diff options
author | Michele Di Giorgio <michele.digiorgio@arm.com> | 2018-06-27 16:41:17 +0100 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:53:57 +0000 |
commit | 4622ac15aa009b3ce90ddc6c2ad6c918d6776103 (patch) | |
tree | 75745983f10da70d1ec59caf6f243e2065cbe0f3 | |
parent | 7c3b92403958e8970e901fd15b2fc904e7996eee (diff) | |
download | ComputeLibrary-4622ac15aa009b3ce90ddc6c2ad6c918d6776103.tar.gz |
COMPMID-1336: Add CLArithmeticAddition support for QASYMM8
Change-Id: Ice2bb644841fdea4e776872ff5481eb927e66bd1
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/137714
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
-rw-r--r-- | arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h | 12 | ||||
-rw-r--r-- | arm_compute/runtime/CL/functions/CLArithmeticAddition.h | 12 | ||||
-rw-r--r-- | src/core/CL/CLKernelLibrary.cpp | 5 | ||||
-rw-r--r-- | src/core/CL/cl_kernels/arithmetic_op_quantized.cl | 89 | ||||
-rw-r--r-- | src/core/CL/kernels/CLArithmeticAdditionKernel.cpp | 25 | ||||
-rw-r--r-- | tests/validation/CL/ArithmeticAddition.cpp | 41 | ||||
-rw-r--r-- | tests/validation/fixtures/ArithmeticAdditionFixture.h | 53 | ||||
-rw-r--r-- | tests/validation/reference/ArithmeticAddition.cpp | 30 |
8 files changed, 235 insertions, 32 deletions
diff --git a/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h b/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h index 5112476aae..a33cbf321f 100644 --- a/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h +++ b/arm_compute/core/CL/kernels/CLArithmeticAdditionKernel.h @@ -53,17 +53,17 @@ public: ~CLArithmeticAdditionKernel() = default; /** Initialise the kernel's inputs, output and convertion policy. * - * @param[in] input1 First tensor input. Data types supported: U8/QS8/QS16/S16/F16/F32. - * @param[in] input2 Second tensor input. Data types supported: U8/QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. - * @param[out] output Output tensor. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[in] input1 First tensor input. Data types supported: U8/QS8/QASYMM8/QS16/S16/F16/F32. + * @param[in] input2 Second tensor input. Data types supported: U8/QS8 (only if @p input1 is QS8), QASYMM8 (only if @p input1 is QASYMM8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[out] output Output tensor. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8),QASYMM8 (only if @p input1 is QASYMM8), QS16 (only if both inputs are QS16), S16/F16/F32. * @param[in] policy Policy to use to handle overflow. */ void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticAdditionKernel * - * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QS16/S16/F16/F32. - * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. - * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QASYMM8/QS16/S16/F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QASYMM8 (only if @p input1 is QASYMM8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QASYMM8 (only if both inputs are QASYMM8), QS16 (only if both inputs are QS16), S16/F16/F32. * @param[in] policy Policy to use to handle overflow. * * @return a status diff --git a/arm_compute/runtime/CL/functions/CLArithmeticAddition.h b/arm_compute/runtime/CL/functions/CLArithmeticAddition.h index 5b2fc8c145..9eea846d97 100644 --- a/arm_compute/runtime/CL/functions/CLArithmeticAddition.h +++ b/arm_compute/runtime/CL/functions/CLArithmeticAddition.h @@ -41,19 +41,19 @@ class CLArithmeticAddition : public ICLSimpleFunction public: /** Initialise the kernel's inputs, output and convertion policy. * - * @param[in, out] input1 First tensor input. Data types supported: U8/QS8/QS16/S16/F16/F32. + * @param[in, out] input1 First tensor input. Data types supported: U8/QS8/QASYMM8/QS16/S16/F16/F32. * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0. - * @param[in, out] input2 Second tensor input. Data types supported: U8, QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[in, out] input2 Second tensor input. Data types supported: U8, QS8 (only if @p input1 is QS8), QASYMM8 (only if @p input1 is QASYMM8), QS16 (only if @p input1 is QS16), S16/F16/F32. * The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0. - * @param[out] output Output tensor. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[out] output Output tensor. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QASYMM8 (only if both inputs are QASYMM8), QS16 (only if both inputs are QS16), S16/F16/F32. * @param[in] policy Policy to use to handle overflow. */ void configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, ConvertPolicy policy); /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticAddition * - * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QS16/S16/F16/F32. - * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QS16 (only if @p input1 is QS16), S16/F16/F32. - * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QS16 (only if both inputs are QS16), S16/F16/F32. + * @param[in] input1 First tensor input info. Data types supported: U8/QS8/QASYMM8/QS16/S16/F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: U8/QS8 (only if @p input1 is QS8), QASYMM8 (only if @p input1 is QASYMM8), QS16 (only if @p input1 is QS16), S16/F16/F32. + * @param[in] output