IVGCVSW-4064 ArmNN Master fails due to an error in RefArgMaxAxis2Uint8Test
* Fix input data to allow for loss of precision due to valgrind which
causes incorrect quantization of multiples of 5 with scale of 2.
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
Change-Id: I354dcb8117e1ab07771b78d0e4808d9f3f95925b
diff --git a/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp
index 3bb1dd6..ba804bf 100644
--- a/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/ArgMinMaxEndToEndTestImpl.hpp
@@ -71,7 +71,7 @@
const armnn::TensorShape inputShape{ 1, 1, 1, 5 };
const armnn::TensorShape outputShape{ 1, 1, 1 };
- std::vector<float> inputData({ 5.0f, 2.0f, 8.0f, 10.0f, 9.0f });
+ std::vector<float> inputData({ 6.0f, 2.0f, 8.0f, 10.0f, 9.0f });
std::vector<int32_t> expectedOutputData({ 3 });
ArgMinMaxEndToEndImpl<ArmnnType>(inputShape,
@@ -89,7 +89,7 @@
const armnn::TensorShape inputShape{ 1, 1, 1, 5 };
const armnn::TensorShape outputShape{ 1, 1, 1 };
- std::vector<float> inputData({ 5.0f, 2.0f, 8.0f, 10.0f, 9.0f });
+ std::vector<float> inputData({ 6.0f, 2.0f, 8.0f, 10.0f, 9.0f });
std::vector<int32_t> expectedOutputData({ 1 });
ArgMinMaxEndToEndImpl<ArmnnType>(inputShape,
@@ -108,9 +108,9 @@
const armnn::TensorShape outputShape{ 2, 1, 4 };
std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f,
- 8.0f, 7.0f, 6.0f, 5.0f,
+ 8.0f, 7.0f, 6.0f, 6.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
50.0f, 60.0f, 70.0f, 80.0f,
10.0f, 200.0f, 30.0f, 400.0f });
@@ -133,9 +133,9 @@
const armnn::TensorShape outputShape{ 2, 1, 4 };
std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f,
- 8.0f, 7.0f, 6.0f, 5.0f,
+ 8.0f, 7.0f, 6.0f, 6.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
50.0f, 60.0f, 70.0f, 80.0f,
10.0f, 200.0f, 30.0f, 400.0f });
@@ -158,9 +158,9 @@
const armnn::TensorShape outputShape{ 1, 2, 4 };
std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f,
- 8.0f, 7.0f, 6.0f, 5.0f,
+ 8.0f, 7.0f, 6.0f, 6.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
50.0f, 60.0f, 70.0f, 80.0f,
10.0f, 200.0f, 30.0f, 400.0f });
@@ -183,9 +183,9 @@
const armnn::TensorShape outputShape{ 1, 2, 4 };
std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f,
- 8.0f, 7.0f, 6.0f, 5.0f,
+ 8.0f, 7.0f, 6.0f, 6.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
50.0f, 60.0f, 70.0f, 80.0f,
10.0f, 200.0f, 30.0f, 400.0f });
@@ -208,9 +208,9 @@
const armnn::TensorShape outputShape{ 1, 3, 4 };
std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f,
- 8.0f, 7.0f, 6.0f, 5.0f,
+ 8.0f, 7.0f, 6.0f, 6.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
10.0f, 200.0f, 30.0f, 400.0f,
50.0f, 60.0f, 70.0f, 80.0f });
@@ -234,9 +234,9 @@
const armnn::TensorShape outputShape{ 1, 3, 4 };
std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f,
- 8.0f, 7.0f, 6.0f, 5.0f,
+ 8.0f, 7.0f, 6.0f, 6.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
10.0f, 200.0f, 30.0f, 400.0f,
50.0f, 60.0f, 70.0f, 80.0f });
@@ -259,10 +259,10 @@
const armnn::TensorShape inputShape{ 1, 3, 2, 4 };
const armnn::TensorShape outputShape{ 1, 3, 2 };
- std::vector<float> inputData({ 1.0f, 3.0f, 5.0f, 7.0f,
- 8.0f, 7.0f, 6.0f, 5.0f,
+ std::vector<float> inputData({ 1.0f, 3.0f, 6.0f, 7.0f,
+ 8.0f, 7.0f, 6.0f, 6.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
10.0f, 200.0f, 30.0f, 400.0f,
50.0f, 60.0f, 70.0f, 80.0f });
@@ -285,10 +285,10 @@
const armnn::TensorShape inputShape{ 1, 3, 2, 4 };
const armnn::TensorShape outputShape{ 1, 3, 2 };
- std::vector<float> inputData({ 1.0f, 3.0f, 5.0f, 7.0f,
+ std::vector<float> inputData({ 1.0f, 3.0f, 6.0f, 7.0f,
18.0f, 16.0f, 14.0f, 12.0f,
100.0f, 20.0f, 300.0f, 40.0f,
- 500.0f, 475.0f, 450.0f, 425.0f,
+ 500.0f, 476.0f, 450.0f, 426.0f,
10.0f, 200.0f, 30.0f, 400.0f,
50.0f, 60.0f, 70.0f, 80.0f });