30 #include "tests/datasets/FullyConnectedLayerDataset.h" 35 #include "tests/validation/fixtures/FullyConnectedLayerFixture.h" 46 constexpr RelativeTolerance<float> rel_tolerance_f32(0.05f);
49 constexpr
float tolerance_num = 0.07f;
52 constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1);
67 QuantizationInfo(1.f / 255.f, 10),
68 QuantizationInfo(1.1f, 10),
73 ActivationLayerInfo(),
82 ActivationLayerInfo(),
130 &weights_info.clone()->set_is_resizable(
false),
131 &bias_info.clone()->set_is_resizable(
false),
132 &output_info.clone()->set_is_resizable(
false),
139 template <
typename T>
145 FullyConnectedParameters),
147 ActivationFunctionsDataset))
153 FullyConnectedParameters),
155 ActivationFunctionsDataset))
165 ActivationFunctionsDataset))
172 ActivationFunctionsDataset))
180 template <
typename T>
187 ActivationFunctionsQuantizedDataset))
194 ActivationFunctionsQuantizedDataset))
203 ActivationFunctionsQuantizedDataset))
FullyConnectedLayerValidationFixture< CLTensor, CLAccessor, CLFullyConnectedLayer, T > CLFullyConnectedLayerFixture
FullyConnectedLayerValidationQuantizedFixture< CLTensor, CLAccessor, CLFullyConnectedLayer, T > CLFullyConnectedLayerQuantizedFixture
half_float::half half
16-bit floating point type
1 channel, 1 F32 per channel
ARM_COMPUTE_EXPECT(has_error==expected, framework::LogLevel::ERRORS)
Fully connected layer info.
std::enable_if< is_container< T >::value, ContainerDataset< T > >::type make(std::string name, T &&values)
Helper function to create a ContainerDataset.
Copyright (c) 2017-2021 Arm Limited.
1 channel, 1 F16 per channel
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16), }), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f/32768.f, 0)), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f/32768.f, 0)), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f/32768.f, 0)), })), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::SQRT), })), framework::dataset::make("Expected", { false, true, true, true, false, false, true, true, false })), input_info, output_info, act_info, expected)
DatasetMode
Possible dataset modes.
TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall
[CLActivationLayer Test snippet]
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, FullyConnectedLayerInfo fc_info=FullyConnectedLayerInfo())
Static function to check if given info will lead to a valid configuration of CLFullyConnectedLayer.
quantized, asymmetric fixed-point 8-bit number unsigned
bool are_weights_reshaped
Reshape the weights tensor if false.
Accessor implementation for CLTensor objects.
TEST_SUITE(U8_to_S8) FIXTURE_DATA_TEST_CASE(RunSmall
validate(CLAccessor(output_state), expected_output)
Lower and Upper Bounded Rectifier ( )
FIXTURE_DATA_TEST_CASE(RunSmall, CLAbsLayerFixture< half >, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)))
Upper Bounded Rectifier ( )
bool transpose_weights
Transpose weights if true.
Store the tensor's metadata.
quantized, asymmetric fixed-point 8-bit number signed
RelativeTolerance< half_float::half > tolerance_f16(half(0.2))
F16 Tolerance value for comparing reference's output against implementation's output for floating poi...
zip(zip(framework::dataset::make("Weights", { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U, 1U), 1, DataType::F32), }), framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32), TensorInfo(TensorShape(2U), 1, DataType::F16), TensorInfo(TensorShape(5U), 1, DataType::F32), })), framework::dataset::make("Expected", { true, false, false}))
DataType
Available data types.
constexpr float abs_tolerance_f32(0.0001f)
F32 Absolute tolerance value for comparing reference's output against implementation's output for flo...
combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)))
const auto QuantizationData