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>
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,