Create core library using high priority operators

A smaller core library is created using a subset of the operators.
Changed the structure of filelist.json in order to include more
information about the kernels and make the selection easier.

Resolves: COMPMID-4514

Change-Id: I079ca7d8e64346174eebdd13b834e1dd4dc36ca2
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5786
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 3 insertions, 3 deletions

diff --git a/src/runtime/CPP/SingleThreadScheduler.cpp b/src/runtime/CPP/SingleThreadScheduler.cpp
index 70536b7ccc..5890553f6f 100644
--- a/src/runtime/CPP/SingleThreadScheduler.cpp
+++ b/src/runtime/CPP/SingleThreadScheduler.cpp
@@ -49,7 +49,7 @@ void SingleThreadScheduler::schedule(ICPPKernel *kernel, const Hints &hints)
     }
 
     ThreadInfo info;
-    info.cpu_info = &_cpu_info;
+    info.cpu_info = &cpu_info();
     kernel->run(kernel->window(), info);
 }
 
@@ -57,14 +57,14 @@ void SingleThreadScheduler::schedule_op(ICPPKernel *kernel, const Hints &hints,
 {
     ARM_COMPUTE_UNUSED(hints);
     ThreadInfo info;
-    info.cpu_info = &_cpu_info;
+    info.cpu_info = &cpu_info();
     kernel->run_op(tensors, window, info);
 }
 
 void SingleThreadScheduler::run_workloads(std::vector<Workload> &workloads)
 {
     ThreadInfo info;
-    info.cpu_info = &_cpu_info;
+    info.cpu_info = &cpu_info();
     for(auto &wl : workloads)
     {
         wl(info);