33 #include "tests/datasets/ShapeDatasets.h" 38 #include "tests/validation/fixtures/GEMMFixture.h" 81 const auto m_n_values =
zip(
138 constexpr
float alpha = 1.3f;
139 constexpr
float beta = 0.7f;
140 const bool is_interleaved_transposed =
false;
152 constexpr
float alpha = 1.3f;
153 constexpr
float beta = 0.7f;
154 const bool is_interleaved_transposed =
false;
166 constexpr
float alpha = 1.3f;
167 constexpr
float beta = 0.7f;
168 const bool is_interleaved_transposed =
false;
171 const bool fp_mixed_precision =
true;
181 constexpr
float alpha = 1.3f;
182 constexpr
float beta = 0.7f;
183 const bool is_interleaved_transposed =
false;
195 constexpr
float alpha = 1.3f;
196 constexpr
float beta = 0.7f;
197 const bool is_interleaved_transposed =
false;
211 constexpr
float alpha = 1.3f;
212 constexpr
float beta = 0.7f;
213 const bool is_interleaved_transposed =
false;
216 const bool fp_mixed_precision =
false;
228 constexpr
float alpha = 1.3f;
229 constexpr
float beta = 0.7f;
230 const bool is_interleaved_transposed =
false;
233 const bool fp_mixed_precision =
false;
244 constexpr
float alpha = 1.3f;
245 constexpr
float beta = 0.7f;
246 const bool is_interleaved_transposed =
false;
264 broadcast_bias_values),
265 framework::dataset::
make("fp16_mixed_precision", false)),
283 broadcast_bias_values),
303 broadcast_bias_values),
304 fp16_mixed_precision_values),
322 broadcast_bias_values),
323 fp16_mixed_precision_values),
constexpr float tolerance_num_f16
F16 Tolerance number.
GEMM reshape information class.
half_float::half half
16-bit floating point type
1 channel, 1 F32 per channel
ARM_COMPUTE_EXPECT(has_error==expected, framework::LogLevel::ERRORS)
std::enable_if< is_container< T >::value, ContainerDataset< T > >::type make(std::string name, T &&values)
Helper function to create a ContainerDataset.
GEMMMatrixMultiplyValidationFixture< CLTensor, CLAccessor, T, CLGEMMMatrixMultiplyNative > CLGEMMMatrixMultiplyNativeFixture
Activation Layer Information class.
static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float alpha, float beta, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target, bool fp_mixed_precision=false, const ActivationLayerInfo &activation_info=ActivationLayerInfo())
Static function to check if given info will lead to a valid configuration of CLGEMMMatrixMultiplyKern...
Copyright (c) 2017-2021 Arm Limited.
1 channel, 1 F16 per channel
DatasetMode
Possible dataset modes.
TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall
[CLActivationLayer Test snippet]
quantized, asymmetric fixed-point 8-bit number unsigned
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)))
GPUTarget
Available GPU Targets.
Class reprensenting a relative tolerance value.
This template synthetizes an ICLSimpleFunction which runs the given kernel K.
Store the tensor's metadata.
GEMMMatrixMultiply3DValidationFixture< CLTensor, CLAccessor, T, CLGEMMMatrixMultiplyNative > CLGEMMMatrixMultiplyNative3DFixture
TEST_CASE(FusedActivation, framework::DatasetMode::ALL)
Validate fused activation expecting the following behaviours:
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)))