From 574775c7fa78a094bbeb7f9f87aca832936884e2 Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Mon, 18 Feb 2019 20:08:02 +0000 Subject: COMPMID-1937: Adds support for DequantizationLayer for NEON/CL. Change-Id: I4b73edd176a277294e0e42e642460bc61210778a Signed-off-by: Georgios Pinitas Reviewed-on: https://review.mlplatform.org/c/744 Tested-by: Arm Jenkins Reviewed-by: Giuseppe Rossini --- tests/validation/CL/DequantizationLayer.cpp | 99 ++++++++--------- tests/validation/NEON/DequantizationLayer.cpp | 120 ++++++++++----------- .../fixtures/DequantizationLayerFixture.h | 87 +++------------ tests/validation/reference/DequantizationLayer.cpp | 32 ++---- tests/validation/reference/DequantizationLayer.h | 6 +- 5 files changed, 128 insertions(+), 216 deletions(-) (limited to 'tests/validation') diff --git a/tests/validation/CL/DequantizationLayer.cpp b/tests/validation/CL/DequantizationLayer.cpp index 5303566922..b1b0d81c6d 100644 --- a/tests/validation/CL/DequantizationLayer.cpp +++ b/tests/validation/CL/DequantizationLayer.cpp @@ -40,107 +40,94 @@ namespace test { namespace validation { -namespace -{ -const auto DequantizationShapes = concat(datasets::Small3DShapes(), - datasets::Small4DShapes()); -} // namespace - TEST_SUITE(CL) TEST_SUITE(DequantizationLayer) // *INDENT-OFF* // clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), // Wrong input data type - TensorInfo(TensorShape(16U, 5U, 16U), 1, DataType::U8), // Invalid shape - TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), // Wrong output data type - TensorInfo(TensorShape(16U, 16U, 2U, 5U), 1, DataType::U8), // Missmatching shapes - TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::U8), // Shrink window - TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), // Valid +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), // Wrong input data type + TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Wrong output data type + TensorInfo(TensorShape(16U, 16U, 2U, 5U), 1, DataType::QASYMM8), // Missmatching shapes + TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid + TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid }), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), - TensorInfo(TensorShape(16U, 5U, 16U), 1, DataType::U8), TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::F32), TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), })), - framework::dataset::make("MinMax",{ TensorInfo(TensorShape(2U), 1, DataType::F32), - TensorInfo(TensorShape(2U), 1, DataType::U8), - TensorInfo(TensorShape(2U), 1, DataType::F32), - TensorInfo(TensorShape(2U), 1, DataType::F32), - TensorInfo(TensorShape(2U), 1, DataType::U8), - TensorInfo(TensorShape(2U), 1, DataType::U8), - })), - framework::dataset::make("Expected", { false, false, false, false, false, true})), - input_info, output_info, min_max, expected) + framework::dataset::make("Expected", { false, false, false, true, true})), + input_info, output_info, expected) { - ARM_COMPUTE_EXPECT(bool(CLDequantizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), &min_max.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(bool(CLDequantizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(DequantizationShapes, framework::dataset::make("DataType", DataType::U8)), shape, data_type) +DATA_TEST_CASE(Configuration, + framework::DatasetMode::ALL, + combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::F16, DataType::F32 })), + shape, data_type) { - TensorShape shape_min_max = shape; - shape_min_max.set(Window::DimX, 2); - - // Remove Y and Z dimensions and keep the batches - shape_min_max.remove_dimension(1); - shape_min_max.remove_dimension(1); - // Create tensors - CLTensor src = create_tensor(shape, data_type); - CLTensor dst = create_tensor(shape, DataType::F32); - CLTensor min_max = create_tensor(shape_min_max, DataType::F32); + CLTensor src = create_tensor(shape, DataType::QASYMM8, 1, QuantizationInfo(0.5f, -10)); + CLTensor dst = create_tensor(shape, data_type); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(min_max.