IVGCVSW-3296 Add CL backend support for ResizeNearestNeighbour
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: I7f4c722141837939fd8904c52e75704a15c8a5e3
diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index 7db8471..d6747f5 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -950,7 +950,11 @@
LayerTestResult<T, 4> ResizeNearestNeighborMagTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayout dataLayout);
+ const armnn::DataLayout dataLayout,
+ float inQuantScale,
+ int32_t inQuantOffset,
+ float outQuantScale,
+ int32_t outQuantOffset);
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 2> Rsqrt2dTestCommon(
@@ -3391,7 +3395,11 @@
LayerTestResult<T, 4> ResizeNearestNeighborMagTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayout dataLayout)
+ const armnn::DataLayout dataLayout,
+ float inQuantScale,
+ int32_t inQuantOffset,
+ float outQuantScale,
+ int32_t outQuantOffset)
{
armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
? armnnUtils::GetTensorInfo(1, 1, 3, 2, dataLayout, ArmnnType)
@@ -3402,46 +3410,46 @@
if (armnn::IsQuantizedType<T>())
{
- inputTensorInfo.SetQuantizationScale(0.010765f);
- inputTensorInfo.SetQuantizationOffset(7);
- outputTensorInfo.SetQuantizationScale(0.010132f);
- outputTensorInfo.SetQuantizationOffset(-18);
+ inputTensorInfo.SetQuantizationScale(inQuantScale);
+ inputTensorInfo.SetQuantizationOffset(inQuantOffset);
+ outputTensorInfo.SetQuantizationScale(outQuantScale);
+ outputTensorInfo.SetQuantizationOffset(outQuantOffset);
}
std::vector<float> inputData = armnn::IsQuantizedType<T>()
? std::initializer_list<float>
- {
- 0.183005f, 2.379065f, // 24, 228, : Expected quantised values
- 1.05497f, 1.302565f, // 105, 128,
- 2.400595f, 0.68896f // 230, 71
- }
+ {
+ 0.183005f, 2.379065f, // 24, 228, : expected quantised values
+ 1.054970f, 1.302565f, // 105, 128,
+ 2.400595f, 0.688960f // 230, 71
+ }
: std::initializer_list<float>
- {
- 1.0f, 2.0f,
- 13.0f, 21.0f,
- 144.0f, 233.0f,
+ {
+ 1.0f, 2.0f,
+ 13.0f, 21.0f,
+ 144.0f, 233.0f,
- 233.0f, 144.0f,
- 21.0f, 13.0f,
- 2.0f, 1.0f
- };
+ 233.0f, 144.0f,
+ 21.0f, 13.0f,
+ 2.0f, 1.0f
+ };
std::vector<float> outputData = armnn::IsQuantizedType<T>()
? std::initializer_list<float>
- {
- 0.183005f, 0.183005f, 0.183005f, 2.379065f, 2.379065f,
- 1.05497f, 1.05497f, 1.05497f, 1.302565f, 1.302565f,
- 2.400595f, 2.400595f, 2.400595f, 0.68896f, 0.68896f
- }
+ {
+ 0.183005f, 0.183005f, 0.183005f, 2.379065f, 2.379065f,
+ 1.054970f, 1.054970f, 1.054970f, 1.302565f, 1.302565f,
+ 2.400595f, 2.400595f, 2.400595f, 0.688960f, 0.688960f
+ }
: std::initializer_list<float>
- {
- 1.f, 1.f, 1.f, 2.f, 2.f,
- 13.f, 13.f, 13.f, 21.f, 21.f,
- 144.f, 144.f, 144.f, 233.f, 233.f,
+ {
+ 1.f, 1.f, 1.f, 2.f, 2.f,
+ 13.f, 13.f, 13.f, 21.f, 21.f,
+ 144.f, 144.f, 144.f, 233.f, 233.f,
- 233.f, 233.f, 233.f, 144.f, 144.f,
- 21.f, 21.f, 21.f, 13.f, 13.f,
- 2.f, 2.f, 2.f, 1.f, 1.f
- };
+ 233.f, 233.f, 233.f, 144.f, 144.f,
+ 21.f, 21.f, 21.f, 13.f, 13.f,
+ 2.f, 2.f, 2.f, 1.f, 1.f
+ };
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
if (dataLayout == armnn::DataLayout::NHWC)
@@ -3488,7 +3496,6 @@
return result;
}
-
template<armnn::DataType ArmnnType, typename T, std::size_t InputDim, std::size_t OutputDim>
LayerTestResult<T, OutputDim> MeanTestHelper(
armnn::IWorkloadFactory& workloadFactory,