Add Fused Activation to OpenCL MatMul

- 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>

1 files changed, 8 insertions, 8 deletions

diff --git a/src/gpu/cl/operators/ClMatMul.cpp b/src/gpu/cl/operators/ClMatMul.cpp
index 3822c16aa1..c453761a8e 100644
--- a/src/gpu/cl/operators/ClMatMul.cpp
+++ b/src/gpu/cl/operators/ClMatMul.cpp
@@ -47,7 +47,7 @@ ClMatMul::ClMatMul()
 {
 }
 
-Status ClMatMul::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulInfo &matmul_info)
+Status ClMatMul::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulInfo &matmul_info, const ActivationLayerInfo &act_info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
@@ -57,15 +57,15 @@ Status ClMatMul::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const
 
     std::unique_ptr<IClMatMulNativeKernelConfig> t = ClMatMulNativeKernelConfigurationFactory::create(gpu_target);
 
-    MatMulKernelInfo kernel_info = t->configure(lhs, rhs, matmul_info);
+    const MatMulKernelInfo kernel_info = t->configure(lhs, rhs, matmul_info);
 
-    bool is_quantized = is_data_type_quantized_asymmetric(lhs->data_type());
+    const bool is_quantized = is_data_type_quantized_asymmetric(lhs->data_type());
 
-    return is_quantized ? ClMatMulLowpNativeKernel::validate(lhs, rhs, dst, kernel_info) :
-                          ClMatMulNativeKernel::validate(lhs, rhs, dst, kernel_info);
+    return is_quantized ? ClMatMulLowpNativeKernel::validate(lhs, rhs, dst, kernel_info, act_info) :
+           ClMatMulNativeKernel::validate(lhs, rhs, dst, kernel_info, act_info);
 }
 
-void ClMatMul::configure(const CLCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulInfo &matmul_info)
+void ClMatMul::configure(const CLCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulInfo &matmul_info, const ActivationLayerInfo &act_info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst);
     ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst, matmul_info);
@@ -86,14 +86,14 @@ void ClMatMul::configure(const CLCompileContext &compile_context, ITensorInfo *l
         _matmul_lowp_native_kernel->set_target(gpu_target);
 
         // Configure the low-precision native matrix multiply kernel
-        _matmul_lowp_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info);
+        _matmul_lowp_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info, act_info);
     }
     else
     {
         _matmul_native_kernel->set_target(gpu_target);
 
         // Configure the native matrix multiply kernel
-        _matmul_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info);
+        _matmul_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info, act_info);
     }
 }