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function CLDequantizationLayer dequant_layer; - dequant_layer.configure(&src, &dst, &min_max); + dequant_layer.configure(&src, &dst); // Validate valid region const ValidRegion valid_region = shape_to_valid_region(shape); validate(src.info()->valid_region(), valid_region); validate(dst.info()->valid_region(), valid_region); - // Validate valid region of min_max tensor - const ValidRegion valid_region_min_max = shape_to_valid_region(shape_min_max); - validate(min_max.info()->valid_region(), valid_region_min_max); - // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 4).required_padding(); - validate(src.info()->padding(), padding); - validate(dst.info()->padding(), padding); - - // Validate padding of min_max tensor - const PaddingSize padding_min_max = PaddingCalculator(shape_min_max.x(), 2).required_padding(); - validate(min_max.info()->padding(), padding_min_max); + validate(src.info()->padding(), PaddingSize()); + validate(dst.info()->padding(), PaddingSize()); } template using CLDequantizationLayerFixture = DequantizationValidationFixture; -TEST_SUITE(Integer) -TEST_SUITE(U8) -FIXTURE_DATA_TEST_CASE(RunSmall, CLDequantizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small3DShapes(), datasets::Small4DShapes()), - framework::dataset::make("DataType", DataType::U8))) +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, CLDequantizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +FIXTURE_DATA_TEST_CASE(RunLarge, CLDequantizationLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() // FP16 + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, CLDequantizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) { // Validate output validate(CLAccessor(_target), _reference); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLDequantizationLayerFixture, framework::DatasetMode::NIGHTLY, combine(concat(datasets::Large3DShapes(), datasets::Large4DShapes()), - framework::dataset::make("DataType", DataType::U8))) +FIXTURE_DATA_TEST_CASE(RunLarge, CLDequantizationLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) { // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() // U8 -TEST_SUITE_END() // Integer +TEST_SUITE_END() // FP32 TEST_SUITE_END() // DequantizationLayer TEST_SUITE_END() // CL diff --git a/tests/validation/NEON/DequantizationLayer.cpp b/tests/validation/NEON/DequantizationLayer.cpp index 48a6b227c1..0ae20b7b5d 100644 --- a/tests/validation/NEON/DequantizationLayer.cpp +++ b/tests/validation/NEON/DequantizationLayer.cpp @@ -42,8 +42,11 @@ namespace validation { namespace { -/** Tolerance for float operations */ -constexpr AbsoluteTolerance tolerance_f32(0.001f); +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 }); +#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +const auto data_types = framework::dataset::make("DataType", { DataType::F32 }); +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ } // namespace TEST_SUITE(NEON) @@ -51,96 +54,91 @@ TEST_SUITE(DequantizationLayer) // *INDENT-OFF* // clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( - framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), // Wrong input data type - TensorInfo(TensorShape(16U, 5U, 16U), 1, DataType::U8), // Invalid shape - TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), // Wrong output data type - TensorInfo(TensorShape(16U, 16U, 2U, 5U), 1, DataType::U8), // Missmatching shapes - TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::U8), // Shrink window - TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), // Valid - }), - framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), - TensorInfo(TensorShape(16U, 5U, 16U), 1, DataType::U8), - TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), - TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), - TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::F32), - TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), - })), - framework::dataset::make("MinMax",{ TensorInfo(TensorShape(2U), 1, DataType::F32), - TensorInfo(TensorShape(2U), 1, DataType::U8), - TensorInfo(TensorShape(2U), 1, DataType::F32), - TensorInfo(TensorShape(2U), 1, DataType::F32), - TensorInfo(TensorShape(2U), 1, DataType::U8), - TensorInfo(TensorShape(2U), 1, DataType::U8), - })), - framework::dataset::make("Expected", { false, false, false, false, false, true})), - input_info, output_info, min_max, expected) +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), // Wrong input data type + TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Wrong output data type + TensorInfo(TensorShape(16U, 16U, 2U, 5U), 1, DataType::QASYMM8), // Missmatching shapes + TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid + TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid + }), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), + TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), + TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), + TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::F32), + TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { false, false, false, true, true})), + input_info, output_info, expected) { - ARM_COMPUTE_EXPECT(bool(NEDequantizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), &min_max.