/* * Copyright (c) 2018-2021 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 "arm_compute/runtime/CL/functions/CLElementwiseOperations.h" #include "arm_compute/core/CL/CLKernelLibrary.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/Types.h" #include "src/core/CL/ICLKernel.h" #include "src/runtime/gpu/cl/operators/ClAdd.h" #include "src/runtime/gpu/cl/operators/ClElementwiseOperations.h" #include "src/runtime/gpu/cl/operators/ClSub.h" namespace arm_compute { struct CLArithmeticAddition::Impl { const ICLTensor *src_0{ nullptr }; const ICLTensor *src_1{ nullptr }; ICLTensor *dst{ nullptr }; std::unique_ptr op{ nullptr }; }; CLArithmeticAddition::CLArithmeticAddition() : _impl(std::make_unique()) { } CLArithmeticAddition::CLArithmeticAddition(CLArithmeticAddition &&) = default; CLArithmeticAddition &CLArithmeticAddition::operator=(CLArithmeticAddition &&) = default; CLArithmeticAddition::~CLArithmeticAddition() = default; void CLArithmeticAddition::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, policy, act_info); } void CLArithmeticAddition::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), policy, act_info); } Status CLArithmeticAddition::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { return opencl::ClAdd::validate(input1, input2, output, policy, act_info); } void CLArithmeticAddition::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC_0, _impl->src_0); pack.add_tensor(TensorType::ACL_SRC_1, _impl->src_1); pack.add_tensor(TensorType::ACL_DST, _impl->dst); _impl->op->run(pack); } struct CLArithmeticSubtraction::Impl { const ICLTensor *src_0{ nullptr }; const ICLTensor *src_1{ nullptr }; ICLTensor *dst{ nullptr }; std::unique_ptr op{ nullptr }; }; CLArithmeticSubtraction::CLArithmeticSubtraction() : _impl(std::make_unique()) { } CLArithmeticSubtraction::CLArithmeticSubtraction(CLArithmeticSubtraction &&) = default; CLArithmeticSubtraction &CLArithmeticSubtraction::operator=(CLArithmeticSubtraction &&) = default; CLArithmeticSubtraction::~CLArithmeticSubtraction() = default; void CLArithmeticSubtraction::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, policy, act_info); } void CLArithmeticSubtraction::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), policy, act_info); } Status CLArithmeticSubtraction::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { return opencl::ClSub::validate(input1, input2, output, policy, act_info); } void CLArithmeticSubtraction::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC_0, _impl->src_0); pack.add_tensor(TensorType::ACL_SRC_1, _impl->src_1); pack.add_tensor(TensorType::ACL_DST, _impl->dst); _impl->op->run(pack); } struct CLArithmeticDivision::Impl { const ICLTensor *src_0{ nullptr }; const ICLTensor *src_1{ nullptr }; ICLTensor *dst{ nullptr }; std::unique_ptr op{ nullptr }; }; CLArithmeticDivision::CLArithmeticDivision() : _impl(std::make_unique()) { } CLArithmeticDivision::CLArithmeticDivision(CLArithmeticDivision &&) = default; CLArithmeticDivision &CLArithmeticDivision::operator=(CLArithmeticDivision &&) = default; CLArithmeticDivision::~CLArithmeticDivision() = default; void CLArithmeticDivision::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, act_info); } void CLArithmeticDivision::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } Status CLArithmeticDivision::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) { return opencl::ClElementwiseDivision::validate(input1, input2, output, act_info); } void CLArithmeticDivision::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC_0, _impl->src_0); pack.add_tensor(TensorType::ACL_SRC_1, _impl->src_1); pack.add_tensor(TensorType::ACL_DST, _impl->dst); _impl->op->run(pack); } struct CLElementwiseMax::Impl { const ICLTensor *src_0{ nullptr }; const ICLTensor *src_1{ nullptr }; ICLTensor *dst{ nullptr }; std::unique_ptr op{ nullptr }; }; CLElementwiseMax::CLElementwiseMax() : _impl(std::make_unique()) { } CLElementwiseMax::CLElementwiseMax(CLElementwiseMax &&) = default; CLElementwiseMax &CLElementwiseMax::operator=(CLElementwiseMax &&) = default; CLElementwiseMax::~CLElementwiseMax() = default; void CLElementwiseMax::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, act_info); } void CLElementwiseMax::configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } Status CLElementwiseMax::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) { return opencl::ClElementwiseMax::validate(input1, input2, output, act_info); } void CLElementwiseMax::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC_0, _impl->src_0); pack.add_tensor(TensorType::ACL_SRC_1, _impl->src_1); pack.add_tensor(TensorType::ACL_DST, _impl->dst); _impl->op->run(pack); } struct CLElementwiseMin::Impl { const ICLTensor *src_0{ nullptr }; const ICLTensor *src_1{ nullptr }; ICLTensor *dst{ nullptr }; std::unique_ptr op{ nullptr }; }; CLElementwiseMin::CLElementwiseMin() : _impl(std::make_unique()) { } CLElementwiseMin::CLElementwiseMin(CLElementwiseMin &&) = default; CLElementwiseMin &CLElementwiseMin::operator=(CLElementwiseMin &&) = default; CLElementwiseMin::~CLElementwiseMin() = default; void CLElementwiseMin::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, act_info); } void CLElementwiseMin::configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } Status CLElementwiseMin::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) { return opencl::ClElementwiseMin::validate(input1, input2, output, act_info); } void CLElementwiseMin::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC_0, _impl->src_0); pack.add_tensor(TensorType::ACL_SRC_1, _impl->src_1); pack.add_tensor(TensorType::ACL_DST, _impl->dst); _impl->op->run(pack); } struct CLElementwiseSquaredDiff::Impl { const ICLTensor *src_0{ nullptr }; const ICLTensor *src_1{ nullptr }; ICLTensor *dst{ nullptr }; std::unique_ptr op{ nullptr }; }; CLElementwiseSquaredDiff::CLElementwiseSquaredDiff() : _impl(std::make_unique()) { } CLElementwiseSquaredDiff::CLElementwiseSquaredDiff(CLElementwiseSquaredDiff &&) = default; CLElementwiseSquaredDiff &CLElementwiseSquaredDiff::operator=(CLElementwiseSquaredDiff &&) = default; CLElementwiseSquaredDiff::~CLElementwiseSquaredDiff() = default; void CLElementwiseSquaredDiff::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, act_info); } void CLElementwiseSquaredDiff::configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } Status CLElementwiseSquaredDiff::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) { return opencl::ClElementwiseSquaredDiff::validate(input1, input2, output, act_info); } void CLElementwiseSquaredDiff::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC_0, _impl->src_0); pack.add_tensor(TensorType::ACL_SRC_1, _impl->src_1); pack.add_tensor(TensorType::ACL_DST, _impl->dst); _impl->op->run(pack); } struct CLElementwisePower::Impl { const ICLTensor *src_0{ nullptr }; const ICLTensor *src_1{ nullptr }; ICLTensor *dst{ nullptr }; std::unique_ptr op{ nullptr }; }; CLElementwisePower::CLElementwisePower() : _impl(std::make_unique()) { } CLElementwisePower::CLElementwisePower(CLElementwisePower &&) = default; CLElementwisePower &CLElementwisePower::operator=(CLElementwisePower &&) = default; CLElementwisePower::~CLElementwisePower() = default; void CLElementwisePower::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, act_info); } void CLElementwisePower::configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info) { _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } Status CLElementwisePower::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info) { return opencl::ClElementwisePower::validate(input1, input2, output, act_info); } void CLElementwisePower::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC_0, _impl->src_0); pack.add_tensor(TensorType::ACL_SRC_1, _impl->src_1); pack.add_tensor(TensorType::ACL_DST, _impl->dst); _impl->op->run(pack); } } // namespace arm_compute