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author | Andrew Mundy <andrew.mundy@arm.com> | 2018-03-15 16:47:03 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:49:16 +0000 |
commit | 4d9379a9d3ada794f532ce8acdc8607f4faa2b21 (patch) | |
tree | 14ba02ebcdaf6cb927e9422e45cbab6456c9a097 /tests/validation/NEON | |
parent | 3f217ec4ff11e20fe686beb9a28d0bbd80a56cd6 (diff) | |
download | ComputeLibrary-4d9379a9d3ada794f532ce8acdc8607f4faa2b21.tar.gz |
COMPMID-1040: Added support for nullptr bias tensor in NEWinogradLayer
Change-Id: Ie624ee17c63dede711d913a82819e128954a57c9
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/124861
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/validation/NEON')
-rw-r--r-- | tests/validation/NEON/ConvolutionLayer.cpp | 43 | ||||
-rw-r--r-- | tests/validation/NEON/DilatedConvolutionLayer.cpp | 30 |
2 files changed, 37 insertions, 36 deletions
diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp index 27216af6d1..3a365253cb 100644 --- a/tests/validation/NEON/ConvolutionLayer.cpp +++ b/tests/validation/NEON/ConvolutionLayer.cpp @@ -76,22 +76,17 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo TEST_SUITE(NEON) TEST_SUITE(ConvolutionLayer) -DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0), - TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), - TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) - }), - framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) - })), - framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(1U), 1, DataType::F32, 0), - TensorInfo(TensorShape(21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(16U), 1, DataType::F32, 0) - })), +DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) + })), framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(6U, 6U, 1U), 1, DataType::F32, 0), TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0), TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0), @@ -103,11 +98,10 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z PadStrideInfo(3, 2, 1, 0) })), framework::dataset::make("Expected", { ConvolutionMethod::WINOGRAD, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), - input_info, weights_info, biases_info, output_info, conv_info, expected) + input_info, weights_info, output_info, conv_info, expected) { ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), - &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } @@ -117,6 +111,9 @@ TEST_SUITE(WinogradLayer) template <typename T> using NEWinogradConvolutionLayerFixture = WinogradConvolutionLayerValidationFixture<Tensor, Accessor, NEWinogradLayer, T>; +template <typename T> +using NEWinogradConvolutionLayerNoBiasFixture = WinogradConvolutionLayerValidationFixture<Tensor, Accessor, NEWinogradLayer, T, false>; + TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(framework::dataset::concat(datasets::SmallWinogradConvolutionLayer3x3Dataset(), @@ -128,6 +125,16 @@ FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, frame validate(Accessor(_target), _reference, tolerance_f32); } +FIXTURE_DATA_TEST_CASE(RunSmallNoBias, NEWinogradConvolutionLayerNoBiasFixture<float>, framework::DatasetMode::PRECOMMIT, + combine(combine(framework::dataset::concat(datasets::SmallWinogradConvolutionLayer3x3Dataset(), + datasets::SmallWinogradConvolutionLayer5x5Dataset()), + framework::dataset::make("DataType", { DataType::F32 })), + ActivationFunctionsDataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f32); +} + TEST_SUITE_END() TEST_SUITE_END() diff --git a/tests/validation/NEON/DilatedConvolutionLayer.cpp b/tests/validation/NEON/DilatedConvolutionLayer.cpp index 1e8c19fc5e..358cec3d6f 100644 --- a/tests/validation/NEON/DilatedConvolutionLayer.cpp +++ b/tests/validation/NEON/DilatedConvolutionLayer.cpp @@ -66,22 +66,17 @@ const auto CNNDataTypes = framework::dataset::make("DataType", TEST_SUITE(NEON) TEST_SUITE(DilatedConvolutionLayer) -DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0), - TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), - TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) - }), - framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) - })), - framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(1U), 1, DataType::F32, 0), - TensorInfo(TensorShape(21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(21U), 1, DataType::F32, 0), - TensorInfo(TensorShape(16U), 1, DataType::F32, 0) - })), +DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(8U, 8U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0), + TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0) + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0) + })), framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(6U, 6U, 1U), 1, DataType::F32, 0), TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0), TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0), @@ -98,11 +93,10 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z Size2D(3U, 3U) })), framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })), - input_info, weights_info, biases_info, output_info, conv_info, dilation, expected) + input_info, weights_info, output_info, conv_info, dilation, expected) { ConvolutionMethod is_valid = NEConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), - &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), dilation); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); |