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(bool(NEDequantizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::Small3DShapes(), framework::dataset::make("DataType", DataType::U8)), shape, data_type) +DATA_TEST_CASE(Configuration, + framework::DatasetMode::ALL, + combine(datasets::SmallShapes(), data_types), + shape, data_type) { - TensorShape shape_min_max = shape; - shape_min_max.set(Window::DimX, 2); - - // Remove Y and Z dimensions and keep the batches - shape_min_max.remove_dimension(1); - shape_min_max.remove_dimension(1); - // Create tensors - Tensor src = create_tensor(shape, data_type); - Tensor dst = create_tensor(shape, DataType::F32); - Tensor min_max = create_tensor(shape_min_max, DataType::F32); + Tensor src = create_tensor(shape, DataType::QASYMM8, 1, QuantizationInfo(0.5f, -10)); + Tensor dst = create_tensor(shape, data_type); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(min_max.info()->is_resizable(), framework::LogLevel::ERRORS); // Create and configure function NEDequantizationLayer dequant_layer; - dequant_layer.configure(&src, &dst, &min_max); + dequant_layer.configure(&src, &dst); // Validate valid region const ValidRegion valid_region = shape_to_valid_region(shape); validate(src.info()->valid_region(), valid_region); validate(dst.info()->valid_region(), valid_region); - // Validate valid region of min_max tensor - const ValidRegion valid_region_min_max = shape_to_valid_region(shape_min_max); - validate(min_max.info()->valid_region(), valid_region_min_max); - // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 8).required_padding(); - validate(src.info()->padding(), padding); - validate(dst.info()->padding(), padding); - - // Validate padding of min_max tensor - const PaddingSize padding_min_max = PaddingCalculator(shape_min_max.x(), 2).required_padding(); - validate(min_max.info()->padding(), padding_min_max); + validate(src.info()->padding(), PaddingSize()); + validate(dst.info()->padding(), PaddingSize()); } template using NEDequantizationLayerFixture = DequantizationValidationFixture; -TEST_SUITE(Integer) -TEST_SUITE(U8) -FIXTURE_DATA_TEST_CASE(RunSmall, NEDequantizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small3DShapes(), datasets::Small4DShapes()), - framework::dataset::make("DataType", DataType::U8))) +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, NEDequantizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} +FIXTURE_DATA_TEST_CASE(RunLarge, NEDequantizationLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // FP16 +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, NEDequantizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) { // Validate output - validate(Accessor(_target), _reference, tolerance_f32); + validate(Accessor(_target), _reference); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEDequantizationLayerFixture, framework::DatasetMode::NIGHTLY, combine(concat(datasets::Large3DShapes(), datasets::Large4DShapes()), - framework::dataset::make("DataType", DataType::U8))) +FIXTURE_DATA_TEST_CASE(RunLarge, NEDequantizationLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) }))) { // Validate output - validate(Accessor(_target), _reference, tolerance_f32); + validate(Accessor(_target), _reference); } -TEST_SUITE_END() // U8 -TEST_SUITE_END() // Integer +TEST_SUITE_END() // FP32 TEST_SUITE_END() // DequantizationLayer TEST_SUITE_END() // NEON diff --git a/tests/validation/fixtures/DequantizationLayerFixture.h b/tests/validation/fixtures/DequantizationLayerFixture.h index 0bf3522cd6..2e3712dff2 100644 --- a/tests/validation/fixtures/DequantizationLayerFixture.h +++ b/tests/validation/fixtures/DequantizationLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -47,10 +47,10 @@ class DequantizationValidationFixture : public framework::Fixture { public: template - void setup(TensorShape shape, DataType data_type) + void setup(TensorShape shape, DataType data_type, QuantizationInfo qinfo) { - _target = compute_target(shape, data_type); - _reference = compute_reference(shape, data_type); + _target = compute_target(shape, data_type, qinfo); + _reference = compute_reference(shape, data_type, qinfo); } protected: @@ -60,80 +60,28 @@ protected: library->fill_tensor_uniform(tensor, 0); } - template - void fill_min_max(U &&tensor) - { - std::mt19937 gen(library->seed()); - std::uniform_real_distribution distribution(-1.0f, 1.0f); - - Window window; - - window.set(0, Window::Dimension(0, tensor.shape()[0], 2)); - - for(unsigned int d = 1; d < tensor.shape().num_dimensions(); ++d) - { - window.set(d, Window::Dimension(0, tensor.shape()[d], 1)); - } - - execute_window_loop(window, [&](const Coordinates & id) - { - const float n1 = distribution(gen); - const float n2 = distribution(gen); - - float min = 0.0f; - float max = 0.0f; - - if(n1 < n2) - { - min = n1; - max = n2; - } - else - { - min = n2; - max = n1; - } - - auto out_ptr = reinterpret_cast(tensor(id)); - out_ptr[0] = min; - out_ptr[1] = max; - }); - } - - TensorType compute_target(const TensorShape &shape, DataType data_type) + TensorType compute_target(const TensorShape &shape, DataType data_type, QuantizationInfo qinfo) { - TensorShape shape_min_max = shape; - shape_min_max.set(Window::DimX, 2); - - // Remove Y and Z dimensions and keep the batches - shape_min_max.remove_dimension(1); - shape_min_max.remove_dimension(1); - // Create tensors - TensorType src = create_tensor(shape, data_type); - TensorType dst = create_tensor(shape, DataType::F32); - TensorType min_max = create_tensor(shape_min_max, DataType::F32); + TensorType src = create_tensor(shape, DataType::QASYMM8, 1, qinfo); + TensorType dst = create_tensor(shape, data_type); // Create and configure function FunctionType dequantization_layer; - dequantization_layer.configure(&src, &dst, &min_max); + dequantization_layer.configure(&src, &dst); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(min_max.info()->is_resizable(), framework::LogLevel::ERRORS); // Allocate tensors src.allocator()->allocate(); dst.allocator()->allocate(); - min_max.allocator()->allocate(); ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!min_max.info()->is_resizable(), framework::LogLevel::ERRORS); // Fill tensors fill(AccessorType(src)); - fill_min_max(AccessorType(min_max)); // Compute function dequantization_layer.run(); @@ -141,28 +89,19 @@ protected: return dst; } - SimpleTensor compute_reference(const TensorShape &shape, DataType data_type) + SimpleTensor compute_reference(const TensorShape &shape, DataType data_type, QuantizationInfo qinfo) { - TensorShape shape_min_max = shape; - shape_min_max.set(Window::DimX, 2); - - // Remove Y and Z dimensions and keep the batches - shape_min_max.remove_dimension(1); - shape_min_max.remove_dimension(1); - // Create reference - SimpleTensor src{ shape, data_type }; - SimpleTensor min_max{ shape_min_max, data_type }; + SimpleTensor src{ shape, DataType::QASYMM8, 1, qinfo }; // Fill reference fill(src); - fill_min_max(min_max); - return reference::dequantization_layer(src, min_max); + return reference::dequantization_layer(src); } - TensorType _target{}; - SimpleTensor _reference{}; + TensorType _target{}; + SimpleTensor _reference{}; }; } // namespace validation } // namespace test diff --git a/tests/validation/reference/DequantizationLayer.cpp b/tests/validation/reference/DequantizationLayer.cpp index 33096a1d81..df50c14ec7 100644 --- a/tests/validation/reference/DequantizationLayer.cpp +++ b/tests/validation/reference/DequantizationLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -31,36 +31,24 @@ namespace validation { namespace reference { -template ::value, int>::type> -SimpleTensor dequantization_layer(const SimpleTensor &src, const SimpleTensor &min_max) +template +SimpleTensor dequantization_layer(const SimpleTensor &src) { - // Create reference - SimpleTensor dst{ src.shape(), DataType::F32 }; + const DataType dst_data_type = std::is_same::value ? DataType::F32 : DataType::F16; + const QuantizationInfo &quantization_info = src.quantization_info(); - // Compute reference - const int width = src.shape().x(); - const int height = src.shape().y(); - const int depth = src.shape().z(); - const int stride_w = width * height * depth; - const int num_batches = min_max.shape().total_size_upper(1); + SimpleTensor dst{ src.shape(), dst_data_type }; - for(int k = 0; k < num_batches; ++k) + for(int i = 0; i < src.num_elements(); ++i) { - const float min = min_max[k * 2 + 0]; - const float max = min_max[k * 2 + 1]; - const float range = max - min; - const float scaling = range / 255.0f; - - for(int i = 0; i < stride_w; ++i) - { - dst[i + k * stride_w] = (static_cast(src[i + k * stride_w]) * scaling) + min; - } + dst[i] = static_cast(quantization_info.dequantize(src[i])); } return dst; } -template SimpleTensor dequantization_layer(const SimpleTensor &src, const SimpleTensor &min_max); +template SimpleTensor dequantization_layer(const SimpleTensor &src); +template SimpleTensor dequantization_layer(const SimpleTensor &src); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/DequantizationLayer.h b/tests/validation/reference/DequantizationLayer.h index 1a8adcf9d8..1d0e54b442 100644 --- a/tests/validation/reference/DequantizationLayer.h +++ b/tests/validation/reference/DequantizationLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -35,8 +35,8 @@ namespace validation { namespace reference { -template ::value, int>::type = 0> -SimpleTensor dequantization_layer(const SimpleTensor &src, const SimpleTensor &min_max); +template +SimpleTensor dequantization_layer(const SimpleTensor &src); } // namespace reference } // namespace validation } // namespace test -- cgit v1.2.1