IVGCVSW-3536 Add Axis parameter to reference Softmax implementation
* Add Axis parameter to Softmax Descriptor
* Add new reference implementation for Softmax using Axis parameter
* Add unit tests to cover each Axis
Change-Id: Iafac2275d2212337456f2b1b56b0f76f77fb9543
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp
index d6e0e87..b40a3f5 100644
--- a/src/backends/backendsCommon/test/LayerTests.cpp
+++ b/src/backends/backendsCommon/test/LayerTests.cpp
@@ -77,6 +77,36 @@
// 2-channel bias used by a number of Conv2d tests.
static std::vector<float> Bias2({0, 2});
+struct Simple3dSoftmaxOutputData
+{
+ const std::vector<float> outputData =
+ {
+ 0.0964599f, 0.26220518f, 0.0964599f, 0.0964599f,
+ 0.15903549f, 0.0964599f, 0.0964599f, 0.0964599f
+ };
+
+ const armnn::TensorShape inputShape{ 1, 8, 1 };
+
+ const std::vector<float> inputData =
+ {
+ 0.f, 1.f, 0.f, 0.f,
+ .5f, 0.f, 0.f, 0.f,
+ };
+};
+
+struct Simple4dSoftmaxData
+{
+ const armnn::TensorShape inputShape{ 1, 8, 1, 1 };
+
+ const std::vector<float> outputData = { 0.0964599f, 0.26220518f, 0.0964599f, 0.0964599f,
+ 0.15903549f, 0.0964599f, 0.0964599f, 0.0964599f };
+ const std::vector<float> inputData =
+ {
+ 0.f, 1.f, 0.f, 0.f,
+ .5f, 0.f, 0.f, 0.f
+ };
+};
+
// Helper function that returns either Bias2 or an empty vector depending on whether bias is enabled.
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
boost::multi_array<T, 1> GetBias2(bool biasEnabled, float qScale)
@@ -1647,12 +1677,117 @@
return SimpleSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta);
}
+LayerTestResult<float,2> SimpleAxisSoftmaxTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float beta,
+ int axis)
+{
+ return SimpleSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta, axis);
+}
+
LayerTestResult<float,3> Simple3dSoftmaxTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta)
{
- return Simple3dSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta);
+ Simple3dSoftmaxOutputData data;
+ return Simple3dSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta,
+ data.inputShape, data.outputData, data.inputData);
+}
+
+LayerTestResult<float,3> Simple3dAxisSoftmaxTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float beta,
+ int axis)
+{
+ armnn::TensorShape inputShape;
+ std::vector<float> inputData;
+ std::vector<float> outputData;
+ switch (axis)
+ {
+ case -3:
+ case 0:
+ {
+ inputShape = {5, 2, 2};
+
+ inputData =
+ {
+ 17.0f, -1.0f, 17.0f, -1.0f, 16.0f, -2.0f, 16.0f, -2.0f, 15.0f, -3.0f,
+
+ 15.0f, -3.0f, 14.0f, -4.0f, 14.0f, -4.0f, 1.0f, -17.0f, 1.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.643914213228014f, 0.643914213228014f, 0.643914213228014f,
+ 0.236882800924671f,
+ 0.236882800924671f, 0.236882800924671f, 0.236882800924671f, 0.087144312427294f,
+ 0.087144312427294f,
+
+ 0.087144312427294f, 0.087144312427294f, 0.032058600957022f, 0.032058600957022f,
+ 0.032058600957022f,
+ 0.032058600957022f, 7.246299848982885e-08f, 7.246299848982885e-08f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ case -2:
+ case 1:
+ {
+ inputShape = {2, 5, 2};
+
+ inputData =
+ {
+ 17.0f, -1.0f, 16.0f, -2.0f, 15.0f, -3.0f, 14.0f, -4.0f, 1.0f, -17.0f,
+
+ 17.0f, -1.0f, 16.0f, -2.0f, 15.0f, -3.0f, 14.0f, -4.0f, 1.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.643914213228014f, 0.236882800924671f, 0.236882800924671f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f,
+
+ 0.643914213228014f, 0.643914213228014f, 0.236882800924671f, 0.236882800924671f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ case -1:
+ case 2:
+ {
+ inputShape = {2, 2, 5};
+
+ inputData =
+ {
+ 17.0f, 16.0f, 15.0f, 14.0f, 1.0f, -1.0f, -2.0f, -3.0f, -4.0f, -17.0f,
+ 17.0f, 16.0f, 15.0f, 14.0f, 1.0f, -1.0f, -2.0f, -3.0f, -4.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ }
+
+ return Simple3dSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta,
