From 00394ae1015c1eaa73f4d98fad31b7771063cd3a Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Thu, 22 Jun 2017 18:13:55 +0100 Subject: COMPMID-406: Port CLActivationLayer to use QS8/QS16. Change-Id: Ia4114984c38e1d2027ad97335b3c6c11f5754e23 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/78727 Reviewed-by: Anthony Barbier Tested-by: Kaizen --- tests/validation/CL/ActivationLayer.cpp | 69 +++++++++++++++++++++++++++---- tests/validation/NEON/ActivationLayer.cpp | 32 ++++++++++---- tests/validation/Reference.cpp | 9 +++- 3 files changed, 93 insertions(+), 17 deletions(-) (limited to 'tests/validation') diff --git a/tests/validation/CL/ActivationLayer.cpp b/tests/validation/CL/ActivationLayer.cpp index 7286b93485..ac1da5c8b4 100644 --- a/tests/validation/CL/ActivationLayer.cpp +++ b/tests/validation/CL/ActivationLayer.cpp @@ -124,7 +124,14 @@ CLTensor compute_activation_layer(bool in_place, const TensorShape &shape, DataT { int min_bound = 0; int max_bound = 0; - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + if(dt == DataType::QS8) + { + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + } + else + { + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + } std::uniform_int_distribution<> distribution(min_bound, max_bound); library->fill(CLAccessor(src), distribution, 0); } @@ -148,7 +155,7 @@ BOOST_AUTO_TEST_SUITE(CL) BOOST_AUTO_TEST_SUITE(ActivationLayer) BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true }) * (SmallShapes() + LargeShapes()) * CNNFloatDataTypes(), in_place, shape, dt) +BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true }) * (SmallShapes() + LargeShapes()) * CNNDataTypes(), in_place, shape, dt) { // Set fixed point position data type allowed const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; @@ -182,7 +189,8 @@ BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true } } // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + const int step = 16 / arm_compute::data_size_from_type(dt); + const PaddingSize padding = PaddingCalculator(shape.x(), step).required_padding(); validate(src.info()->padding(), padding); if(!in_place) @@ -193,10 +201,11 @@ BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true } BOOST_AUTO_TEST_SUITE(Float) BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * CNNFloatDataTypes() * ActivationFunctions(), in_place, shape, dt, act_function) +BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }), + in_place, shape, dt, act_function, alpha_beta) { // Create activation layer info - ActivationLayerInfo act_info(act_function, 1.f, 1.f); + ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); // Compute function CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info); @@ -209,10 +218,11 @@ BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * S } BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * LargeShapes() * CNNFloatDataTypes() * ActivationFunctions(), in_place, shape, dt, act_function) +BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * LargeShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }), + in_place, shape, dt, act_function, alpha_beta) { // Create activation layer info - ActivationLayerInfo act_info(act_function, 1.f, 1.f); + ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); // Compute function CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info); @@ -225,6 +235,49 @@ BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * L } BOOST_AUTO_TEST_SUITE_END() +/** @note We test for fixed point precision [3,5] because [1,2] and [6,7] ranges + * cause overflowing issues in most of the transcendentals functions. + */ +BOOST_AUTO_TEST_SUITE(Quantized) +BOOST_AUTO_TEST_SUITE(QS8) +BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) +BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 6, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), + in_place, shape, act_function, fixed_point_position, alpha_beta) +{ + // Create activation layer info + ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); + + // Compute function + CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS8, act_info, fixed_point_position); + + // Compute reference + RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS8, act_info, fixed_point_position); + + // Validate output + validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position)); +} +BOOST_AUTO_TEST_SUITE_END() + +BOOST_AUTO_TEST_SUITE(QS16) +BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) +BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 14, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), + in_place, shape, act_function, fixed_point_position, alpha_beta) +{ + // Create activation layer info + ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta); + + // Compute function + CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS16, act_info, fixed_point_position); + + // Compute reference + RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS16, act_info, fixed_point_position); + + // Validate output + validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position)); +} +BOOST_AUTO_TEST_SUITE_END() +BOOST_AUTO_TEST_SUITE_END() + BOOST_AUTO_TEST_SUITE_END() BOOST_AUTO_TEST_SUITE_END() -#endif /* DOXYGEN_SKIP_THIS */ +#endif /* DOXYGEN_SKIP_THIS */ \ No newline at end of file diff --git a/tests/validation/NEON/ActivationLayer.cpp b/tests/validation/NEON/ActivationLayer.cpp index 71dfcdc4e2..2b24fd5175 100644 --- a/tests/validation/NEON/ActivationLayer.cpp +++ b/tests/validation/NEON/ActivationLayer.cpp @@ -53,12 +53,13 @@ namespace { /** Define tolerance of the activation layer * + * @param[in] dt The data type used. * @param[in] activation The activation function used. * @param[in] fixed_point_position Number of bits for the fractional part.. * * @return Tolerance depending on the activation function. */ -float activation_layer_tolerance(ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 0) +float activation_layer_tolerance(DataType dt, ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 0) { switch(activation) { @@ -66,7 +67,15 @@ float activation_layer_tolerance(ActivationLayerInfo::ActivationFunction activat case ActivationLayerInfo::ActivationFunction::SOFT_RELU: case ActivationLayerInfo::ActivationFunction::SQRT: case ActivationLayerInfo::ActivationFunction::TANH: - return (fixed_point_position != 0) ? 5.f : 0.00001f; + switch(dt) + { + case DataType::QS8: + return 5.f; + case DataType::QS16: + return 11.f; + default: + return 0.00001f; + } break; default: return 0.f; @@ -124,7 +133,14 @@ Tensor compute_activation_layer(bool in_place, const TensorShape &shape, DataTyp { int min_bound = 0; int max_bound = 0; - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + if(dt == DataType::QS8) + { + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + } + else + { + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + } std::uniform_int_distribution<> distribution(min_bound, max_bound); library->fill(NEAccessor(src), distribution, 0); } @@ -206,7 +222,7 @@ BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * S RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info); // Validate output - validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(act_function)); + validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(dt, act_function)); } BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly")) @@ -223,7 +239,7 @@ BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * L RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info); // Validate output - validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(act_function)); + validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(dt, act_function)); } BOOST_AUTO_TEST_SUITE_END() @@ -246,13 +262,13 @@ BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * S RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS8, act_info, fixed_point_position); // Validate output - validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position)); + validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(DataType::QS8, act_function, fixed_point_position)); } BOOST_AUTO_TEST_SUITE_END() BOOST_AUTO_TEST_SUITE(QS16) BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 6, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), +BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 14, 1) * boost::unit_test::data::make({ 0.5f, 1.f }), in_place, shape, act_function, fixed_point_position, alpha_beta) { // Create activation layer info @@ -265,7 +281,7 @@ BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * S RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS16, act_info, fixed_point_position); // Validate output - validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position)); + validate(NEAccessor(dst), ref_dst, activation_layer_tolerance(DataType::QS16, act_function, fixed_point_position)); } BOOST_AUTO_TEST_SUITE_END() diff --git a/tests/validation/Reference.cpp b/tests/validation/Reference.cpp index 0a57fc0ea5..1b941870ba 100644 --- a/tests/validation/Reference.cpp +++ b/tests/validation/Reference.cpp @@ -459,7 +459,14 @@ RawTensor Reference::compute_reference_activation_layer(const TensorShape &shape { int min_bound = 0; int max_bound = 0; - std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + if(dt == DataType::QS8) + { + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + } + else + { + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds(act_info.activation(), fixed_point_position); + } std::uniform_int_distribution<> distribution(min_bound, max_bound); library->fill(ref_src, distribution, 0); } -- cgit v1.2.1