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, 22 insertions, 9 deletions

diff --git a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
index cc0f20e695..d42e656e0c 100644
--- a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp
@@ -42,10 +42,17 @@
 #include "src/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.h"
 #include "src/core/NEON/kernels/NEGEMMLowpReductionKernel.h"
 #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h"
+#include "src/core/helpers/MemoryHelpers.h"
 #include "src/runtime/cpu/operators/internal/CpuGemmAssemblyDispatch.h"
 
 namespace arm_compute
 {
+using WorkspaceDataType = WorkspaceData<Tensor>;
+struct NEGEMMLowpMatrixMultiplyCore::AsmGlueTensors
+{
+    ITensorPack       tensors{};
+    WorkspaceDataType ws{};
+};
 namespace
 {
 cpu::AsmGemmInfo init_assembly_metadata(const GEMMInfo &info)
@@ -66,11 +73,11 @@ using namespace arm_compute::misc::shape_calculator;
 NEGEMMLowpMatrixMultiplyCore::~NEGEMMLowpMatrixMultiplyCore() = default;
 
 NEGEMMLowpMatrixMultiplyCore::NEGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
-    : _memory_group(memory_manager), _weights_manager(weights_manager), _asm_glue(std::make_unique<cpu::CpuGemmAssemblyDispatch>(memory_manager, weights_manager)), _mm_kernel(), _mtx_a_reshape_kernel(),
+    : _memory_group(memory_manager), _weights_manager(weights_manager), _asm_glue(std::make_unique<cpu::CpuGemmAssemblyDispatch>(weights_manager)), _mm_kernel(), _mtx_a_reshape_kernel(),
       _mtx_b_reshape_kernel(), _mtx_a_reduction_kernel(), _mtx_b_reduction_kernel(), _offset_contribution_kernel(), _offset_contribution_output_stage_kernel(), _activation_func(),
       _convert_to_signed_asymm(), _convert_from_signed_asymm(), _vector_sum_col(), _vector_sum_row(), _tmp_a(), _tmp_b(), _mm_result_s32(), _signed_a(), _signed_output(), _original_b(nullptr), _a_offset(0),
       _b_offset(0), _run_vector_matrix_multiplication(false), _assembly_path(false), _fused_assembly_path(false), _reshape_b_only_on_first_run(false), _is_prepared(false), _fuse_output_stage(false),
-      _run_activation(false), _flip_signedness(false)
+      _run_activation(false), _flip_signedness(false), _asm_glue_tensors(std::make_unique<AsmGlueTensors>())
 {
 }
 
@@ -149,18 +156,24 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b,
                 auto c_info_to_use = c == nullptr ? nullptr : c->info();
                 _asm_glue->configure(a_to_use->info(), b->info(), c_info_to_use, output->info(), asm_info);
                 _fused_assembly_path = _asm_glue->is_configured();
-                _asm_glue_tensors.add_const_tensor(TensorType::ACL_SRC_2, c);
-                _asm_glue_tensors.add_tensor(TensorType::ACL_DST, output);
+                _asm_glue_tensors->tensors.add_const_tensor(TensorType::ACL_SRC_2, c);
+                _asm_glue_tensors->tensors.add_tensor(TensorType::ACL_DST, output);
             }
             else
             {
                 auto output_to_use = (_fuse_output_stage ? &_mm_result_s32 : output);
                 _asm_glue->configure(a_to_use->info(), b->info(), nullptr, output_to_use->info(), asm_info);
-                _asm_glue_tensors.add_tensor(TensorType::ACL_DST, output_to_use);
+                _asm_glue_tensors->tensors.add_tensor(TensorType::ACL_DST, output_to_use);
             }
             _assembly_path = _asm_glue->is_configured();
-            _asm_glue_tensors.add_const_tensor(TensorType::ACL_SRC_0, a_to_use);
-            _asm_glue_tensors.add_const_tensor(TensorType::ACL_SRC_1, b);
+            _asm_glue_tensors->tensors.add_const_tensor(TensorType::ACL_SRC_0, a_to_use);
+            _asm_glue_tensors->tensors.add_const_tensor(TensorType::ACL_SRC_1, b);
+
+            if(_assembly_path)
+            {
+                _asm_glue_tensors->ws = manage_workspace<Tensor>(_asm_glue->workspace(), _memory_group, _asm_glue_tensors->tensors);
+            }
+
             break;
         }
         default:
@@ -520,7 +533,7 @@ void NEGEMMLowpMatrixMultiplyCore::run()
     // Run GEMM
     if(_asm_glue->is_configured())
     {
-        _asm_glue->run(_asm_glue_tensors);
+        _asm_glue->run(_asm_glue_tensors->tensors);
     }
     else
     {
@@ -590,7 +603,7 @@ void NEGEMMLowpMatrixMultiplyCore::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();