+ inputShape, outputData, inputData, axis);
}
LayerTestResult<float,4> Simple4dSoftmaxTest(
@@ -1660,7 +1795,167 @@
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta)
{
- return Simple4dSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta);
+ Simple4dSoftmaxData data;
+ return Simple4dSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta, data.inputShape,
+ data.outputData, data.inputData);
+}
+
+LayerTestResult<float,4> Simple4dAxisSoftmaxTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float beta,
+ int axis)
+{
+ armnn::TensorShape inputShape;
+ std::vector<float> inputData;
+ std::vector<float> outputData;
+ switch (axis)
+ {
+ case -4:
+ case 0:
+ {
+ inputShape = {5, 2, 2, 2};
+
+ inputData =
+ {
+ 17.0f, -1.0f, 17.0f, -1.0f, 17.0f, -1.0f, 17.0f, -1.0f, 16.0f, -2.0f,
+ 16.0f, -2.0f, 16.0f, -2.0f, 16.0f, -2.0f, 15.0f, -3.0f, 15.0f, -3.0f,
+ 15.0f, -3.0f, 15.0f, -3.0f, 14.0f, -4.0f, 14.0f, -4.0f, 14.0f, -4.0f,
+ 14.0f, -4.0f, 1.0f, -17.0f, 1.0f, -17.0f, 1.0f, -17.0f, 1.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.643914213228014f, 0.643914213228014f, 0.643914213228014f,
+ 0.643914213228014f,
+ 0.643914213228014f, 0.643914213228014f, 0.643914213228014f, 0.236882800924671f,
+ 0.236882800924671f,
+ 0.236882800924671f, 0.236882800924671f, 0.236882800924671f, 0.236882800924671f,
+ 0.236882800924671f,
+ 0.236882800924671f, 0.087144312427294f, 0.087144312427294f, 0.087144312427294f,
+ 0.087144312427294f,
+
+ 0.087144312427294f, 0.087144312427294f, 0.087144312427294f, 0.087144312427294f,
+ 0.032058600957022f,
+ 0.032058600957022f, 0.032058600957022f, 0.032058600957022f, 0.032058600957022f,
+ 0.032058600957022f,
+ 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f,
+ 7.246299848982885e-08f, 7.246299848982885e-08f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f, 7.246299848982885e-08f
+ };
+ break;
+ }
+ case -3:
+ case 1:
+ {
+ inputShape = {2, 5, 2, 2};
+
+ inputData =
+ {
+ 17.0f, -1.0f, 17.0f, -1.0f, 16.0f, -2.0f, 16.0f, -2.0f, 15.0f, -3.0f,
+ 15.0f, -3.0f, 14.0f, -4.0f, 14.0f, -4.0f, 1.0f, -17.0f, 1.0f, -17.0f,
+ 17.0f, -1.0f, 17.0f, -1.0f, 16.0f, -2.0f, 16.0f, -2.0f, 15.0f, -3.0f,
+ 15.0f, -3.0f, 14.0f, -4.0f, 14.0f, -4.0f, 1.0f, -17.0f, 1.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.643914213228014f, 0.643914213228014f, 0.643914213228014f,
+ 0.236882800924671f,
+ 0.236882800924671f, 0.236882800924671f, 0.236882800924671f, 0.087144312427294f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.087144312427294f, 0.032058600957022f, 0.032058600957022f,
+ 0.032058600957022f,
+ 0.032058600957022f, 7.246299848982885e-08f, 7.246299848982885e-08f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f,
+
+
+ 0.643914213228014f, 0.643914213228014f, 0.643914213228014f, 0.643914213228014f,
+ 0.236882800924671f,
+ 0.236882800924671f, 0.236882800924671f, 0.236882800924671f, 0.087144312427294f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.087144312427294f, 0.032058600957022f, 0.032058600957022f,
+ 0.032058600957022f,
+ 0.032058600957022f, 7.246299848982885e-08f, 7.246299848982885e-08f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ case -2:
+ case 2:
+ {
+ inputShape = {2, 2, 5, 2};
+
+ inputData =
+ {
+ 17.0f, -1.0f, 16.0f, -2.0f, 15.0f, -3.0f, 14.0f, -4.0f, 1.0f, -17.0f,
+ 17.0f, -1.0f, 16.0f, -2.0f, 15.0f, -3.0f, 14.0f, -4.0f, 1.0f, -17.0f,
+ 17.0f, -1.0f, 16.0f, -2.0f, 15.0f, -3.0f, 14.0f, -4.0f, 1.0f, -17.0f,
+ 17.0f, -1.0f, 16.0f, -2.0f, 15.0f, -3.0f, 14.0f, -4.0f, 1.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.643914213228014f, 0.236882800924671f, 0.236882800924671f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.643914213228014f, 0.236882800924671f, 0.236882800924671f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f,
+
