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-rw-r--r--test/1.1/Mean.cpp201
1 files changed, 152 insertions, 49 deletions
diff --git a/test/1.1/Mean.cpp b/test/1.1/Mean.cpp
index c9a5a6d3..c7c5a9b5 100644
--- a/test/1.1/Mean.cpp
+++ b/test/1.1/Mean.cpp
@@ -8,12 +8,10 @@
#include "../1.1/HalPolicy.hpp"
-#include <boost/test/data/test_case.hpp>
+#include <doctest/doctest.h>
#include <array>
-BOOST_AUTO_TEST_SUITE(MeanTests)
-
using namespace android::hardware;
using namespace driverTestHelpers;
using namespace armnn_driver;
@@ -24,12 +22,6 @@ using RequestArgument = V1_0::RequestArgument;
namespace
{
-#ifndef ARMCOMPUTECL_ENABLED
- static const std::array<armnn::Compute, 1> COMPUTE_DEVICES = {{ armnn::Compute::CpuRef }};
-#else
- static const std::array<armnn::Compute, 2> COMPUTE_DEVICES = {{ armnn::Compute::CpuRef, armnn::Compute::GpuAcc }};
-#endif
-
void MeanTestImpl(const TestTensor& input,
const hidl_vec<uint32_t>& axisDimensions,
const int32_t* axisValues,
@@ -94,64 +86,175 @@ void MeanTestImpl(const TestTensor& input,
if (preparedModel.get() != nullptr)
{
V1_0::ErrorStatus execStatus = Execute(preparedModel, request);
- BOOST_TEST(execStatus == V1_0::ErrorStatus::NONE);
+ CHECK((int)execStatus == (int)V1_0::ErrorStatus::NONE);
}
const float* expectedOutputData = expectedOutput.GetData();
for (unsigned int i = 0; i < expectedOutput.GetNumElements(); i++)
{
- BOOST_TEST(outputData[i] == expectedOutputData[i]);
+ CHECK(outputData[i] == expectedOutputData[i]);
}
}
} // anonymous namespace
-BOOST_DATA_TEST_CASE(MeanNoKeepDimsTest, COMPUTE_DEVICES)
+TEST_SUITE("MeanTests_CpuRef")
{
- TestTensor input{ armnn::TensorShape{ 4, 3, 2 }, { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
- 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
- 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
- hidl_vec<uint32_t> axisDimensions = { 2 };
- int32_t axisValues[] = { 0, 1 };
- int32_t keepDims = 0;
- TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
-
- MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, sample);
-}
+ TEST_CASE("MeanNoKeepDimsTest_CpuRef")
+ {
+ TestTensor input{ armnn::TensorShape{ 4, 3, 2 },
+ { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
+ 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
+ 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 2 };
+ int32_t axisValues[] = { 0, 1 };
+ int32_t keepDims = 0;
+ TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, armnn::Compute::CpuRef);
+ }
-BOOST_DATA_TEST_CASE(MeanKeepDimsTest, COMPUTE_DEVICES)
-{
- TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
- hidl_vec<uint32_t> axisDimensions = { 1 };
- int32_t axisValues[] = { 2 };
- int32_t keepDims = 1;
- TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
+ TEST_CASE("MeanKeepDimsTest_CpuRef")
+ {
+ TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 1 };
+ int32_t axisValues[] = { 2 };
+ int32_t keepDims = 1;
+ TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, armnn::Compute::CpuRef);
+ }
+
+ TEST_CASE("MeanFp16NoKeepDimsTest_CpuRef")
+ {
+ TestTensor input{ armnn::TensorShape{ 4, 3, 2 },
+ { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
+ 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
+ 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 2 };
+ int32_t axisValues[] = { 0, 1 };
+ int32_t keepDims = 0;
+ TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuRef);
+ }
+
+ TEST_CASE("MeanFp16KeepDimsTest_CpuRef")
+ {
+ TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 1 };
+ int32_t axisValues[] = { 2 };
+ int32_t keepDims = 1;
+ TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
- MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, sample);
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuRef);
+ }
}
-BOOST_DATA_TEST_CASE(MeanFp16NoKeepDimsTest, COMPUTE_DEVICES)
+#ifdef ARMCOMPUTECL_ENABLED
+TEST_SUITE("MeanTests_CpuAcc")
{
- TestTensor input{ armnn::TensorShape{ 4, 3, 2 }, { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
- 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
- 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
- hidl_vec<uint32_t> axisDimensions = { 2 };
- int32_t axisValues[] = { 0, 1 };
- int32_t keepDims = 0;
- TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
-
- MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, sample);
+ TEST_CASE("MeanNoKeepDimsTest_CpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 4, 3, 2 },
+ { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
+ 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
+ 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 2 };
+ int32_t axisValues[] = { 0, 1 };
+ int32_t keepDims = 0;
+ TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, armnn::Compute::CpuAcc);
+ }
+
+ TEST_CASE("MeanKeepDimsTest_CpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 1 };
+ int32_t axisValues[] = { 2 };
+ int32_t keepDims = 1;
+ TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, armnn::Compute::CpuAcc);
+ }
+
+ TEST_CASE("MeanFp16NoKeepDimsTest_CpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 4, 3, 2 },
+ { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
+ 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
+ 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 2 };
+ int32_t axisValues[] = { 0, 1 };
+ int32_t keepDims = 0;
+ TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuAcc);
+ }
+
+ TEST_CASE("MeanFp16KeepDimsTest_CpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 1 };
+ int32_t axisValues[] = { 2 };
+ int32_t keepDims = 1;
+ TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuAcc);
+ }
}
-BOOST_DATA_TEST_CASE(MeanFp16KeepDimsTest, COMPUTE_DEVICES)
+TEST_SUITE("MeanTests_GpuAcc")
{
- TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
- hidl_vec<uint32_t> axisDimensions = { 1 };
- int32_t axisValues[] = { 2 };
- int32_t keepDims = 1;
- TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
+ TEST_CASE("MeanNoKeepDimsTest_GpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 4, 3, 2 },
+ { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
+ 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
+ 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 2 };
+ int32_t axisValues[] = { 0, 1 };
+ int32_t keepDims = 0;
+ TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, armnn::Compute::GpuAcc);
+ }
- MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, sample);
-}
+ TEST_CASE("MeanKeepDimsTest_GpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 1 };
+ int32_t axisValues[] = { 2 };
+ int32_t keepDims = 1;
+ TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
-BOOST_AUTO_TEST_SUITE_END()
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, false, armnn::Compute::GpuAcc);
+ }
+
+ TEST_CASE("MeanFp16NoKeepDimsTest_GpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 4, 3, 2 },
+ { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f,
+ 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f,
+ 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 2 };
+ int32_t axisValues[] = { 0, 1 };
+ int32_t keepDims = 0;
+ TestTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0f, 13.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::GpuAcc);
+ }
+
+ TEST_CASE("MeanFp16KeepDimsTest_GpuAcc")
+ {
+ TestTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f } };
+ hidl_vec<uint32_t> axisDimensions = { 1 };
+ int32_t axisValues[] = { 2 };
+ int32_t keepDims = 1;
+ TestTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, { 2.0f, 2.0f } };
+
+ MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::GpuAcc);
+ }
+}
+#endif
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