COMPMID-675 - Reworked NEGEMMLowp interface/function

The new interface makes NEGEMMLowp able to work with ASYMM8 data types.

Implemented 2 new functions:
- NEGEMMLowpMatrixMultiplyCore
- NEGEMMLowpOutputStage

These functions should make the integration in android NN doable

For more information about GEMMLowp:
https://github.com/google/gemmlowp/blob/master/doc/low-precision.md

Change-Id: Ie2c775f45234f68ca53dba644b3a912b997fd890
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/95504
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>

1 files changed, 22 insertions, 11 deletions

diff --git a/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h b/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h
index c81a432295..0c441df4b9 100644
--- a/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h
+++ b/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h
@@ -25,6 +25,8 @@
 #define __ARM_COMPUTE_NEGEMMLOWPMATRIXMULTIPLYCORE_H__
 
 #include "arm_compute/core/NEON/INEKernel.h"
+#include "arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.h"
+#include "arm_compute/core/NEON/kernels/NEGEMMLowpReductionKernel.h"
 #include "arm_compute/runtime/IFunction.h"
 #include "arm_compute/runtime/IMemoryManager.h"
 #include "arm_compute/runtime/MemoryGroup.h"
@@ -41,11 +43,13 @@ class ITensor;
  *  -# @ref NEGEMMInterleave4x4Kernel
  *  -# @ref NEGEMMTranspose1xWKernel
  *  -# @ref NEGEMMLowpMatrixMultiplyKernel
+ *  -# @ref NEGEMMLowpOffsetContributionKernel
  *
  * otherwise if the DOT product instruction is available:
  *
  *  -# @ref NEGEMMInterleaveBlockedKernel
  *  -# @ref NEGEMMLowpAArch64V8P4Kernel
+ *  -# @ref NEGEMMLowpOffsetContributionKernel
  *
 */
 class NEGEMMLowpMatrixMultiplyCore : public IFunction
@@ -58,11 +62,11 @@ public:
     * @note GEMM_LOWP:  low precision GEMM kernel
     *  This kernel performs the following computations:
     *
-    *  -# Convert a values from uint8 to int32
-    *  -# Convert b values from uint8 to int32
-    *  -# Compute the int32 matrix product of the resulting a * b.
+    *  -# Convert a values from QASYMM8 to int32 and add a_offset to each of them.
+    *  -# Convert b values from QASYMM8 to int32 add b_offset to each of them.
+    *  -# Compute the matrix product of the resulting a * b in int32.
     *
-    * @param[in]  a      First input tensor  (Matrix A). Data type supported: U8.
+    * @param[in]  a      First input tensor  (Matrix A). Data type supported: QASYMM8.
     * @param[in]  b      Second input tensor (Matrix B). Data type supported: same as @p a
     * @param[out] output Output tensor. Data type supported: Data type supported: S32
     */
@@ -72,13 +76,20 @@ public:
     void run() override;
 
 private:
-    MemoryGroup                _memory_group;
-    std::unique_ptr<INEKernel> _mm_kernel;
-    std::unique_ptr<INEKernel> _mtx_a_reshape_kernel;
-    std::unique_ptr<INEKernel> _mtx_b_reshape_kernel;
-    Tensor                     _tmp_a;
-    Tensor                     _tmp_b;
-    Tensor                     _workspace;
+    MemoryGroup                        _memory_group;
+    std::unique_ptr<INEKernel>         _mm_kernel;
+    std::unique_ptr<INEKernel>         _mtx_a_reshape_kernel;
+    std::unique_ptr<INEKernel>         _mtx_b_reshape_kernel;
+    NEGEMMLowpMatrixAReductionKernel   _mtx_a_reduction_kernel;
+    NEGEMMLowpMatrixBReductionKernel   _mtx_b_reduction_kernel;
+    NEGEMMLowpOffsetContributionKernel _offset_contribution_kernel;
+    Tensor                             _vector_sum_col;
+    Tensor                             _vector_sum_row;
+    Tensor                             _tmp_a;
+    Tensor                             _tmp_b;
+    Tensor                             _workspace;
+    int32_t                            _a_offset;
+    int32_t                            _b_offset;
 };
 }
 #endif /*__ARM_COMPUTE_NEGEMMLOWPMATRIXMULTIPLYCORE_H__ */