| /* |
| * Copyright (c) 2017-2021 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/CLSoftmaxLayer.h" |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/KernelDescriptors.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Utils.h" |
| #include "src/core/gpu/cl/kernels/ClSoftmaxKernel.h" |
| #include "src/runtime/gpu/cl/operators/ClPermute.h" |
| #include "src/runtime/gpu/cl/operators/ClSoftmax.h" |
| |
| namespace arm_compute |
| { |
| using OperatorType = opencl::ClSoftmax; |
| |
| template <bool IS_LOG> |
| struct CLSoftmaxLayerGeneric<IS_LOG>::Impl |
| { |
| const ICLTensor *src{ nullptr }; |
| ICLTensor *dst{ nullptr }; |
| std::unique_ptr<OperatorType> op{ nullptr }; |
| MemoryGroup memory_group{}; |
| std::vector<std::pair<int, std::unique_ptr<CLTensor>>> workspace_tensors{}; |
| }; |
| |
| template <bool IS_LOG> |
| CLSoftmaxLayerGeneric<IS_LOG>::CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager) |
| : _impl(std::make_unique<Impl>()) |
| { |
| _impl->memory_group = MemoryGroup(std::move(memory_manager)); |
| } |
| |
| template <bool IS_LOG> |
| CLSoftmaxLayerGeneric<IS_LOG>::~CLSoftmaxLayerGeneric() = default; |
| |
| template <bool IS_LOG> |
| void CLSoftmaxLayerGeneric<IS_LOG>::configure(const ICLTensor *input, ICLTensor *output, float beta, int32_t axis) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, output, beta, axis); |
| } |
| |
| template <bool IS_LOG> |
| void CLSoftmaxLayerGeneric<IS_LOG>::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta, int32_t axis) |
| { |
| _impl->src = input; |
| _impl->dst = output; |
| _impl->op = std::make_unique<OperatorType>(); |
| |
| SoftmaxKernelInfo softmax_info{ beta, IS_LOG, input->info()->data_type(), axis }; |
| _impl->op->configure(compile_context, *input->info(), *output->info(), softmax_info); |
| allocate_workspace(); |
| } |
| |
| template <bool IS_LOG> |
| Status CLSoftmaxLayerGeneric<IS_LOG>::validate(const ITensorInfo *input, const ITensorInfo *output, float beta, int32_t axis) |
| { |
| SoftmaxKernelInfo softmax_info{ beta, IS_LOG, input->data_type(), axis }; |
| return OperatorType::validate(*input, *output, softmax_info); |
| } |
| |
| template <bool IS_LOG> |
| void CLSoftmaxLayerGeneric<IS_LOG>::allocate_workspace() |
| { |
| const auto memory_requirements = _impl->op->workspace(); |
| std::for_each(memory_requirements.begin(), memory_requirements.end(), [this](const experimental::MemoryInfo & memory_info) |
| { |
| auto tensor_info = TensorInfo{ TensorShape(memory_info.size), 1, DataType::U8 }; |
| _impl->workspace_tensors.emplace_back(memory_info.slot, std::make_unique<CLTensor>()); |
| auto tensor = _impl->workspace_tensors.back().second.get(); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(tensor); |
| tensor->allocator()->init(tensor_info); |
| _impl->memory_group.manage(tensor); |
| }); |
| |
| std::for_each(_impl->workspace_tensors.begin(), _impl->workspace_tensors.end(), [](std::pair<int, std::unique_ptr<CLTensor>> &wt) |
| { |
| auto tensor = wt.second.get(); |
| tensor->allocator()->allocate(); |
| }); |
| } |
| |
| template <bool IS_LOG> |
| void CLSoftmaxLayerGeneric<IS_LOG>::run() |
| { |
| // Acquire all the temporaries |
| MemoryGroupResourceScope scope_mg(_impl->memory_group); |
| |
| ARM_COMPUTE_ERROR_ON_NULLPTR(_impl->src, _impl->dst); |
| |
| ITensorPack pack; |
| pack.add_tensor(TensorType::ACL_SRC, _impl->src); |
| pack.add_tensor(TensorType::ACL_DST, _impl->dst); |
| |
| std::for_each(_impl->workspace_tensors.begin(), _impl->workspace_tensors.end(), [&pack](std::pair<int, std::unique_ptr<CLTensor>> &wt) |
| { |
| auto tensor = wt.second.get(); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(tensor); |
| pack.add_tensor(wt.first, tensor); |
| }); |
| |
| _impl->op->run(pack); |
| } |
| |
| template class CLSoftmaxLayerGeneric<false>; |
| template class CLSoftmaxLayerGeneric<true>; |
| |
| } // namespace arm_compute |