+ 0.643914213228014f, 0.643914213228014f, 0.236882800924671f, 0.236882800924671f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.643914213228014f, 0.236882800924671f, 0.236882800924671f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ case -1:
+ case 3:
+ {
+ inputShape = {2, 2, 2, 5};
+
+ inputData =
+ {
+ 17.0f, 16.0f, 15.0f, 14.0f, 1.0f, -1.0f, -2.0f, -3.0f, -4.0f, -17.0f,
+ 17.0f, 16.0f, 15.0f, 14.0f, 1.0f, -1.0f, -2.0f, -3.0f, -4.0f, -17.0f,
+ 17.0f, 16.0f, 15.0f, 14.0f, 1.0f, -1.0f, -2.0f, -3.0f, -4.0f, -17.0f,
+ 17.0f, 16.0f, 15.0f, 14.0f, 1.0f, -1.0f, -2.0f, -3.0f, -4.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ }
+
+ return Simple4dSoftmaxTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, beta, inputShape,
+ outputData, inputData, axis);
}
LayerTestResult<uint8_t,2> SimpleSoftmaxUint8Test(
@@ -1676,7 +1971,9 @@
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta)
{
- return Simple3dSoftmaxTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, beta);
+ Simple3dSoftmaxOutputData data;
+ return Simple3dSoftmaxTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, beta,
+ data.inputShape, data.outputData, data.inputData);
}
LayerTestResult<uint8_t,4> Simple4dSoftmaxUint8Test(
@@ -1684,7 +1981,10 @@
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta)
{
- return Simple4dSoftmaxTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, beta);
+ Simple4dSoftmaxData data;
+
+ return Simple4dSoftmaxTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, beta,
+ data.inputShape, data.outputData, data.inputData);
}
LayerTestResult<int16_t,2> SimpleSoftmaxUint16Test(
@@ -1700,7 +2000,9 @@
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta)
{
- return Simple3dSoftmaxTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, beta);
+ Simple3dSoftmaxOutputData data;
+ return Simple3dSoftmaxTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, beta,
+ data.inputShape, data.outputData, data.inputData);
}
LayerTestResult<int16_t,4> Simple4dSoftmaxUint16Test(
@@ -1708,7 +2010,10 @@
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta)
{
- return Simple4dSoftmaxTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, beta);
+ Simple4dSoftmaxData data;
+
+ return Simple4dSoftmaxTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, beta,
+ data.inputShape, data.outputData, data.inputData);
}
LayerTestResult<float,4> CompareNormalizationTest(
diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index d99e3b4..913c3a6 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -472,16 +472,34 @@
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta);
+LayerTestResult<float, 2> SimpleAxisSoftmaxTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float beta,
+ int axis);
+
LayerTestResult<float, 3> Simple3dSoftmaxTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta);
+LayerTestResult<float, 3> Simple3dAxisSoftmaxTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float beta,
+ int axis);
+
LayerTestResult<float, 4> Simple4dSoftmaxTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta);
+LayerTestResult<float, 4> Simple4dAxisSoftmaxTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float beta,
+ int axis);
+
LayerTestResult<uint8_t, 2> SimpleSoftmaxUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
diff --git a/src/backends/backendsCommon/test/SoftmaxTestImpl.hpp b/src/backends/backendsCommon/test/SoftmaxTestImpl.hpp
index 8081950..983a53b 100644
--- a/src/backends/backendsCommon/test/SoftmaxTestImpl.hpp
+++ b/src/backends/backendsCommon/test/SoftmaxTestImpl.hpp
@@ -25,7 +25,9 @@
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
float beta,
const armnn::TensorShape& inputShape,
- const std::vector<float>& outputData)
+ const std::vector<float>& outputData,
+ const std::vector<float>& inputData,
+ int axis = 1)
{
using std::exp;
@@ -47,16 +49,14 @@
// Each row is independently softmax'd.
