Update ACL pin to c952596e70f2fe0073029f053e329a4e930ced8c

* activationInfo passed in directly to configure() rather than part of matMulInfo

Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I546def1c1e1cabaf50629f7d78ae0ba459766ed4

3 files changed, 8 insertions, 9 deletions

diff --git a/scripts/get_compute_library.sh b/scripts/get_compute_library.sh
index 89ff764c57..731ab7e1ce 100755
--- a/scripts/get_compute_library.sh
+++ b/scripts/get_compute_library.sh
@@ -10,7 +10,7 @@ CMD=$( basename "$0" )
 #DEFAULT_CLFRAMEWORKREVISION="branches/arm_compute_23_05" # Release 23.05
 #
 # For pinning to a revision use this:
-DEFAULT_CLFRAMEWORKREVISION="043613fbb199e2c4fdd12c2c9a1785db9b0c45fa" #9743: Break up Utils.h a bit to reduce unused code being included everywhere
+DEFAULT_CLFRAMEWORKREVISION="c952596e70f2fe0073029f053e329a4e930ced8c" #9819: Implement FP32/FP16 MatMul NT/T kernel using the MMUL extension
 
 usage() {
   echo -e "get_compute_library.sh: Clones the Arm Compute Library (ACL) repo from the ML Platform server and checks out
diff --git a/src/backends/cl/workloads/ClBatchMatMulWorkload.cpp b/src/backends/cl/workloads/ClBatchMatMulWorkload.cpp
index cfed1b83a1..313c3453a5 100644
--- a/src/backends/cl/workloads/ClBatchMatMulWorkload.cpp
+++ b/src/backends/cl/workloads/ClBatchMatMulWorkload.cpp
@@ -50,9 +50,8 @@ arm_compute::Status ClBatchMatMulValidate(const TensorInfo& inputInfoX,
     arm_compute::MatMulInfo matMulInfo;
     matMulInfo.adj_lhs(descriptor.m_TransposeX);
     matMulInfo.adj_rhs(descriptor.m_TransposeY);
-    matMulInfo.fused_activation(activationInfo);
 
-    return arm_compute::CLMatMul::validate(&aclInputInfoX, &aclInputInfoY, &aclOutputInfo, matMulInfo);
+    return arm_compute::CLMatMul::validate(&aclInputInfoX, &aclInputInfoY, &aclOutputInfo, matMulInfo, activationInfo);
 }
 
 ClBatchMatMulWorkload::ClBatchMatMulWorkload(const BatchMatMulQueueDescriptor& descriptor,
@@ -92,9 +91,10 @@ ClBatchMatMulWorkload::ClBatchMatMulWorkload(const BatchMatMulQueueDescriptor& d
     arm_compute::MatMulInfo matMulInfo;
     matMulInfo.adj_lhs(descriptor.m_Parameters.m_TransposeX);
     matMulInfo.adj_rhs(descriptor.m_Parameters.m_TransposeY);
-    matMulInfo.fused_activation(activationInfo);
 
-    m_MatMulLayer.configure(clCompileContext, &inputX, &inputY, &output, matMulInfo);
+    arm_compute::GpuMatMulSettings settings;
+
+    m_MatMulLayer.configure(clCompileContext, &inputX, &inputY, &output, matMulInfo, settings, activationInfo);
 
     // Report Profiling Details
     WorkloadInfo detailsInfo;
diff --git a/src/backends/neon/workloads/NeonBatchMatMulWorkload.cpp b/src/backends/neon/workloads/NeonBatchMatMulWorkload.cpp
index 628e314046..7f2b6eaf99 100644
--- a/src/backends/neon/workloads/NeonBatchMatMulWorkload.cpp
+++ b/src/backends/neon/workloads/NeonBatchMatMulWorkload.cpp
@@ -46,12 +46,12 @@ arm_compute::Status NeonBatchMatMulValidate(const TensorInfo& inputInfoX,
     arm_compute::MatMulInfo matMulInfo;
     matMulInfo.adj_lhs(descriptor.m_TransposeX);
     matMulInfo.adj_rhs(descriptor.m_TransposeY);
-    matMulInfo.fused_activation(activationInfo);
 
     arm_compute::CpuMatMulSettings settings;
     settings.fast_math(isFastMathEnabled);
 
-    return arm_compute::NEMatMul::validate(&aclInputInfoX, &aclInputInfoY, &aclOutputInfo, matMulInfo, settings);
+    return arm_compute::NEMatMul::validate(&aclInputInfoX, &aclInputInfoY, &aclOutputInfo, matMulInfo, settings,
+                                           activationInfo);
 }
 
 NeonBatchMatMulWorkload::NeonBatchMatMulWorkload(const BatchMatMulQueueDescriptor& descriptor,
@@ -84,12 +84,11 @@ NeonBatchMatMulWorkload::NeonBatchMatMulWorkload(const BatchMatMulQueueDescripto
     arm_compute::MatMulInfo matMulInfo;
     matMulInfo.adj_lhs(descriptor.m_Parameters.m_TransposeX);
     matMulInfo.adj_rhs(descriptor.m_Parameters.m_TransposeY);
-    matMulInfo.fused_activation(activationInfo);
 
     arm_compute::CpuMatMulSettings settings;
     settings.fast_math(isFastMathEnabled);
 
-    m_MatMulLayer.configure(&inputX, &inputY, &output, matMulInfo, settings);
+    m_MatMulLayer.configure(&inputX, &inputY, &output, matMulInfo, settings, activationInfo);
 
     // Report Profiling Details
     WorkloadInfo detailsInfo;