diff options
Diffstat (limited to 'tests/validation/NEON/FullyConnectedLayer.cpp')
| -rw-r--r-- | tests/validation/NEON/FullyConnectedLayer.cpp | 425 |
1 files changed, 329 insertions, 96 deletions
diff --git a/tests/validation/NEON/FullyConnectedLayer.cpp b/tests/validation/NEON/FullyConnectedLayer.cpp index 4bb48bf42c..ee7e56227d 100644 --- a/tests/validation/NEON/FullyConnectedLayer.cpp +++ b/tests/validation/NEON/FullyConnectedLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 Arm Limited. + * Copyright (c) 2017-2021, 2023-2024 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -25,6 +25,8 @@ #include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" +#include "src/core/helpers/MemoryHelpers.h" +#include "src/cpu/operators/CpuFullyConnected.h" #include "tests/NEON/Accessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/FullyConnectedLayerDataset.h" @@ -40,6 +42,7 @@ namespace test { namespace validation { +using framework::dataset::make; namespace { /** Tolerance for float operations */ @@ -56,7 +59,7 @@ constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_signed(1); /** CNN data types */ -const auto CNNDataTypes = framework::dataset::make("DataType", +const auto CNNDataTypes = make("DataType", { #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC DataType::F16, @@ -64,18 +67,25 @@ const auto CNNDataTypes = framework::dataset::make("DataType", DataType::F32, }); -const auto FullyConnectedParameters = combine(framework::dataset::make("TransposeWeights", { false, true }), framework::dataset::make("ReshapeWeights", { false, true })); +const auto FullyConnectedParameters = combine(make("TransposeWeights", { false, true }), make("ReshapeWeights", { false, true })); -const auto QuantizationData = framework::dataset::make("QuantizationInfo", +const auto QuantizationData = make("QuantizationInfo", { QuantizationInfo(1.f / 256.f, 10), QuantizationInfo(1.1f, 10), }); -const auto EmptyActivationFunctionDataset = framework::dataset::make("ActivationInfo", + +const auto IgnoredQuantizationData = make("IgnoredQuantizationInfo", +{ + QuantizationInfo(), +}); + +const auto NoActivationFunctionDataset = make("ActivationInfo", { ActivationLayerInfo(), }); -const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", + +const auto ActivationFunctionsDataset = make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), @@ -83,7 +93,7 @@ const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH), }); -const auto ActivationFunctionsQuantizedDataset = framework::dataset::make("ActivationInfo", +const auto ActivationFunctionsQuantizedDataset = make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), @@ -94,40 +104,183 @@ const auto ActivationFunctionsQuantizedDataset = framework::dataset::make("Activ TEST_SUITE(NEON) TEST_SUITE(FullyConnectedLayer) +/** Test case for memory injection in @ref cpu::CpuFullyConnected. + * + * Configure the operator once and inject memory at run-time in multiple executions. + * + * Checks performed in order: + * - Both runs compute the same output + */ +TEST_CASE(MemoryInjection, framework::DatasetMode::ALL) +{ + auto fc = std::make_unique<cpu::CpuFullyConnected>(); + const auto src_info = TensorInfo(TensorShape(8U), 1, DataType::F32, DataLayout::NHWC); + const auto weight_info = TensorInfo(TensorShape(8U, 4U), 1, DataType::F32, DataLayout::NHWC); + const auto bias_info = TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC); + auto dst_info = TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC); + const auto fc_info = FullyConnectedLayerInfo{}; + fc->configure(&src_info, &weight_info, &bias_info, &dst_info, fc_info); + + // telhs are newly created every call of this lambda function + auto src = create_tensor<Tensor>(src_info); + auto weight = create_tensor<Tensor>(weight_info); + auto bias = create_tensor<Tensor>(bias_info); + src.allocator()->allocate(); + weight.allocator()->allocate(); + bias.allocator()->allocate(); + + ITensorPack run_pack{ { TensorType::ACL_SRC_0, &src }, { TensorType::ACL_SRC_1, &weight }, { TensorType::ACL_SRC_2, &bias } }; + ITensorPack prep_pack{ { TensorType::ACL_SRC_1, &weight }, { TensorType::ACL_SRC_2, &bias } }; + + auto mg = MemoryGroup{}; + auto ws = manage_workspace<Tensor>(fc->workspace(), mg, run_pack, prep_pack); + + auto run_conv = [&]() -> Tensor + { + auto dst = create_tensor<Tensor>(dst_info); + dst.allocator()->allocate(); + run_pack.add_tensor(TensorType::ACL_DST, &dst); + + library->fill_tensor_value(Accessor(src), 