46 constexpr AbsoluteTolerance<float> tolerance_f(0.00001f);
47 constexpr AbsoluteTolerance<float> tolerance_f16(0.01f);
63 shape0, shape1, epsilon, dt)
69 GCTensor src = create_tensor<GCTensor>(shape0, dt, 1, fixed_point_position);
70 GCTensor dst = create_tensor<GCTensor>(shape0, dt, 1, fixed_point_position);
71 GCTensor mean = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
72 GCTensor var = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
73 GCTensor beta = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
74 GCTensor gamma = create_tensor<GCTensor>(shape1, dt, 1, fixed_point_position);
78 norm.
configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon);
82 validate(dst.info()->valid_region(), valid_region);
Accessor implementation for GCTensor objects.
Basic function to run GCBatchNormalizationLayerKernel and simulate a batch normalization layer...
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.
void configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, float epsilon, ActivationLayerInfo act_info=ActivationLayerInfo())
Set the input and output tensors.
Interface for OpenGL ES tensor.
This file contains all available output stages for GEMMLowp on OpenCL.
#define TEST_SUITE(SUITE_NAME)
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.
bool is_data_type_fixed_point(DataType dt)
Check if a given data type is of fixed point type.
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), AbsoluteDifferenceU8Dataset), shape, data_type0, data_type1, output_data_type)
Lower and Upper Bounded Rectifier ( )
Upper Bounded Rectifier ( )
TEST_SUITE_END() DATA_TEST_CASE(Configuration
combine(combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType",{DataType::U8, DataType::S16})), datasets::BorderModes()), framework::dataset::make("filter_size",{5}))
DataType
Available data types.
convolution configure & src
ValidRegion shape_to_valid_region(const TensorShape &a_shape, bool border_undefined=false, BorderSize border_size=BorderSize(0))
Create a valid region based on tensor shape, border mode and border size.