Implement memory injection in CpuDirectGemmConv2d

The following operators are now stateless by implementing
memory injection.

- CpuDirectGemmConv2d
- CpuGemmAssemblyDispatch

A test case is added to test if CpuDirectGemmConv2d can
run on different group of tensors with a single configure.

Resolves: COMPMID-4506

Change-Id: I48f44ed41236ca7e18da2de07bdbacc9007a3c5e
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5718
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>

1 files changed, 15 insertions, 4 deletions

diff --git a/src/runtime/NEON/functions/NEGEMM.cpp b/src/runtime/NEON/functions/NEGEMM.cpp
index 7318c3e492..b526874790 100644
--- a/src/runtime/NEON/functions/NEGEMM.cpp
+++ b/src/runtime/NEON/functions/NEGEMM.cpp
@@ -38,6 +38,7 @@
 #include "src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h"
 #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h"
 #include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/MemoryHelpers.h"
 #include "src/runtime/cpu/operators/internal/CpuGemmAssemblyDispatch.h"
 
 #include <cmath>
@@ -46,6 +47,14 @@ using namespace arm_compute::misc::shape_calculator;
 
 namespace arm_compute
 {
+using WorkspaceDataType = WorkspaceData<Tensor>;
+
+struct NEGEMM::AsmGlueTensors
+{
+    ITensorPack       tensors{};
+    WorkspaceDataType ws{};
+};
+
 namespace
 {
 cpu::AsmGemmInfo init_assembly_metadata(const GEMMInfo &info)
@@ -63,7 +72,7 @@ cpu::AsmGemmInfo init_assembly_metadata(const GEMMInfo &info)
 NEGEMM::NEGEMM(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
     : _memory_group(memory_manager), _weights_manager(weights_manager), _interleave_kernel(), _transpose_kernel(), _mm_kernel(), _asm_glue(std::make_unique<cpu::CpuGemmAssemblyDispatch>()), _ma_kernel(),
       _alpha_scale_func(nullptr), _add_bias(), _activation_func(), _tmp_a(), _tmp_b(), _tmp_d(), _original_b(nullptr), _run_vector_matrix_multiplication(false), _run_alpha_scale(false),
-      _run_addition(false), _run_bias_addition(false), _run_activation(false), _reshape_b_only_on_first_run(false), _is_prepared(false)
+      _run_addition(false), _run_bias_addition(false), _run_activation(false), _reshape_b_only_on_first_run(false), _is_prepared(false), _asm_glue_tensors(std::make_unique<AsmGlueTensors>())
 {
 }
 
@@ -94,7 +103,7 @@ void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITe
         _asm_glue->configure(a->info(), b->info(), c_info_to_use, d->info(), asm_info);
         ARM_COMPUTE_ERROR_ON(!_asm_glue->is_configured());
 
-        _asm_glue_tensors =
+        _asm_glue_tensors->tensors =
         {
             { ACL_SRC_0, a },
             { ACL_SRC_1, b },
@@ -102,6 +111,8 @@ void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITe
             { ACL_DST, d },
         };
 
+        _asm_glue_tensors->ws = manage_workspace<Tensor>(_asm_glue->workspace(), _memory_group, _asm_glue_tensors->tensors);
+
         // Scale product by alpha
         if(_run_alpha_scale)
         {
@@ -323,7 +334,7 @@ void NEGEMM::run()
 
     if(_asm_glue->is_configured())
     {
-        _asm_glue->run(_asm_glue_tensors);
+        _asm_glue->run(_asm_glue_tensors->tensors);
         if(_run_alpha_scale)
         {
             _alpha_scale_func.run();
@@ -377,7 +388,7 @@ void NEGEMM::prepare()
                 ARM_COMPUTE_ERROR_ON(!_original_b->is_used());
             }
 
-            _asm_glue->prepare(_asm_glue_tensors);
+            _asm_glue->prepare(_asm_glue_tensors->tensors);
             if(!original_b_managed_by_weights_manager)
             {
                 _original_b->mark_as_unused();