Output tensor info. Data types supported: U8 (Only if both inputs are U8), QS8 (only if both inputs are QS8), QASYMM8 ( only if both inputs are QASYMM8), QS16 (only if both inputs are QS16), S16/F16/F32. * @param[in] policy Policy to use to handle overflow. * * @return a status diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index 712a1179a6..aa11edf9ec 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -149,6 +149,7 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map = { "accumulate_weighted", "accumulate.cl" }, { "activation_layer", "activation_layer.cl" }, { "activation_layer_qa8", "activation_layer_qa8.cl" }, + { "arithmetic_add_quantized", "arithmetic_op_quantized.cl" }, { "arithmetic_add", "arithmetic_op.cl" }, { "arithmetic_sub", "arithmetic_op.cl" }, { "arithmetic_div", "arithmetic_op.cl" }, @@ -416,6 +417,10 @@ const std::map<std::string, std::string> CLKernelLibrary::_program_source_map = #include "./cl_kernels/arithmetic_op.clembed" }, { + "arithmetic_op_quantized.cl", +#include "./cl_kernels/arithmetic_op_quantized.clembed" + }, + { "bitwise_op.cl", #include "./cl_kernels/bitwise_op.clembed" }, diff --git a/src/core/CL/cl_kernels/arithmetic_op_quantized.cl b/src/core/CL/cl_kernels/arithmetic_op_quantized.cl new file mode 100644 index 0000000000..82e92e32a8 --- /dev/null +++ b/src/core/CL/cl_kernels/arithmetic_op_quantized.cl @@ -0,0 +1,89 @@ +/* + * Copyright (c) 2016-2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "helpers.h" + +#ifdef SATURATE +#define ADD(x, y) add_sat((x), (y)) +#define SUB(x, y) sub_sat((x), (y)) +#else /* SATURATE */ +#define ADD(x, y) (x) + (y) +#define SUB(x, y) (x) - (y) +#endif /* SATURATE */ + +#if defined(OFFSET) + +/** This function adds two tensors. + * + * @attention The quantization offset must be passed at compile time using -DOFFSET, i.e. -DOFFSET=10 + * @attention To perform saturating operation -DSATURATE has to be passed to the compiler otherwise wrapping policy will be used. + * + * @param[in] in1_ptr Pointer to the source tensor. Supported data types: QASYMM8 + * @param[in] in1_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] in1_step_x in1_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] in1_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] in1_step_y in1_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] in1_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] in1_step_z in1_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] in1_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] in2_ptr Pointer to the source tensor. Supported data types: same as @p in1_ptr + * @param[in] in2_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] in2_step_x in2_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] in2_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] in2_step_y in2_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] in2_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] in2_step_z in2_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] in2_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] out_ptr Pointer to the destination tensor. Supported data types: same as @p in1_ptr + * @param[in] out_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] out_step_x out_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] out_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] out_step_y out_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] out_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] out_step_z out_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void arithmetic_add_quantized( + TENSOR3D_DECLARATION(in1), + TENSOR3D_DECLARATION(in2), + TENSOR3D_DECLARATION(out)) +{ + // Get pixels pointer + Tensor3D in1 = CONVERT_TO_TENSOR3D_STRUCT(in1); + Tensor3D in2 = CONVERT_TO_TENSOR3D_STRUCT(in2); + Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(out); + + // Load values + const short16 in_a = CONVERT(vload16(0, (__global uchar *)in1.ptr), short16); + const short16 in_b = CONVERT(vload16(0, (__global uchar *)in2.ptr), short16); + const short16 offset = OFFSET; + + // Calculate result + short16 res = ADD(in_a, SUB(in_b, offset)); + + res = max((short16)0, min(res, (short16)255)); + + // Store result + vstore16(CONVERT(res, uchar16), 0, (__global uchar *)out.ptr); +} +#endif /* defined(OFFSET) */ diff --git a/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp b/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp index b0177ab8b6..011807ad88 100644 --- a/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp +++ b/src/core/CL/kernels/CLArithmeticAdditionKernel.cpp @@ -37,9 +37,15 @@ Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, { ARM_COMPUTE_UNUSED(policy); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::U8, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&input2); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input2, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input2, 1, DataType::U8, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + + const bool is_qasymm = is_data_type_quantized_asymmetric(input1.data_type()) || is_data_type_quantized_asymmetric(input2.data_type()); + if(is_qasymm) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &input2); + } const