ComputeLibrary.git -

Age	Commit message (Collapse)	Author
2023-07-11	Add Bias to MatMul Kernels and add support for use in Fully Connected Layer	Mohammed Suhail Munshi
	Resolves: [COMPMID-6316] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I08e6bac9e6b46b76978da0dc6a48ccfe3dde5086 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9833 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>
2023-07-06	Fix nightly failures in MatMulLowpNativeKernel when using bounded activation ↵	Mohammed Suhail Munshi
	functions - Added checks for supported activation functions in MatMulLowpKernel validate - Replaced incorrect float activation macro with quantized implementation in mat_mul_quantized Resolves: [COMPMID-6339] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: I15661f14877f1d3305644e6473feb5482a67e773 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/532858 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Pablo Tello <pablo.tello@arm.com> Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9855 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>
2023-06-26	Use MatMul in fully connected layer with dynamic weights when supported	Mohammed Suhail Munshi
	- Use MatMul kernels in FC layer when using dynamic weights without broadcasting or bias. - Fix minor typo in IClMatMulNativeKernelConfig.h Partially Resolves : [COMPMID-6193] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Id494062b5b4f4e75ff9714c202dde941955afa52 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9797 Tested-by: Arm Jenkins <bsgcomp@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-06-16	Add Fused Activation to OpenCL MatMul	Mohammed Suhail Munshi
	- Added fused activation to MatMul function interface - Added fused activation to CL backend - Includes tests for supported Activation Functions in MatMul Resolves: [COMPMID-6192] Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com> Change-Id: Ie103212b600b60699eaf6a6394d609e6e1f5aba6 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/522465 Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com> Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9714 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
2023-04-27	Add quantized CL MatMul kernel for LHS NT, RHS T	Jakub Sujak
	Implement a native kernel for batched Matrix Multiplication for the quantized data types QASYMM8 and QASYMM8_SIGNED and with the MatMul attributes `adj_x = false, adj_y = true`. Resolves: COMPMID-5923 Change-Id: I477b2dd886edfe83beaba9efc7d6b05ed19f5da4 Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9467 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>
2023-04-20	Implement CL kernel for a native batched matmul Quantized - LHS transposed, ↵	Omar Al Khatib
	RHS transposed Resolves: [COMPMID-5924] Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Change-Id: I9ba657737eb1e3a096c8341ad4ad311571f8edeb Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9454 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>
2023-04-17	Add quantized CL MatMul kernels for Lhs NT/T, Rhs NT	Gunes Bayir
	Implement OpenCL kernels for batched Matrix Multiplication for the quantized data types QASYMM8 and QASYMM8_SIGNED. Quantized MatMul is supported with the following MatMul attributes: * adj_x = false, adj_y = false * adj_x = true, adj_y = false We consider native format kernels only. In other words, no reshaping of the operand matrices is done. Resolves: COMPMID-5921, COMPMID-5922 Change-Id: I99e0f68054a2bd635c60ec2641acc2e7ff398473 Signed-off-by: Omar Al Khatib <omar.alkhatib@arm.com> Signed-off-by: Gunes Bayir <gunes.bayir@arm.com> Signed-off-by: Jakub Sujak <jakub.sujak@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9435 Reviewed-by: SiCong Li <sicong.li@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> Benchmark: Arm Jenkins <bsgcomp@arm.com>