1.f); + library->fill_tensor_value(Accessor(weight), 2.f); + library->fill_tensor_value(Accessor(bias), 3.f); + // This operator is configured once and captured by this lambda. + fc->prepare(prep_pack); + fc->run(run_pack); + return dst; + }; + auto result_0 = run_conv(); + auto result_1 = run_conv(); + for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) + { + ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS); + } +} + +/** Test case for memory injection in @ref NEFullyConnectedLayer. + * + * Make sure @ref NEFullyConnectedLayer still works through injecting the memory at configure time using the old API. + * + * Checks performed in order: + * - Both runs compute the same output + */ +TEST_CASE(MultipleExecutionWithConfigure, framework::DatasetMode::ALL) +{ + auto fc = std::make_unique<NEFullyConnectedLayer>(); + const auto src_info = TensorInfo(TensorShape(8U), 1, DataType::F32, DataLayout::NHWC); + const auto weight_info = TensorInfo(TensorShape(8U, 4U), 1, DataType::F32, DataLayout::NHWC); + const auto bias_info = TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC); + auto dst_info = TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC); + const auto fc_info = FullyConnectedLayerInfo{}; + auto run_conv = [&]() + { + auto src = create_tensor<Tensor>(src_info); + auto weight = create_tensor<Tensor>(weight_info); + auto bias = create_tensor<Tensor>(bias_info); + auto dst = create_tensor<Tensor>(dst_info); + fc->configure(&src, &weight, &bias, &dst, fc_info); + src.allocator()->allocate(); + weight.allocator()->allocate(); + bias.allocator()->allocate(); + dst.allocator()->allocate(); + library->fill_tensor_value(Accessor(src), 1.f); + library->fill_tensor_value(Accessor(weight), 2.f); + library->fill_tensor_value(Accessor(bias), 3.f); + fc->run(); + return dst; + }; + auto result_0 = run_conv(); + auto result_1 = run_conv(); + for(size_t i = 0; i < result_0.info()->tensor_shape().total_size(); ++i) + { + ARM_COMPUTE_EXPECT(((float *)result_0.buffer())[i] == ((float *)result_1.buffer())[i], framework::LogLevel::ERRORS); + } +} + +/** Unit test for @ref cpu::CpuFullyConnected with quantized multipler > 1 + * + * Tests output correctness. + */ +TEST_CASE(Quant8_Signed_Mult_gt_1, framework::DatasetMode::ALL) +{ + auto fc = std::make_unique<cpu::CpuFullyConnected>(); + const auto src_info = TensorInfo(TensorShape(1U, 3U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(0.5f, -1)); + const auto weight_info = TensorInfo(TensorShape(1U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(0.5, -8)); + const auto bias_info = TensorInfo(TensorShape(1U), 1, DataType::S32); + auto dst_info = TensorInfo(TensorShape(1U, 3U), 1, DataType::QASYMM8_SIGNED, QuantizationInfo(0.1f, 0)); + const auto fc_info = FullyConnectedLayerInfo{}; + fc->configure(&src_info, &weight_info, &bias_info, &dst_info, fc_info); + + // telhs are newly created every call of this lambda function + auto src = create_tensor<Tensor>(src_info); + auto weight = create_tensor<Tensor>(weight_info); + auto bias = create_tensor<Tensor>(bias_info); + auto dst = create_tensor<Tensor>(dst_info); + src.allocator()->allocate(); + weight.allocator()->allocate(); + bias.allocator()->allocate(); + dst.allocator()->allocate(); + + ITensorPack run_pack{ { TensorType::ACL_SRC_0, &src }, { TensorType::ACL_SRC_1, &weight }, { TensorType::ACL_SRC_2, &bias }, { TensorType::ACL_DST, &dst } }; + ITensorPack prep_pack{ { TensorType::ACL_SRC_1, &weight }, { TensorType::ACL_SRC_2, &bias } }; + + auto mg = MemoryGroup{}; + auto ws = manage_workspace<Tensor>(fc->workspace(), mg, run_pack, prep_pack); + + // Initialize input values + const std::vector<int8_t> src_values = { 3, 63, 31 }; + const std::vector<int8_t> weight_values = { -4 }; + const std::vector<int32_t> bias_values = { 16 }; + const std::vector<int32_t> expected = { 80, 127, 127 }; + library->fill_static_values(Accessor(src), src_values); + library->fill_static_values(Accessor(weight), weight_values); + library->fill_static_values(Accessor(bias), bias_values); + + // Run FC layer + fc->prepare(prep_pack); + fc->run(run_pack); + + auto dst_ptr = reinterpret_cast<int8_t *>(dst.buffer()); + for(size_t i = 0; i < dst.info()->tensor_shape().total_size(); ++i) + { + ARM_COMPUTE_EXPECT(dst_ptr[i] == expected[i], framework::LogLevel::ERRORS); + } +} + // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Mismatching