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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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Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.
Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/
There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
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- Added fused activation to MatMul function interface
- Added fused activation to CL backend
- Includes tests for supported Activation Functions in MatMul
Resolves: [COMPMID-6192]
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: Ie103212b600b60699eaf6a6394d609e6e1f5aba6
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/522465
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9714
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
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int_8 failures
* Adapt the CLMatMul function and ClMatMul operator to use quantized kernels.
* Add function-level tests.
Resolves: COMPMID-5929 and COMPMID-5811
Change-Id: I5348cdcf07b8074c138e04dfef0a73399377accd
Signed-off-by: Jakub Sujak <jakub.sujak@arm.com>
Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9575
Reviewed-by: Mohmun02 <MohammedSuhail.Munshi@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
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- 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>
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