| /* |
| * 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/CLConvolutionLayer.h" |
| |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/KernelDescriptors.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/CL/functions/CLFFTConvolutionLayer.h" |
| #include "src/core/CL/ICLKernel.h" |
| #include "src/core/helpers/MemoryHelpers.h" |
| #include "src/gpu/cl/operators/ClConv2d.h" |
| |
| #include "src/common/utils/Log.h" |
| #include "support/Cast.h" |
| |
| namespace arm_compute |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| using namespace arm_compute::experimental; |
| struct CLConvolutionLayer::Impl |
| { |
| MemoryGroup memory_group{}; |
| std::shared_ptr<IMemoryManager> memory_manager{}; |
| std::unique_ptr<opencl::IClOperator> op{ nullptr }; |
| ITensorPack run_pack{}; |
| ITensorPack prep_pack{}; |
| WorkspaceData<CLTensor> workspace{}; |
| experimental::MemoryRequirements aux_mem_req{}; |
| std::unique_ptr<IFunction> func{ nullptr }; |
| }; |
| |
| CLConvolutionLayer::CLConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager) |
| : _impl(std::make_unique<Impl>()) |
| { |
| _impl->memory_manager = std::move(memory_manager); |
| } |
| |
| CLConvolutionLayer::~CLConvolutionLayer() = default; |
| |
| void CLConvolutionLayer::configure(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, bool enable_fast_math, unsigned int num_groups) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups); |
| } |
| |
| void CLConvolutionLayer::configure(const CLCompileContext &compile_context, 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, bool enable_fast_math, unsigned int num_groups) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); |
| ARM_COMPUTE_ERROR_THROW_ON(CLConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation, act_info, |
| enable_fast_math, num_groups)); |
| ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups); |
| |
| const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups); |
| |
| switch(opencl::ClConv2d::get_convolution_method(input->info(), weights->info(), output->info(), conv2d_info, |
| weights_info, CLScheduler::get().target())) |
| { |
| case ConvolutionMethod::WINOGRAD: |
| case ConvolutionMethod::DIRECT: |
| case ConvolutionMethod::GEMM: |
| { |
| auto f = std::make_unique<opencl::ClConv2d>(); |
| f->configure(compile_context, input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv2d_info, weights_info); |
| _impl->op = std::move(f); |
| break; |
| } |
| case ConvolutionMethod::FFT: |
| { |
| auto f = std::make_unique<CLFFTConvolutionLayer>(_impl->memory_manager); |
| f->configure(compile_context, input, weights, biases, output, conv_info, act_info, enable_fast_math); |
| _impl->func = std::move(f); |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("Not supported."); |
| break; |
| } |
| |
| if(_impl->op) |
| { |
| _impl->memory_group = MemoryGroup(std::move(_impl->memory_manager)); |
| _impl->aux_mem_req = _impl->op->workspace(); |
| _impl->run_pack = { { ACL_SRC_0, input }, { ACL_SRC_1, weights }, { ACL_SRC_2, biases }, { ACL_DST, output } }; |
| _impl->prep_pack = { { ACL_SRC_1, weights }, { ACL_SRC_2, biases } }; |
| _impl->workspace = manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack); |
| } |
| } |
| |
| Status CLConvolutionLayer::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, bool enable_fast_math, unsigned int num_groups) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG((num_groups != 1) && (input->data_layout() != DataLayout::NCHW), "Grouping (num_groups != 1) with NHWC data layout is not supported"); |
| |
| const GPUTarget gpu_target = CLScheduler::get().target(); |
| const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups); |
| |
| switch(opencl::ClConv2d::get_convolution_method(input, weights, output, conv2d_info, weights_info, gpu_target)) |
| { |
| case ConvolutionMethod::WINOGRAD: |
| case ConvolutionMethod::DIRECT: |
| case ConvolutionMethod::GEMM: |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(opencl::ClConv2d::validate(input, weights, biases, output, conv2d_info, weights_info)); |
| break; |
| } |
| case ConvolutionMethod::FFT: |
| { |
| // Validate FFT-based convolution layer |
| ARM_COMPUTE_RETURN_ON_ERROR(CLFFTConvolutionLayer::validate(input, weights, nullptr, output, conv_info, act_info, enable_fast_math)); |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("Not supported."); |
| break; |
| } |
| |
| return Status{}; |
| } |
| |
| ConvolutionMethod CLConvolutionLayer::get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output, const PadStrideInfo &conv_info, |
| const WeightsInfo &weights_info, const ActivationLayerInfo &act_info, const GPUTarget gpu_target, const Size2D &dilation, bool enable_fast_math) |
| { |
| const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, 1); |
| return opencl::ClConv2d::get_convolution_method(input, weights, output, conv2d_info, weights_info, gpu_target); |
| } |
| |
| void CLConvolutionLayer::run() |
| { |
| prepare(); |
| |
| MemoryGroupResourceScope scope_mg(_impl->memory_group); |
| |
| if(_impl->func) |
| { |
| _impl->func->run(); |
| } |
| else |
| { |
| _impl->op->run(_impl->run_pack); |
| } |
| } |
| |
| void CLConvolutionLayer::prepare() |
| { |
| if(_impl->func) |
| { |
| _impl->func->prepare(); |
| } |
| else |
| { |
| _impl->op->prepare(_impl->prep_pack); |
| |
| // Release temporary tensors that are only used in prepare stage |
| release_temporaries(_impl->aux_mem_req, _impl->workspace); |
| } |
| } |
| } // namespace arm_compute |