COMPMID-415: Use absolute and relative tolerance

Change-Id: Ib779fa307e05fa67172ddaf521239b4c746debc8
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/82229
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>

5 files changed, 21 insertions, 21 deletions

diff --git a/tests/validation_new/NEON/ActivationLayer.cpp b/tests/validation_new/NEON/ActivationLayer.cpp
index db0faaecdf..bc2fe603fd 100644
--- a/tests/validation_new/NEON/ActivationLayer.cpp
+++ b/tests/validation_new/NEON/ActivationLayer.cpp
@@ -51,7 +51,7 @@ namespace
  *
  * @return Tolerance depending on the activation function.
  */
-float tolerance(DataType data_type, ActivationLayerInfo::ActivationFunction activation)
+AbsoluteTolerance<float> tolerance(DataType data_type, ActivationLayerInfo::ActivationFunction activation)
 {
     switch(activation)
     {
@@ -62,17 +62,17 @@ float tolerance(DataType data_type, ActivationLayerInfo::ActivationFunction acti
             switch(data_type)
             {
                 case DataType::QS8:
-                    return 5.f;
+                    return AbsoluteTolerance<float>(5.f);
                 case DataType::QS16:
-                    return 11.f;
+                    return AbsoluteTolerance<float>(11.f);
                 case DataType::F16:
-                    return 0.01f;
+                    return AbsoluteTolerance<float>(0.01f);
                 default:
-                    return 0.00001f;
+                    return AbsoluteTolerance<float>(0.00001f);
             }
             break;
         default:
-            return 0.f;
+            return AbsoluteTolerance<float>(0.f);
     }
 }
 
diff --git a/tests/validation_new/NEON/ConvolutionLayer.cpp b/tests/validation_new/NEON/ConvolutionLayer.cpp
index af33cc0707..1efff02428 100644
--- a/tests/validation_new/NEON/ConvolutionLayer.cpp
+++ b/tests/validation_new/NEON/ConvolutionLayer.cpp
@@ -44,11 +44,11 @@ namespace validation
 {
 namespace
 {
-const float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+const AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
 #ifdef ARM_COMPUTE_ENABLE_FP16
-const float tolerance_f16 = 0.01f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
-#endif                             /* ARM_COMPUTE_ENABLE_FP16 */
-const float tolerance_q = 1.0f;    /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
+const AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+#endif                                               /* ARM_COMPUTE_ENABLE_FP16 */
+const AbsoluteTolerance<float> tolerance_q(1.0f);    /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
 
 /** CNN data types */
 const auto CNNDataTypes = framework::dataset::make("DataType",
diff --git a/tests/validation_new/NEON/DirectConvolutionLayer.cpp b/tests/validation_new/NEON/DirectConvolutionLayer.cpp
index a46f5a5dcc..90c4abe9c2 100644
--- a/tests/validation_new/NEON/DirectConvolutionLayer.cpp
+++ b/tests/validation_new/NEON/DirectConvolutionLayer.cpp
@@ -43,11 +43,11 @@ namespace validation
 {
 namespace
 {
-constexpr float tolerance_qs = 1.f; /**< Tolerance for fixed point tests */
+constexpr AbsoluteTolerance<float> tolerance_qs(1.f); /**< Tolerance for fixed point tests */
 #ifdef ARM_COMPUTE_ENABLE_FP16
-constexpr float tolerance_fp16 = 0.01f;  /**< Tolerance for half precision floating point tests */
-#endif                                   /* ARM_COMPUTE_ENABLE_FP16 */
-constexpr float tolerance_fp32 = 0.001f; /**< Tolerance for floating point tests */
+constexpr AbsoluteTolerance<float> tolerance_fp16(0.01f);  /**< Tolerance for half precision floating point tests */
+#endif                                                     /* ARM_COMPUTE_ENABLE_FP16 */
+constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */
 
 /** Direct convolution data set. */
 const auto data = combine(datasets::SmallDirectConvolutionShapes(),
diff --git a/tests/validation_new/NEON/NormalizationLayer.cpp b/tests/validation_new/NEON/NormalizationLayer.cpp
index dfe793131a..1da2ed0874 100644
--- a/tests/validation_new/NEON/NormalizationLayer.cpp
+++ b/tests/validation_new/NEON/NormalizationLayer.cpp
@@ -46,12 +46,12 @@ namespace
 {
 /** Tolerance for float operations */
 #ifdef ARM_COMPUTE_ENABLE_FP16
-constexpr float tolerance_f16 = 0.001f;
+constexpr AbsoluteTolerance<float> tolerance_f16(0.001f);
 #endif /* ARM_COMPUTE_ENABLE_FP16 */
-constexpr float tolerance_f32 = 0.00001f;
+constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f);
 /** Tolerance for fixed point operations */
-constexpr int8_t  tolerance_qs8  = 2;
-constexpr int16_t tolerance_qs16 = 3;
+constexpr AbsoluteTolerance<int8_t>  tolerance_qs8(2);
+constexpr AbsoluteTolerance<int16_t> tolerance_qs16(3);
 
 /** Input data set. */
 const auto NormalizationDataset = combine(combine(combine(datasets::SmallShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
diff --git a/tests/validation_new/NEON/SoftmaxLayer.cpp b/tests/validation_new/NEON/SoftmaxLayer.cpp
index ce5b8b8359..337ee29986 100644
--- a/tests/validation_new/NEON/SoftmaxLayer.cpp
+++ b/tests/validation_new/NEON/SoftmaxLayer.cpp
@@ -44,12 +44,12 @@ namespace validation
 namespace
 {
 /** Tolerance for float operations */
-constexpr float tolerance_f32 = 0.000001f;
+constexpr AbsoluteTolerance<float> tolerance_f32(0.000001f);
 #ifdef ARM_COMPUTE_ENABLE_FP16
-const float tolerance_f16 = 0.0001f;
+constexpr AbsoluteTolerance<float> tolerance_f16(0.0001f);
 #endif /* ARM_COMPUTE_ENABLE_FP16*/
 /** Tolerance for fixed point operations */
-constexpr int8_t tolerance_fixed_point = 2;
+constexpr AbsoluteTolerance<int8_t> tolerance_fixed_point(2);
 
 /** CNN data types */
 const auto CNNDataTypes = framework::dataset::make("DataType",