data types + make("InputInfo", { TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Mismatching data types TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Invalid weights dimensions TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Wrongly reshaped weights TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), }), - framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(315U, 271U), 1, DataType::F16), + make("WeightsInfo",{ TensorInfo(TensorShape(315U, 271U), 1, DataType::F16), TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), TensorInfo(TensorShape(217U, 315U), 1, DataType::F32), TensorInfo(TensorShape(217U, 315U), 1, DataType::F32), TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), })), - framework::dataset::make("BiasInfo",{ TensorInfo(TensorShape(271U), 1, DataType::F32), + make("BiasInfo",{ TensorInfo(TensorShape(271U), 1, DataType::F32), TensorInfo(TensorShape(192U), 1, DataType::F32), TensorInfo(TensorShape(192U), 1, DataType::F32), TensorInfo(TensorShape(271U), 1, DataType::F32), TensorInfo(TensorShape(271U), 1, DataType::F32), TensorInfo(TensorShape(192U), 1, DataType::F32), })), - framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), + make("OutputInfo",{ TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), })), - framework::dataset::make("TransposeWeights",{ true, true, false, true, true, true })), - framework::dataset::make("ReshapedWeights",{ false, false, false, false, false , false})), - framework::dataset::make("Expected", { false, true, true, false, false, true })), + make("TransposeWeights",{ true, true, false, true, true, true })), + make("ReshapedWeights",{ false, false, false, false, false , false})), + make("Expected", { false, true, true, false, false, true })), input_info, weights_info, bias_info, output_info, transpose_weights, reshaped_weights, expected) { // Create Fully Connected layer info @@ -145,74 +298,89 @@ template <typename T> using NEFullyConnectedLayerFixture = FullyConnectedLayerValidationFixture<Tensor, Accessor, NEFullyConnectedLayer, T>; template <typename T> using NEFullyConnectedLayerMixedDataLayoutFixture = FullyConnectedLayerValidationFixture<Tensor, Accessor, NEFullyConnectedLayer, T, true>; +template <typename T> +using NEFullyConnectedLayerDynamicWeightsFixture = FullyConnectedWithDynamicWeightsFixture<Tensor, Accessor, NEFullyConnectedLayer, T>; +template <typename T> +using NEFullyConnectedLayerDynamicBiasFixture = FullyConnectedWithDynamicBiasFixture<Tensor, Accessor, NEFullyConnectedLayer, T>; TEST_SUITE(Float) #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F16)), - EmptyActivationFunctionDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + FullyConnectedParameters, + make("DataType", DataType::F16), + NoActivationFunctionDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); } -FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine( +FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::FullyConnectedLayerWithActivationDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F16)), + FullyConnectedParameters, + make("DataType", DataType::F16), ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F16)), - EmptyActivationFunctionDataset)) +FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeFullyConnectedLayerDataset(), + FullyConnectedParameters, + make("DataType", DataType::F16), + NoActivationFunctionDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); } +FIXTURE_DATA_TEST_CASE(RunDynamicWeights, NEFullyConnectedLayerDynamicWeightsFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::F16), + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)), + make("WeightsReshaped", { false, true }))) +{ +} TEST_SUITE_END() #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F32)), - EmptyActivationFunctionDataset)) +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters, + make("DataType", DataType::F32), + NoActivationFunctionDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEFullyConnectedLayerMixedDataLayoutFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(combine( - framework::dataset::make("Input", TensorShape(9U, 5U, 7U)), - framework::dataset::make("Weights", TensorShape(315U, 