TensorShape out_shape = TensorShape::broadcast_shape(input1.tensor_shape(), input2.tensor_shape()); @@ -50,12 +56,16 @@ Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, if(output.total_size() > 0) { ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(&output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::S16, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MSG((output.data_type() == DataType::U8) && ((input1.data_type() != DataType::U8) || (input2.data_type() != DataType::U8)), "Output can only be U8 if both inputs are U8"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output.tensor_shape(), 0), "Wrong shape for output"); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(&input1, &output); + if(is_qasymm) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input1, &output); + } } return Status{}; @@ -124,6 +134,8 @@ void CLArithmeticAdditionKernel::configure(const ICLTensor *input1, const ICLTen const bool has_float_out = is_data_type_float(output->info()->data_type()); + std::string kernel_name = "arithmetic_add"; + // Set kernel build options std::set<std::string> build_opts; build_opts.emplace((policy == ConvertPolicy::WRAP || has_float_out) ? "-DWRAP" : "-DSATURATE"); @@ -134,9 +146,14 @@ void CLArithmeticAdditionKernel::configure(const ICLTensor *input1, const ICLTen { build_opts.emplace("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input1->info()->fixed_point_position())); } + else if(is_data_type_quantized_asymmetric(input1->info()->data_type())) + { + build_opts.emplace("-DOFFSET=" + support::cpp11::to_string(input1->info()->quantization_info().offset)); + kernel_name += "_quantized"; + } // Create kernel - _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("arithmetic_add", build_opts)); + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts)); ICLKernel::configure(win_config.second); } diff --git a/tests/validation/CL/ArithmeticAddition.cpp b/tests/validation/CL/ArithmeticAddition.cpp index 9323ed2934..0646c05ad7 100644 --- a/tests/validation/CL/ArithmeticAddition.cpp +++ b/tests/validation/CL/ArithmeticAddition.cpp @@ -46,6 +46,9 @@ namespace /** Input data sets **/ const auto ArithmeticAdditionU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", DataType::U8)); +const auto ArithmeticAdditionQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); const auto ArithmeticAdditionS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), framework::dataset::make("DataType", DataType::S16)); const auto ArithmeticAdditionFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), @@ -121,6 +124,44 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticAdditionFixture<uint8_t>, framework } TEST_SUITE_END() +template <typename T> +using CLArithmeticAdditionQuantizedFixture = ArithmeticAdditionValidationQuantizedFixture<CLTensor, CLAccessor, CLArithmeticAddition, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), + shape, policy) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::QASYMM8); + + // Create and Configure function + CLArithmeticAddition add; + add.configure(&ref_src1, &ref_src2, &dst, policy); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticAdditionQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), ArithmeticAdditionQASYMM8Dataset), + framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() +TEST_SUITE_END() + TEST_SUITE(S16) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), diff --git a/tests/validation/fixtures/ArithmeticAdditionFixture.h b/tests/validation/fixtures/ArithmeticAdditionFixture.h index f3888ae565..99a56777a2 100644 --- a/tests/validation/fixtures/ArithmeticAdditionFixture.h +++ b/tests/validation/fixtures/ArithmeticAdditionFixture.h @@ -41,14 +41,15 @@ namespace test namespace validation { template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class ArithmeticAdditionBroadcastValidationFixedPointFixture : public framework::Fixture +class ArithmeticAdditionGenericFixture : public framework::Fixture { public: template <typename...> - void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits) + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits, + QuantizationInfo quantization_info) { - _target = compute_target(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, fractional_bits); - _reference = compute_reference(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, fractional_bits); + _target = compute_target(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, fractional_bits, quantization_info); + _reference = compute_reference(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, fractional_bits, quantization_info); } protected: @@ -59,12 +60,12 @@ protected: } TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, - int fixed_point_position) + int fixed_point_position, QuantizationInfo quantization_info) { // Create tensors - TensorType ref_src1 = create_tensor<TensorType>(shape0, data_type0, 1, fixed_point_position); - TensorType ref_src2 = create_tensor<TensorType>(shape1, data_type1, 1, fixed_point_position); - TensorType dst = create_tensor<TensorType>(TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, fixed_point_position); + TensorType ref_src1 = create_tensor<TensorType>(shape0, data_type0, 1, fixed_point_position, quantization_info); + TensorType ref_src2 = create_tensor<TensorType>(shape1, data_type1, 1, fixed_point_position, quantization_info); + TensorType dst = create_tensor<TensorType>(TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, fixed_point_position, quantization_info); // Create and configure function FunctionType add; @@ -94,11 +95,11 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, - int fixed_point_position) + int fixed_point_position, QuantizationInfo quantization_info) { // Create reference - SimpleTensor<T> ref_src1{ shape0, data_type0, 1, fixed_point_position }; - SimpleTensor<T> ref_src2{ shape1, data_type1, 1, fixed_point_position }; + SimpleTensor<T> ref_src1{ shape0, data_type0, 1, fixed_point_position, quantization_info }; + SimpleTensor<T> ref_src2{ shape1, data_type1, 1, fixed_point_position, quantization_info }; // Fill reference fill(ref_src1, 0); @@ -112,24 +113,35 @@ protected: }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class ArithmeticAdditionBroadcastValidationFixture : public ArithmeticAdditionBroadcastValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T> +class ArithmeticAdditionBroadcastValidationFixedPointFixture : public ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits) + { + ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, 0, QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ArithmeticAdditionBroadcastValidationFixture : public ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T> { public: template <typename...> void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy) { - ArithmeticAdditionBroadcastValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, 0); + ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, data_type0, data_type1, output_data_type, convert_policy, 0, QuantizationInfo()); } }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> -class ArithmeticAdditionValidationFixedPointFixture : public ArithmeticAdditionBroadcastValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T> +class ArithmeticAdditionValidationFixedPointFixture : public ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T> { public: template <typename...> void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, int fractional_bits) { - ArithmeticAdditionBroadcastValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, shape, data_type0, data_type1, output_data_type, convert_policy, fractional_bits); + ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, shape, data_type0, data_type1, output_data_type, convert_policy, fractional_bits, QuantizationInfo()); } }; @@ -143,6 +155,17 @@ public: ArithmeticAdditionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type0, data_type1, output_data_type, convert_policy, 0); } }; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ArithmeticAdditionValidationQuantizedFixture : public ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, ConvertPolicy convert_policy, QuantizationInfo quantization_info) + { + ArithmeticAdditionGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, shape, data_type0, data_type1, output_data_type, convert_policy, 0, quantization_info); + } +}; } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/reference/ArithmeticAddition.cpp b/tests/validation/reference/ArithmeticAddition.cpp index 17020a6277..f26838dcb8 100644 --- a/tests/validation/reference/ArithmeticAddition.cpp +++ b/tests/validation/reference/ArithmeticAddition.cpp @@ -97,7 +97,35 @@ SimpleTensor<T> arithmetic_addition(const SimpleTensor<T> &src1, const SimpleTen return dst; } -template SimpleTensor<uint8_t> arithmetic_addition(const SimpleTensor<uint8_t> &src1, const SimpleTensor<uint8_t> &src2, DataType dst_data_type, ConvertPolicy convert_policy); +template <> +SimpleTensor<uint8_t> arithmetic_addition(const SimpleTensor<uint8_t> &src1, const SimpleTensor<uint8_t> &src2, DataType dst_data_type, ConvertPolicy convert_policy) +{ + if(dst_data_type == DataType::QASYMM8) + { + SimpleTensor<float> src1_tmp = convert_from_asymmetric(src1); + SimpleTensor<float> src2_tmp = convert_from_asymmetric(src2); + SimpleTensor<float> dst_tmp(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst_data_type); + + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(src1_tmp, src2_tmp, dst_tmp, convert_policy, id_src1, id_src2, id_dst); + + SimpleTensor<uint8_t> dst = convert_to_asymmetric(dst_tmp, src1.quantization_info()); + return dst; + } + else + { + // DataType::U8 + SimpleTensor<uint8_t> dst(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst_data_type); + + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); + + return dst; + } +} + template SimpleTensor<int16_t> arithmetic_addition(const SimpleTensor<int16_t> &src1, const SimpleTensor<int16_t> &src2, DataType dst_data_type, ConvertPolicy convert_policy); template SimpleTensor<int8_t> arithmetic_addition(const SimpleTensor<int8_t> &src1, const SimpleTensor<int8_t> &src2, DataType dst_data_type, ConvertPolicy convert_policy); template SimpleTensor<half> arithmetic_addition(const SimpleTensor<half> &src1, const SimpleTensor<half> &src2, DataType dst_data_type, ConvertPolicy convert_policy); |