| /* |
| * 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/CLGEMMConvolutionLayer.h" |
| |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/PixelValue.h" |
| #include "arm_compute/core/Size2D.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/core/utils/quantization/AsymmHelpers.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| #include "src/core/experimental/PostOpUtils.h" |
| #include "src/core/helpers/MemoryHelpers.h" |
| #include "src/gpu/cl/operators/ClGemmConv2d.h" |
| #include "support/Cast.h" |
| |
| #include <cmath> |
| #include <memory> |
| #include <tuple> |
| |
| namespace arm_compute |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| using namespace arm_compute::utils::cast; |
| using namespace arm_compute::experimental; |
| |
| struct CLGEMMConvolutionLayer::Impl |
| { |
| const ITensor *weights{ nullptr }; |
| std::unique_ptr<opencl::ClGemmConv2d> op{ nullptr }; |
| ITensorPack run_pack{}; |
| ITensorPack prep_pack{}; |
| MemoryGroup memory_group{}; |
| IWeightsManager *weights_manager{ nullptr }; |
| MemoryRequirements aux_mem_req{}; |
| WorkspaceData<CLTensor> workspace_tensors{}; |
| bool is_prepared{ false }; |
| }; |
| |
| CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager) |
| : _impl(std::make_unique<Impl>()) |
| { |
| _impl->memory_group = MemoryGroup(memory_manager); |
| _impl->weights_manager = weights_manager; |
| } |
| |
| CLGEMMConvolutionLayer::~CLGEMMConvolutionLayer() = default; |
| |
| void CLGEMMConvolutionLayer::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, |
| const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, num_groups, post_ops); |
| } |
| |
| void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, |
| const PadStrideInfo &conv_info, |
| const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); |
| _impl->weights = weights; |
| _impl->op = std::make_unique<opencl::ClGemmConv2d>(); |
| // Convert post op arguments to ITensorInfo |
| auto transformed_post_ops = experimental::transform_post_op_list_arguments<ICLTensor *, ITensorInfo *>(post_ops, [](auto tensor) |
| { |
| return tensor->info(); |
| }); |
| const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups, transformed_post_ops); |
| _impl->op->configure(compile_context, input->info(), weights->info(), (biases != nullptr ? biases->info() : nullptr), output->info(), conv2d_info, weights_info); |
| |
| _impl->run_pack = |
| { |
| { TensorType::ACL_SRC_0, input }, |
| { TensorType::ACL_SRC_1, weights }, |
| { TensorType::ACL_SRC_2, biases }, |
| { TensorType::ACL_DST, output } |
| }; |
| // Add post op tensors |
| size_t post_op_tensor_index = 0; |
| for(const auto &op : post_ops.get_list()) |
| { |
| for(auto &tensor : op->arguments()) |
| { |
| _impl->run_pack.add_const_tensor(experimental::get_post_op_arg_type(post_op_tensor_index++), *tensor); |
| } |
| } |
| _impl->prep_pack = |
| { |
| { TensorType::ACL_SRC_1, weights }, |
| { TensorType::ACL_SRC_2, biases }, |
| }; |
| _impl->aux_mem_req = _impl->op->workspace(); |
| _impl->workspace_tensors = manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack); |
| } |
| |
| Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, |
| const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ITensorInfo *> &post_ops) |
| { |
| const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups, post_ops); |
| return opencl::ClGemmConv2d::validate(input, weights, biases, output, conv2d_info, weights_info); |
| } |
| |
| void CLGEMMConvolutionLayer::run() |
| { |
| prepare(); |
| MemoryGroupResourceScope scope_mg(_impl->memory_group); |
| _impl->op->run(_impl->run_pack); |
| } |
| |
| void CLGEMMConvolutionLayer::prepare() |
| { |
| if(!_impl->is_prepared) |
| { |
| _impl->op->prepare(_impl->prep_pack); |
| auto has_reshape = std::find_if(_impl->aux_mem_req.begin(), |
| _impl->aux_mem_req.end(), |
| [](const MemoryInfo & m) -> bool { return m.lifetime == MemoryLifetime::Persistent; }); |
| |
| if(has_reshape != std::end(_impl->aux_mem_req)) |
| { |
| _impl->weights->mark_as_unused(); |
| } |
| else |
| { |
| // Pack the B matrix to be used as the underlying GEMM performs no reshapes |
| _impl->run_pack.add_const_tensor(ACL_SRC_1, _impl->weights); |
| } |
| release_temporaries(_impl->aux_mem_req, _impl->workspace_tensors); |
| _impl->is_prepared = true; |
| } |
| } |
| } // namespace arm_compute |