30 #include "tests/datasets/DepthwiseConvolutionLayerDataset.h" 35 #include "tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h" 46 constexpr RelativeTolerance<float> tolerance_f32(0.01f);
47 constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1);
48 constexpr
float tolerance_num = 0.05f;
150 framework::dataset::make(
"Expected", {
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
true,
true })),
215 bool is_valid = bool(
CLDepthwiseConvolutionLayer::validate(&
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, depth_multiplier));
221 template <
typename T>
224 template <
typename T>
232 datasets::SmallDepthwiseConvolutionLayerDataset3x3NCHW()),
273 datasets::SmallDepthwiseConvolutionLayerDataset3x3NCHW()),
311 template <
typename T>
313 template <
typename T>
322 framework::dataset::
make("
DataType", DataType::QASYMM8)),
341 framework::dataset::
make("DepthMultiplier", 1)),
342 framework::dataset::
make("
DataType", DataType::QASYMM8)),
half_float::half half
16-bit floating point type
1 channel, 1 F32 per channel
std::enable_if< is_container< T >::value, ContainerDataset< T > >::type make(std::string name, T &&values)
Helper function to create a ContainerDataset.
Activation Layer Information class.
This file contains all available output stages for GEMMLowp on OpenCL.
1 channel, 1 F16 per channel
DepthwiseConvolutionLayerValidationFixture< CLTensor, CLAccessor, CLDepthwiseConvolutionLayer3x3, T > CLDepthwiseConvolutionLayerFixture3x3
#define TEST_SUITE(SUITE_NAME)
1 channel, 1 S32 per channel
DepthwiseConvolutionLayerValidationQuantizedFixture< CLTensor, CLAccessor, CLDepthwiseConvolutionLayer3x3, T > CLDepthwiseConvolutionLayerQuantizedFixture3x3
FIXTURE_DATA_TEST_CASE(RunSmall, CLAbsoluteDifferenceFixture< uint8_t >, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), AbsoluteDifferenceU8Dataset))
validate(dst.info() ->valid_region(), dst_valid_region)
DatasetMode
Possible dataset modes.
quantized, asymmetric fixed-point 8-bit number
Accessor implementation for CLTensor objects.
Padding and stride information class.
Num samples, channels, height, width.
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), AbsoluteDifferenceU8Dataset), shape, data_type0, data_type1, output_data_type)
TEST_SUITE_END() DATA_TEST_CASE(Configuration
ARM_COMPUTE_EXPECT(src.info() ->is_resizable(), framework::LogLevel::ERRORS)
Num samples, height, width, channels.
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier=1, ActivationLayerInfo act_info=ActivationLayerInfo(), GPUTarget gpu_target=GPUTarget::MIDGARD)
Static function to check if given info will lead to a valid configuration of CLDepthwiseConvolutionLa...
combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType",{DataType::U8, DataType::S16})), datasets::BorderModes()), framework::dataset::make("filter_size",{5}))
Store the tensor's metadata.
JoinDataset< T, U > concat(T &&dataset1, U &&dataset2)
Helper function to create a JoinDataset.
Quantization settings (used for QASYMM8 data type)
DepthwiseConvolutionLayerValidationFixture< CLTensor, CLAccessor, CLDepthwiseConvolutionLayer, T > CLDepthwiseConvolutionLayerFixture
DataType
Available data types.
DepthwiseConvolutionLayerValidationQuantizedFixture< CLTensor, CLAccessor, CLDepthwiseConvolutionLayer, T > CLDepthwiseConvolutionLayerQuantizedFixture
DataLayout
Supported tensor data layouts.
zip(zip(zip(framework::dataset::make("InputInfo",{TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F16), TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::QASYMM8), TensorInfo(TensorShape(5U, 5U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 37U, 2U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 37U, 22U), 1, DataType::F32)}), framework::dataset::make("OutputInfo",{TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F16), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::QASYMM8), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32), TensorInfo(TensorShape(1U, 1U, 16U), 1, DataType::F32), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32), TensorInfo(TensorShape(2U, 37U, 16U), 1, DataType::F32), TensorInfo(TensorShape(22U, 37U, 36U), 1, DataType::F32)})), framework::dataset::make("WinogradInfo",{WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(3U, 3U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW)})), framework::dataset::make("Expected",{false, false, false, false, true, true, true}))
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier)
Static function to check if given info will lead to a valid configuration of CLDepthwiseConvolutionLa...