable way as recommended by Khronos® as outlined here:
https://registry.khronos.org/OpenCL/specs/3.0-unified/html/OpenCL_Ext.html#getting-opencl-api-extension-function-pointers
using clGetExtensionFunctionAddressForPlatform() call.
All extensions should ideally be loaded using the above mentioned function.
Resolves: COMPMID-6732
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Change-Id: I482b6bde721267d5e8c08301e5780d28a9c5ba85
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10852
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>
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Resolves COMPMID-6736
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: Ib887c56afcf481366f1fa9c9f456a43c27269e52
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10844
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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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>
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This reverts commit ded5b182675e3166e947a8eb637b5b1e925816ab.
Resolves COMPMID-6735
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Change-Id: I9b69ca1ec80a671171d3f52081c4b8c61a676617
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10838
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: <felixjohnny.thomasmathibalan@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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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>
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* Resolves COMPMID-6733
Change-Id: I7f0428719b5c0aa79a0b356c50bb801db16558e8
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10792
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: <felixjohnny.thomasmathibalan@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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Resolves COMPMID-6734
Change-Id: I0f0a7a312504b7cca4ed36263843ccd1a190c09e
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10803
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Nikhil Raj Arm <nikhil.raj@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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* This is the initial patch to start working on enabling fp16 in all
multi_isa builds. More changes are required in the way we register
the kernels using the macro REGISTER_FP16_NEON.
* In this patch we add the capability to build the fp16 files in listed in
filelist.json with the correct arch option to enable FP16
* This patch is required towards building an universal multi_isa binary
where fp16 is enable.
* Enable REGISTER_FP16_NEON macro for all builds by removing
__ARM_FEATURE_FP16_VECTOR_ARITHMETIC guard from the macro definition.
The macro has to be used across all types of builds.
Change-Id: I99f4c273f6ee04cad3c097e5e374200f48568fa9
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10682
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>
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* Moved NCHW kernels fp16 and fp32 to their corresponding files
src/cpu/kernels/fuse_batch_normalization/nchw/neon/fp16.cpp and
src/cpu/kernels/fuse_batch_normalization/nchw/neon/fp32.cpp
* Changes in filelist.json to include the new fp16 and fp32 files
* Moved the template batch_normalization_nchw to impl.h as we
need to instantiate it from fp16.cpp and fp32.cpp
* Pooling layer: removed the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC that
prevented the FP16 kernel execution.
* Partially resolves MLCE-1102
Change-Id: Ia8c85e9ffb76c9e387f9ae2685e5df5e52c8dc27
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10777
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>
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Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>
Change-Id: I654f53e5b4e53abc69ce385f6c706293bf8f7198
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10784
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Tested-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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* Moved fp16 and fp32 to their corresponding files
src/cpu/kernels/mul/generic/neon/fp16.cpp and
src/cpu/kernels/mul/generic/neon/fp32.cpp
* Changes in filelist.json: added a new fp16.cpp file for the float16_t kernels
* Partially resolves MLCE-1102
Change-Id: I88f24cf034c11b55ff84644b182ba76c7cb94296
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10778
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
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Resolves ONCPUML-1331
This patch adds an option to make _custom_scheduler thread_local to
support usage of multiple schedulers handled outside of ACL.
It also adds num_threads() function to Scheduler which reverts to
querying CPUInfo if no scheduler has been set.
Change-Id: Iff706165d8d091895331a5bb3a76f6cabe048912
Signed-off-by: David Svantesson-Yeung <david.svantesson-yeung@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10748
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>
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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>
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* Moved the template arm_compute::normalize_float to impl.h because
we need to instantiate it from both NENormalizationLayerKernel.cpp
and src/cpu/kernels/norm_layer/generic/neon/fp16.cpp
* Changes in filelist.json: added a new fp16.cpp file for the float16_t kernels
* Replaced the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC in
NENormalizationLayerKernel by ARM_COMPUTE_ENABLE_FP16 so that
the fp16 kernels can be compiled in for multi_isa builds
* Moved fp32 kernels to the corresponding file
src/cpu/kernels/norm_layer/generic/neon/fp32.cpp
* Partially resolves MLCE-1102
Change-Id: I3f2eb2ed0b6c7f68092b17872b85082fbb5f39e2
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10739
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>
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Resolves COMPMID-6677
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: I99bf2385f6edc0836faacb31f5c66ed4fb051e40
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10729
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>
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* Performing the second pass in reverse order doesn't seem to work
reliably in some specific devices. This patch introduces
another approach to workaround the device issue.
