COMPMID-516 Increase tolerance rate of Scale, Conv, fully connected and GEMM

This patch also fix the scale kernel issue where it was calcuated the
scale factor inside the gpu but now in the CPU. The GPU and CPU gave
different result for simple float division operation

Change-Id: Ib6709cb6c41dcf4fc0fa4eb79e481430695bf40e
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/87266
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Moritz Pflanzer <moritz.pflanzer@arm.com>

4 files changed, 15 insertions, 14 deletions

diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index b2fd22eaee..a6e07248aa 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -43,10 +43,10 @@ namespace validation
 {
 namespace
 {
-RelativeTolerance<float>           tolerance_f32(0.001f);    /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
-RelativeTolerance<half>            tolerance_f16(half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
-constexpr AbsoluteTolerance<float> tolerance_q(1.0f);        /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
-constexpr float                    tolerance_num = 0.07f;    /**< Tolerance number */
+RelativeTolerance<float>            tolerance_f32(0.05f);                 /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+constexpr AbsoluteTolerance<float>  tolerance_q(1.0f);                    /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
+constexpr float                     tolerance_num = 0.07f;                /**< Tolerance number */
 
 /** CNN data types */
 const auto CNNDataTypes = framework::dataset::make("DataType",
diff --git a/tests/validation/CL/FullyConnectedLayer.cpp b/tests/validation/CL/FullyConnectedLayer.cpp
index 22f27e56dd..35b9d2938b 100644
--- a/tests/validation/CL/FullyConnectedLayer.cpp
+++ b/tests/validation/CL/FullyConnectedLayer.cpp
@@ -43,9 +43,9 @@ namespace validation
 namespace
 {
 /** Tolerance for float operations */
-RelativeTolerance<float> tolerance_f32(0.001f);
-RelativeTolerance<half>  tolerance_f16(half(0.2));
-constexpr float          tolerance_num = 0.07f; /**< Tolerance number */
+RelativeTolerance<float>            tolerance_f32(0.05f);
+RelativeTolerance<half_float::half> tolerance_f16(half(0.2));
+constexpr float                     tolerance_num = 0.07f; /**< Tolerance number */
 
 /** Tolerance for fixed point operations */
 constexpr AbsoluteTolerance<float> tolerance_fixed_point(1.f);
diff --git a/tests/validation/CL/GEMM.cpp b/tests/validation/CL/GEMM.cpp
index 854551917e..62671e34d7 100644
--- a/tests/validation/CL/GEMM.cpp
+++ b/tests/validation/CL/GEMM.cpp
@@ -43,9 +43,10 @@ namespace validation
 {
 namespace
 {
-RelativeTolerance<float>           tolerance_f32(0.001f);    /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */
-RelativeTolerance<half>            tolerance_f16(half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */
-constexpr AbsoluteTolerance<float> tolerance_q(1.0f);        /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
+RelativeTolerance<float>            tolerance_f32(0.001f);    /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */
+RelativeTolerance<half_float::half> tolerance_f16(half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */
+constexpr AbsoluteTolerance<float>  tolerance_q(1.0f);        /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
+constexpr float                     tolerance_num = 0.02f;    /**< Tolerance number */
 
 /** CNN data types */
 const auto CNNDataTypes = framework::dataset::make("DataType",
@@ -92,13 +93,13 @@ TEST_SUITE(FP16)
 FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallGEMMDataset(), framework::dataset::make("DataType", DataType::F16)))
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_f16);
+    validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
 }
 FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGEMMDataset(), framework::dataset::make("DataType",
                                                                                                DataType::F16)))
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_f16);
+    validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
 }
 TEST_SUITE_END()
 
diff --git a/tests/validation/CL/Scale.cpp b/tests/validation/CL/Scale.cpp
index 6757bd5ee3..1a458b7a08 100644
--- a/tests/validation/CL/Scale.cpp
+++ b/tests/validation/CL/Scale.cpp
@@ -57,14 +57,14 @@ const auto ScaleDataTypes = framework::dataset::make("DataType",
 /** Tolerance */
 constexpr AbsoluteTolerance<uint8_t> tolerance_u8(1);
 constexpr AbsoluteTolerance<int16_t> tolerance_s16(1);
-RelativeTolerance<float>             tolerance_f32(0.01);
+RelativeTolerance<float>             tolerance_f32(0.05);
 RelativeTolerance<half>              tolerance_f16(half(0.1));
 } // namespace
 
 TEST_SUITE(CL)
 TEST_SUITE(Scale)
 
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), ScaleDataTypes),
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(concat(datasets::MediumShapes(), datasets::LargeShapes()), ScaleDataTypes),
                                                                            framework::dataset::make("InterpolationPolicy", { InterpolationPolicy::NEAREST_NEIGHBOR, InterpolationPolicy::BILINEAR })),
                                                                    datasets::BorderModes()),
                shape, data_type, policy, border_mode)