271U))), - framework::dataset::make("Biases", TensorShape(271U))), - framework::dataset::make("Output", TensorShape(271U))), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F32)), - framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)))) +FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEFullyConnectedLayerMixedDataLayoutFixture<float>, framework::DatasetMode::PRECOMMIT, combine( + make("Input", TensorShape(9U, 5U, 7U)), + make("Weights", TensorShape(315U, 271U)), + make("Biases", TensorShape(271U)), + make("Output", TensorShape(271U)), + FullyConnectedParameters, + make("DataType", DataType::F32), + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)))) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine( - combine(datasets::FullyConnectedLayerWithActivationDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F32)), +FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::FullyConnectedLayerWithActivationDataset(), + FullyConnectedParameters, + make("DataType", DataType::F32), ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), - framework::dataset::make("DataType", DataType::F32)), - EmptyActivationFunctionDataset)) +FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters, + make("DataType", DataType::F32), + NoActivationFunctionDataset)) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); } +FIXTURE_DATA_TEST_CASE(RunDynamicWeights, NEFullyConnectedLayerDynamicWeightsFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::F32), + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)), + make("WeightsReshaped", { false, true }))) +{ +} TEST_SUITE_END() TEST_SUITE_END() @@ -223,87 +391,152 @@ using NEFullyConnectedLayerQuantizedMixedDataLayoutFixture = FullyConnectedLayer TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( - combine(datasets::SmallFullyConnectedLayerDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::QASYMM8)), - QuantizationData), - EmptyActivationFunctionDataset)) +FIXTURE_DATA_TEST_CASE(RunMixedDataLayoutWithActivation, NEFullyConnectedLayerQuantizedMixedDataLayoutFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, + combine( + make("Input", TensorShape(9U, 5U, 7U)), + make("Weights", TensorShape(315U, 271U)), + make("Biases", TensorShape(271U)), + make("Output", TensorShape(271U)), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8), + QuantizationData, + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEFullyConnectedLayerQuantizedMixedDataLayoutFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, - combine(combine(combine(combine(combine(combine(combine( - framework::dataset::make("Input", TensorShape(9U, 5U, 7U)), - framework::dataset::make("Weights", TensorShape(315U, 271U))), - framework::dataset::make("Biases", TensorShape(271U))), - framework::dataset::make("Output", TensorShape(271U))), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::QASYMM8)), - QuantizationData), - framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)))) -{ - // Validate output - validate(Accessor(_target), _reference, tolerance_qasymm8); -} -FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( +FIXTURE_DATA_TEST_CASE(RunSmallWithActivation, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::FullyConnectedLayerWithActivationDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::QASYMM8)), - QuantizationData), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8), + QuantizationData, ActivationFunctionsQuantizedDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } +FIXTURE_DATA_TEST_CASE(RunDynamicWeightsWithActivation, NEFullyConnectedLayerDynamicWeightsFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::QASYMM8), + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)), + make("WeightsReshaped", { false }))) +{ +} +FIXTURE_DATA_TEST_CASE(RunDynamicBiasWithActivation, NEFullyConnectedLayerDynamicBiasFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::QASYMM8), + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)))) +{ +} -FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine( - combine(datasets::LargeFullyConnectedLayerDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::QASYMM8)), - QuantizationData), - EmptyActivationFunctionDataset)) +// Dynamic Quantization Tests here +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallFullyConnectedLayerDataset(), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8), + IgnoredQuantizationData, + NoActivationFunctionDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } -TEST_SUITE_END() -TEST_SUITE(QASYMM8_SIGNED) -FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( - combine(datasets::SmallFullyConnectedLayerDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), - QuantizationData), - EmptyActivationFunctionDataset)) +FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine( + datasets::LargeFullyConnectedLayerDataset(), + FullyConnectedParameters, + framework::dataset::make("DataType", DataType::QASYMM8), + QuantizationData, + NoActivationFunctionDataset)) { // Validate output - validate(Accessor(_target), _reference, tolerance_qasymm8_signed); + validate(Accessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEFullyConnectedLayerQuantizedMixedDataLayoutFixture<int8_t>, framework::DatasetMode::PRECOMMIT, - combine(combine(combine(combine(combine(combine(combine( - framework::dataset::make("Input", TensorShape(9U, 5U, 7U)), - framework::dataset::make("Weights", TensorShape(315U, 271U))), - framework::dataset::make("Biases", TensorShape(271U))), - framework::dataset::make("Output", TensorShape(271U))), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), - QuantizationData), - framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)))) +FIXTURE_DATA_TEST_CASE(RunDynamicBias, NEFullyConnectedLayerDynamicBiasFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::QASYMM8), + NoActivationFunctionDataset)) +{ +} +FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEFullyConnectedLayerQuantizedMixedDataLayoutFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, + combine( + make("Input", TensorShape(9U, 5U, 7U)), + make("Weights", TensorShape(315U, 271U)), + make("Biases", TensorShape(271U)), + make("Output", TensorShape(271U)), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8), + IgnoredQuantizationData, + NoActivationFunctionDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( +FIXTURE_DATA_TEST_CASE(RunDynamicWeights, NEFullyConnectedLayerDynamicWeightsFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::QASYMM8), + NoActivationFunctionDataset, + make("WeightsReshaped", { false }))) +{ +} +TEST_SUITE_END() // QASYMM8 +TEST_SUITE(QASYMM8_SIGNED) +FIXTURE_DATA_TEST_CASE(RunMixedDataLayoutWithActivation, NEFullyConnectedLayerQuantizedMixedDataLayoutFixture<int8_t>, framework::DatasetMode::PRECOMMIT, + combine( + make("Input", TensorShape(9U, 5U, 7U)), + make("Weights", TensorShape(315U, 271U)), + make("Biases", TensorShape(271U)), + make("Output", TensorShape(271U)), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8_SIGNED), + QuantizationData, + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8_signed); +} +FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::FullyConnectedLayerWithActivationDataset(), - FullyConnectedParameters), - framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), - QuantizationData), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8_SIGNED), + QuantizationData, ActivationFunctionsQuantizedDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8_signed); } +FIXTURE_DATA_TEST_CASE(RunDynamicWeightsWithActivation, NEFullyConnectedLayerDynamicWeightsFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::QASYMM8_SIGNED), + make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)), + make("WeightsReshaped", { false }))) +{ +} + +// Dynamic Quantization tests +FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine( + datasets::SmallFullyConnectedLayerDataset(), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8_SIGNED), + IgnoredQuantizationData, + NoActivationFunctionDataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8_signed); +} +FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, NEFullyConnectedLayerQuantizedMixedDataLayoutFixture<int8_t>, framework::DatasetMode::PRECOMMIT, + combine( + make("Input", TensorShape(9U, 5U, 7U)), + make("Weights", TensorShape(315U, 271U)), + make("Biases", TensorShape(271U)), + make("Output", TensorShape(271U)), + FullyConnectedParameters, + make("DataType", DataType::QASYMM8_SIGNED), + QuantizationData, + NoActivationFunctionDataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8_signed); +} +FIXTURE_DATA_TEST_CASE(RunDynamicWeights, NEFullyConnectedLayerDynamicWeightsFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallFullyConnectedLayerDataset(), + make("DataType", DataType::QASYMM8_SIGNED), + NoActivationFunctionDataset, + make("WeightsReshaped", { false }))) +{ +} TEST_SUITE_END() // QASYMM8_SIGNED TEST_SUITE_END() // Quantized TEST_SUITE_END() // FullyConnectedLayer |