diff options
Diffstat (limited to 'tests/validation/NEON/DirectConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/NEON/DirectConvolutionLayer.cpp | 27 |
1 files changed, 27 insertions, 0 deletions
diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp index fe61a9d98a..88578ca586 100644 --- a/tests/validation/NEON/DirectConvolutionLayer.cpp +++ b/tests/validation/NEON/DirectConvolutionLayer.cpp @@ -98,6 +98,25 @@ const auto data_f16_nightly = combine(data_f16, framework::dataset::make("NumKer const auto data_precommit = combine(data, framework::dataset::make("NumKernels", { 1 })); const auto data_precommit9x9 = combine(data9x9, framework::dataset::make("NumKernels", { 4 })); +/* The following tests is from real use-case that made DirectConvolution + * overflows in terms of its tensor indexing. This test case is using + * a separate tolerance due to the following reason. + * - It has shown that it requires generally larger absolute tolerance + * for large numbers or larger relative tolerance for small numbers. + * - With the first reason, since it is mainly testing index overflow, + * a value with a margin is used to avoid uninteded test failures + * during nightly. + */ +constexpr AbsoluteTolerance<float> usecase_tolerance_fp32(0.05f); + +const auto data_nightly_usecase = combine(framework::dataset::make("InputShape", { TensorShape{ 3U, 800U, 800U } }), + combine(framework::dataset::make("StrideX", { 1 }), + combine(framework::dataset::make("StrideY", { 1 }), + combine(framework::dataset::make("PadX", { 4 }), + combine(framework::dataset::make("PadY", { 4 }), + combine(framework::dataset::make("KernelSize", 9), + framework::dataset::make("NumKernels", { 16 }))))))); + /** Activation function Dataset*/ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", { @@ -227,6 +246,14 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEDirectConvolutionLayerFixture<float>, framewo // Validate output validate(Accessor(_target), _reference, tolerance_fp32); } +FIXTURE_DATA_TEST_CASE(RunLargeUsecase, NEDirectConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(data_nightly_usecase, framework::dataset::make("DataType", + DataType::F32)), + framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })), + framework::dataset::make("DataLayout", { DataLayout::NHWC }))) +{ + // Validate output + validate(Accessor(_target), _reference, usecase_tolerance_fp32); +} TEST_SUITE_END() // FP32 TEST_SUITE_END() // Float TEST_SUITE_END() // DirectConvolutionLayer |