COMPMID-1652 CL Cleanup and add missing tests
Change-Id: I359cc0fd0c3fa42ab10a770e59d58704403889b2
Reviewed-on: https://review.mlplatform.org/498
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Isabella Gottardi <isabella.gottardi@arm.com>
diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp
index 5f10b4b..f347d54 100644
--- a/tests/validation/CL/ConvolutionLayer.cpp
+++ b/tests/validation/CL/ConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -18,7 +18,7 @@
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/core/Types.h"
@@ -73,74 +73,84 @@
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f)
});
+const auto ActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f)
+});
} // namespace
TEST_SUITE(CL)
TEST_SUITE(ConvolutionLayer)
+// *INDENT-OFF*
+// clang-format off
DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
- framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32),
- TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32),
- TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(23U, 27U, 31U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32),
- TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32),
- TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32)
- }),
- framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32),
- TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 3U, 31U, 21U), 1, DataType::F32),
- TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
- TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16),
- TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32),
- TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32)
- })),
- framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
- TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
- TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32),
- TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32),
- TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32),
- TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32)
- })),
- framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1),
- PadStrideInfo(1, 2, 1, 1),
- PadStrideInfo(1, 1, 0, 0),
- PadStrideInfo(1, 1, 0, 0),
- PadStrideInfo(2, 1, 0, 0),
- PadStrideInfo(3, 2, 1, 0),
- PadStrideInfo(1, 1, 2, 2),
- PadStrideInfo(1, 1, 2, 2)
- })),
- framework::dataset::make("GpuTarget", { GPUTarget::BIFROST,
- GPUTarget::MIDGARD,
- GPUTarget::G71,
- GPUTarget::G71,
- GPUTarget::MIDGARD,
- GPUTarget::BIFROST,
- GPUTarget::BIFROST,
- GPUTarget::BIFROST
- })),
- framework::dataset::make("Dilation",
-{
- Size2D(1U, 1U),
- Size2D(1U, 1U),
- Size2D(1U, 1U),
- Size2D(1U, 1U),
- Size2D(1U, 1U),
- Size2D(1U, 1U),
- Size2D(1U, 1U),
- Size2D(2U, 1U),
-})),
-framework::dataset::make("EnableFastMath", { false, false, false, false, false, false, true, true })),
-framework::dataset::make("Expected",
-{
- ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::WINOGRAD, ConvolutionMethod::GEMM,
-})),
-input_info, weights_info, output_info, conv_info, gpu_target, dilation, enable_fast_math, expected)
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Select GEMM
+ TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), // Select GEMM
+ TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), // Select GEMM
+ TensorInfo(TensorShape(23U, 27U, 31U, 4U), 1, DataType::F32), // Select WINOGRAD
+ TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32), // Select GEMM
+ TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32), // Select GEMM
+ TensorInfo(TensorShape(17U, 31U, 32U), 1, DataType::F32), // Select WINOGRAD
+ TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32) // Select GEMM
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(3U, 3U, 31U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16),
+ TensorInfo(TensorShape(5U, 5U, 32U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32)
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32),
+ TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32),
+ TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32)
+ })),
+ framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1),
+ PadStrideInfo(1, 2, 1, 1),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(3, 2, 1, 0),
+ PadStrideInfo(1, 1, 2, 2),
+ PadStrideInfo(1, 1, 2, 2)
+ })),
+ framework::dataset::make("GpuTarget", { GPUTarget::BIFROST,
+ GPUTarget::MIDGARD,
+ GPUTarget::G71,
+ GPUTarget::G71,
+ GPUTarget::MIDGARD,
+ GPUTarget::BIFROST,
+ GPUTarget::BIFROST,
+ GPUTarget::BIFROST
+ })),
+ framework::dataset::make("Dilation", { Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(2U, 1U),
+ })),
+ framework::dataset::make("EnableFastMath", { false, false, false, false, false, false, true, true })),
+ framework::dataset::make("Expected",{ ConvolutionMethod::GEMM,
+ ConvolutionMethod::GEMM,
+ ConvolutionMethod::GEMM,
+ ConvolutionMethod::WINOGRAD,
+ ConvolutionMethod::GEMM,
+ ConvolutionMethod::GEMM,
+ ConvolutionMethod::WINOGRAD,
+ ConvolutionMethod::GEMM,
+ })),
+ input_info, weights_info, output_info, conv_info, gpu_target, dilation, enable_fast_math, expected)
{
ConvolutionMethod is_valid = CLConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(true),
&weights_info.clone()->set_is_resizable(true),
@@ -152,11 +162,13 @@
enable_fast_math);
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
-TEST_SUITE_END()
+// clang-format on
+// *INDENT-ON*
+TEST_SUITE_END() // ConvolutionLayer
TEST_SUITE(GEMMConvolutionLayer)
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()),
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::SmallConvolutionLayerDataset(),
CNNDataTypes),
ActivationFunctionsDataset),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
@@ -206,23 +218,24 @@
TEST_SUITE(Float)
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType",
DataType::F16)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- ActivationFunctionsDataset))
+ ActivationFunctionsSmallDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType",
- DataType::F16)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- ActivationFunctionsDataset))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ ActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
@@ -231,23 +244,24 @@
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType",
DataType::F32)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- ActivationFunctionsDataset))
+ ActivationFunctionsSmallDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType",
- DataType::F32)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- ActivationFunctionsDataset))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ ActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, absolute_tolerance_float);
@@ -264,6 +278,11 @@
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f)
});
+const auto QuantizedActivationFunctionsSmallDataset = framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f)
+});
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
@@ -275,22 +294,24 @@
QuantizationInfo(1.f, 10),
});
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- QuantizationData),
- QuantizedActivationFunctionsDataset))
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ QuantizationData),
+ QuantizedActivationFunctionsSmallDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType", DataType::QASYMM8)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- QuantizationData),
- QuantizedActivationFunctionsDataset))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ QuantizationData),
+ QuantizedActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qasymm8);
@@ -305,7 +326,7 @@
TEST_SUITE(GroupedGEMMConvolutionLayer)
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()),
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
GroupedCNNDataTypes),
ActivationFunctionsDataset),
input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info)
@@ -348,21 +369,22 @@
TEST_SUITE(Float)
TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType", DataType::F32)),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
- ActivationFunctionsDataset))
+ ActivationFunctionsSmallDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeGroupedConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW })),
- ActivationFunctionsDataset))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ ActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
@@ -371,21 +393,22 @@
TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallGroupedConvolutionLayerDataset(),
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerReducedDataset(),
framework::dataset::make("ReshapeWeights", { true })),
framework::dataset::make("DataType", DataType::F16)),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
- ActivationFunctionsDataset))
+ ActivationFunctionsSmallDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeGroupedConvolutionLayerDataset(),
- framework::dataset::make("ReshapeWeights", { true })),
- framework::dataset::make("DataType", DataType::F16)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW })),
- ActivationFunctionsDataset))
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMGroupedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(combine(framework::dataset::concat(datasets::SmallGroupedConvolutionLayerDataset(), datasets::LargeGroupedConvolutionLayerDataset()),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })),
+ ActivationFunctionsDataset))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32, tolerance_num);