Resolves: COMPMID-6669
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I591f05ff06f8439ebe4d32093441ae871a292f4c
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10730
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>
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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>
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Resolves COMPMID-6369
Signed-off-by: Anitha Raj <anitha.raj@arm.com>
Change-Id: I997a48c4e8efb67fbe53efd6fc498df4e6b41eea
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10726
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>
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Resolves COMPMID-6369
Change-Id: I67dd589cdc02070dafe6f000988e6abafd6c5d79
Signed-off-by: Anitha Raj <anitha.raj@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10722
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>
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Resolves COMPMID-6369`
Signed-off-by: Anitha Raj <anitha.raj@arm.com>
Change-Id: I2a3dc604895321f71198ece1dfed3af3a25c0228
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10724
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>
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Bypass importation of memory of the original weights into the
reinterpreted_weights auxiliary tensor if other weight transformation
path is selected (which would've freed the original weights and its
tensor info)
Resolves COMPMID-6635
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: Ib8a345c3ac542bc3745d6a67db822b55df37e827
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10698
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Anitha Raj <Anitha.Raj@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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Resolves: COMPMID-6633
Change-Id: I1e78df468876ec3569fa46597734e7de328b06f4
Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10663
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
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Change-Id: Ie68b0a19040cc6b5bf47fca406989f39aa8d7b81
Signed-off-by: David Mansell <David.Mansell@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10687
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>
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* Changes in filelist.json moving fp16 file from common to fp16 attribute
* Changes in kernel CpuPool2dAssemblyWrapperKernel, replaced
__ARM_FEATURE_FP16_VECTOR_ARITHMETIC by ENABLE_FP16_KERNELS to
make sure the fp16 kernels are compiled in for multi_isa=1
* Partially resolves MLCE-1102
Change-Id: I327154ec5b1ddfb9f54d9096f00c35b3e05c678a
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10662
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>
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* Changes in filelist.json moving fp16 file from common to fp16 attribute
* Removed the guard __ARM_FEATURE_FP16_VECTOR_ARITHMETIC in
CpuDepthwiseConv2dAssemblyWrapperKernel to always create the assembly
kernel
* Partially resolves MLCE-1102
Change-Id: I2f88d5e54a94042cfb3cb4ea0386338a7c444866
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10626
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>
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Resolves: COMPMID-6471
Change-Id: I5add2af4292ff2eeafcde85f3bff8e98b2069b13
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10660
Reviewed-by: SiCong Li <sicong.li@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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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>
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Resolves COMPMID-6479
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Change-Id: I13aa0ef944a75ba8b5e4df183d52df57b9aba90f
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10659
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>
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- 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>
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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>
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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>
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Resolves: COMPMID-6599
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: Id91185871f0dc30c08c7c38379acd5a3c1056473
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10575
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>
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* Fix SVE header being included in non-SVE file.
Resolves: COMPMID-6613
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: Ic7f662a239b761b83e67e11b6cc03f7d5f5cd051
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10573
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>
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- 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>
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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>
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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>
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- 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>
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Resolves: COMPMID-6493
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I038d91ba266e1e8bf124336bcd272ec77e92038c
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10490
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>
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* The new softmax implementation consists of only a single kernel.
- There are 2 versions of softmax, one for the x dimension
and one for any other dimensions.
- Softmax kernel handles both native and quantized data type.
Resolves: COMPMID-6447
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I4a9ae5bc63f78aebeaa85ee48a0d102c9c245eda
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10489
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>
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* FP16 kernels must be instantiated in fp16.cpp.
* Partially resolves MLCE-1102
Change-Id: Iab9c29dbfd89358f2f663862ff5010c88aeccf8c
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10496
Reviewed-by: Anitha Raj <Anitha.Raj@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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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>
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Resolves: COMPMID-6397
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: Id4404f75dae03fd529db1adac5ab9ca48d08ec46
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10498
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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* FP16 kernels must be instantiated in fp16.cpp.
* Partially resolves MLCE-1102
Change-Id: Ie652203876a0ac12b025e96d20990b6efb21e772
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10477
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>
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Signed-off-by: David Mansell <David.Mansell@arm.com>
Change-Id: If02f7809f9b6e84979121698c5e7a62cbb41e2c3
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10487
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>
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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>
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This reverts commit aeced744b854758768243833bcdf999c0c3c1a5b.
Reason for revert: Incorrect SME architecture checks.
Change-Id: I23fe78178041a544a8791a4655bf6fe4aa375e38
Signed-off-by: David Mansell <David.Mansell@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10501
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>
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