aboutsummaryrefslogtreecommitdiff
path: root/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
diff options
context:
space:
mode:
Diffstat (limited to 'tests/validation/fixtures/WinogradConvolutionLayerFixture.h')
-rw-r--r--tests/validation/fixtures/WinogradConvolutionLayerFixture.h23
1 files changed, 19 insertions, 4 deletions
diff --git a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
index e1cc953375..1061fd00ab 100644
--- a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
@@ -72,9 +72,14 @@ protected:
switch(tensor.data_type())
{
case DataType::F16:
+ {
+ arm_compute::utils::uniform_real_distribution_fp16 distribution{ half(min), half(max) };
+ library->fill(tensor, distribution, i);
+ break;
+ }
case DataType::F32:
{
- std::uniform_real_distribution<> distribution(min, max);
+ std::uniform_real_distribution<float> distribution(min, max);
library->fill(tensor, distribution, i);
break;
}
@@ -183,7 +188,7 @@ protected:
}
case DataType::F32:
{
- std::uniform_real_distribution<> distribution(min, max);
+ std::uniform_real_distribution<float> distribution(min, max);
library->fill(tensor, distribution, i);
break;
}
@@ -338,9 +343,14 @@ protected:
switch(tensor.data_type())
{
case DataType::F16:
+ {
+ arm_compute::utils::uniform_real_distribution_fp16 distribution{ half(min), half(max) };
+ library->fill(tensor, distribution, i);
+ break;
+ }
case DataType::F32:
{
- std::uniform_real_distribution<> distribution(min, max);
+ std::uniform_real_distribution<float> distribution(min, max);
library->fill(tensor, distribution, i);
break;
}
@@ -420,9 +430,14 @@ protected:
switch(tensor.data_type())
{
case DataType::F16:
+ {
+ arm_compute::utils::uniform_real_distribution_fp16 distribution{ half(min), half(max) };
+ library->fill(tensor, distribution, i);
+ break;
+ }
case DataType::F32:
{
- std::uniform_real_distribution<> distribution(min, max);
+ std::uniform_real_distribution<float> distribution(min, max);
library->fill(tensor, distribution, i);
break;
}