commit 6a98a6e322bfb03f98ac9c4dfdc932ec4bea1fd7
author Usama Arif <usama.arif@arm.com> Fri May 10 17:07:27 2019 +0100
committer Usama Arif <usama.arif@arm.com> Wed May 15 14:04:19 2019 +0000
tree 8a21fd98641709708acba3b9cb00b5690ab5e3ec
parent c61321061b77763ed4569e4342ba3347a873ccb8

COMPMID-2194: Refactor activation function macro in OpenCL. Change all activation calls to macro from activation_float_helpers.h

The different kernels now call the macro from
activation_float_helpers.h. activation_helpers.h is now removed.

Change-Id: I2e1314c6bc891809e88590d99e048072541cca14
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1123
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

tests/validation/CL/Winograd.cpp

diff --git a/tests/validation/CL/Winograd.cpp b/tests/validation/CL/Winograd.cpp
index 62f0335..5894d7f 100644
--- a/tests/validation/CL/Winograd.cpp
+++ b/tests/validation/CL/Winograd.cpp
@@ -61,6 +61,7 @@
 RelativeTolerance<half_float::half> rel_tolerance_f16(half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for FP16 data types */
 constexpr float                     tolerance_num   = 0.05f;  /**< Tolerance number */
 constexpr float                     abs_tolerance_convolution_layer_f16   = 2.5f;  /**< Tolerance number */
+constexpr float                      tolerance_num_convolution_f16 = 0.15f;                 /**< Tolerance number */
 
 // Input transform
 const auto SmallWinogradInputTransformDatasetNCHW =
@@ -753,7 +754,7 @@
                                                framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16);
+    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_convolution_f16);
 }
 
 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
@@ -775,7 +776,7 @@
                                        framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16);
+    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_convolution_f16);
 }
 
 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
@@ -797,7 +798,7 @@
                                        framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16);
+    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_convolution_f16);
 }
 
 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
@@ -820,7 +821,7 @@
 
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16);
+    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_convolution_f16);
 }
 
 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
@@ -844,7 +845,7 @@
 
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16);
+    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_convolution_f16);
 }
 
 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,
@@ -868,7 +869,7 @@
 
 {
     // Validate output
-    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16);
+    validate(CLAccessor(_target), _reference, tolerance_convolution_layer_f16, tolerance_num_convolution_f16);
 }
 
 FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFastMathFixture16, framework::DatasetMode::NIGHTLY,