Rework gemmlowp reshaped_only_rhs using the new macros

Resolve COMPMID-4416

Change-Id: I83cdf0de7adaf4d465ffebd494ab913182072485
Signed-off-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5788
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 23 insertions, 8 deletions

diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index 5cf210bab4..ab9d35de0f 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -97,7 +97,7 @@ void fill(U &&tensor, int i)
 template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d, bool reinterpret_output_as_3d, typename OutputType, bool is_fused = false>
 TensorType compute_gemmlowp_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
                                    GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo(), DataType data_type_a = DataType::QASYMM8, DataType data_type_b = DataType::QASYMM8,
-                                   QuantizationInfo b_qinfo = QuantizationInfo())
+                                   QuantizationInfo b_qinfo = QuantizationInfo(), bool reshape_b_only_on_first_run = false)
 {
     // Create tensors
     DataType data_type_output = output_stage.type == GEMMLowpOutputStageType::NONE ? DataType::S32 : data_type_a;
@@ -126,7 +126,8 @@ TensorType compute_gemmlowp_target(const TensorShape &shape_a, const TensorShape
     // Create and configure function
     // The GEMMinfo includes the values of the depth in case of reinterpreted 3d input/output
     FunctionType gemmlowp;
-    gemmlowp.configure(&a, &b, is_fused ? &bias : nullptr, &output, GEMMInfo(false, false, false, (reinterpret_output_as_3d ? shape_output[2] : 0), reinterpret_input_as_3d, false, output_stage));
+    gemmlowp.configure(&a, &b, is_fused ? &bias : nullptr, &output, GEMMInfo(false, false, reshape_b_only_on_first_run, (reinterpret_output_as_3d ? shape_output[2] : 0), reinterpret_input_as_3d, false,
+                                                                             output_stage));
 
     ARM_COMPUTE_ASSERT(a.info()->is_resizable());
     ARM_COMPUTE_ASSERT(b.info()->is_resizable());
@@ -208,11 +209,12 @@ protected:
 };
 
 template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d = false, bool reinterpret_output_as_3d = false, typename TI = uint8_t, typename TW = uint8_t>
-class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture : public framework::Fixture
+class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture : public framework::Fixture
 {
 public:
     template <typename...>
-    void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage, DataType data_type_b)
+    void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage, DataType data_type_b,
+               bool reshape_b_only_on_first_run)
     {
         ARM_COMPUTE_ASSERT(output_stage.type != GEMMLowpOutputStageType::NONE);
         DataType data_type_a = data_type_b == DataType::QASYMM8_SIGNED ? DataType::QASYMM8_SIGNED : DataType::QASYMM8;
@@ -232,21 +234,21 @@ public:
             }
 
             _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales));
-            _target    = compute_target(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales));
+            _target    = compute_target(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales), reshape_b_only_on_first_run);
         }
         else
         {
             _reference = compute_reference(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo());
-            _target    = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo());
+            _target    = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo(), reshape_b_only_on_first_run);
         }
     }
 
 protected:
     TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage,
-                              DataType data_type_a, DataType data_type_b, QuantizationInfo b_qinfo)
+                              DataType data_type_a, DataType data_type_b, QuantizationInfo b_qinfo, bool reshape_b_only_on_first_run = false)
     {
         return compute_gemmlowp_target<TensorType, AccessorType, FunctionType, reinterpret_input_as_3d, reinterpret_output_as_3d, qasymm8_t, true>(shape_a, shape_b, shape_output, a_offset, b_offset,
-                output_stage, data_type_a, data_type_b, b_qinfo);
+                output_stage, data_type_a, data_type_b, b_qinfo, reshape_b_only_on_first_run);
     }
 
     SimpleTensor<TI> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
@@ -277,6 +279,19 @@ protected:
     SimpleTensor<TI> _reference{};
 };
 
+template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d = false, bool reinterpret_output_as_3d = false, typename TI = uint8_t, typename TW = uint8_t>
+class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture : public
+    GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture<TensorType, AccessorType, FunctionType, reinterpret_input_as_3d, reinterpret_output_as_3d, TI, TW>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage, DataType data_type_b)
+    {
+        GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture<TensorType, AccessorType, FunctionType, reinterpret_input_as_3d, reinterpret_output_as_3d, TI, TW>::setup(shape_a, shape_b,
+                shape_output, a_offset, b_offset, output_stage, data_type_b, false);
+    }
+};
+
 template <typename TensorType, typename AccessorType, typename FunctionType>
 class GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture : public framework::Fixture
 {