auto input = MakeTensor<T, n>(inputTensorInfo, std::vector<T>(
- QuantizedVector<T>(qScale, qOffset, {
- 0.f, 1.f, 0.f, 0.f,
- .5f, 0.f, 0.f, 0.f,
- })));
+ QuantizedVector<T>(qScale, qOffset, inputData)));
std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
armnn::SoftmaxQueueDescriptor data;
data.m_Parameters.m_Beta = beta;
+ data.m_Parameters.m_Axis = axis;
armnn::WorkloadInfo info;
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
@@ -100,33 +100,98 @@
const std::vector<float> outputData = { x0[0] / sum0, x0[1] / sum0, x0[2] / sum0, x0[3] / sum0,
x1[0] / sum1, x1[1] / sum1, x1[2] / sum1, x1[3] / sum1 };
- return SimpleSoftmaxBaseTestImpl<ArmnnType, 2>(workloadFactory, memoryManager, beta, inputShape, outputData);
+ const std::vector<float> inputData =
+ {
+ 0.f, 1.f, 0.f, 0.f,
+ .5f, 0.f, 0.f, 0.f,
+ };
+
+ return SimpleSoftmaxBaseTestImpl<ArmnnType, 2>(workloadFactory, memoryManager, beta,
+ inputShape, outputData, inputData);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 2> SimpleSoftmaxTestImpl(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ float beta,
+ int axis)
+{
+ armnn::TensorShape inputShape;
+ std::vector<float> inputData;
+ std::vector<float> outputData;
+ switch (axis)
+ {
+ case -2:
+ case 0:
+ {
+ inputShape = {5, 2};
+
+ inputData =
+ {
+ 17.0f, -1.0f, 16.0f, -2.0f, 15.0f, -3.0f, 14.0f, -4.0f, 1.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.643914213228014f, 0.236882800924671f, 0.236882800924671f,
+ 0.087144312427294f,
+ 0.087144312427294f, 0.032058600957022f, 0.032058600957022f, 7.246299848982885e-08f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ case -1:
+ case 1:
+ {
+ inputShape = {2, 5};
+
+ inputData =
+ {
+ 17.0f, 16.0f, 15.0f, 14.0f, 1.0f, -1.0f, -2.0f, -3.0f, -4.0f, -17.0f
+ };
+
+ outputData =
+ {
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f,
+ 0.643914213228014f, 0.236882800924671f, 0.087144312427294f, 0.032058600957022f,
+ 7.246299848982885e-08f
+ };
+ break;
+ }
+ }
+ return SimpleSoftmaxBaseTestImpl<ArmnnType, 2>(workloadFactory, memoryManager, beta,
+ inputShape, outputData, inputData, axis);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 3> Simple3dSoftmaxTestImpl(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- float beta)
+ float beta,
+ const armnn::TensorShape& inputShape,
+ const std::vector<float>& outputData,
+ const std::vector<float>& inputData,
+ int axis = 1)
{
- const armnn::TensorShape inputShape{ 1, 8, 1 };
- const std::vector<float> outputData = { 0.0964599f, 0.26220518f, 0.0964599f, 0.0964599f,
- 0.15903549f, 0.0964599f, 0.0964599f, 0.0964599f };
-
- return SimpleSoftmaxBaseTestImpl<ArmnnType, 3>(workloadFactory, memoryManager, beta, inputShape, outputData);
+ return SimpleSoftmaxBaseTestImpl<ArmnnType, 3>(workloadFactory, memoryManager, beta,
+ inputShape, outputData, inputData, axis);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> Simple4dSoftmaxTestImpl(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- float beta)
+ float beta,
+ const armnn::TensorShape& inputShape,
+ const std::vector<float>& outputData,
+ const std::vector<float>& inputData,
+ int axis = 1)
{
- const armnn::TensorShape inputShape{ 1, 8, 1, 1 };
- const std::vector<float> outputData = { 0.0964599f, 0.26220518f, 0.0964599f, 0.0964599f,
- 0.15903549f, 0.0964599f, 0.0964599f, 0.0964599f };
- return SimpleSoftmaxBaseTestImpl<ArmnnType, 4>(workloadFactory, memoryManager, beta, inputShape, outputData);
+ return SimpleSoftmaxBaseTestImpl<ArmnnType, 4>(workloadFactory, memoryManager, beta,
+ inputShape, outputData, inputData, axis);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>