/* * Copyright (c) 2021-2022 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 "src/gpu/cl/operators/ClDirectConv2d.h" #include "arm_compute/core/KernelDescriptors.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/common/utils/Log.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/gpu/cl/kernels/ClActivationKernel.h" #include "src/gpu/cl/kernels/ClDirectConv2dKernel.h" #include "src/runtime/heuristics/direct_conv/ClDirectConvDefaultConfigBifrost.h" #include "src/runtime/heuristics/direct_conv/ClDirectConvDefaultConfigValhall.h" #include "src/runtime/heuristics/direct_conv/ClDirectConvKernelConfig.h" #include "src/runtime/heuristics/direct_conv/IClDirectConvKernelConfig.h" using namespace arm_compute::cl_direct_conv; namespace arm_compute { namespace opencl { namespace { ITensorPack select_activation_src_dst(ITensorPack &tensors) { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC, tensors.get_tensor(TensorType::ACL_DST)); pack.add_tensor(TensorType::ACL_DST, tensors.get_tensor(TensorType::ACL_DST)); return pack; } DirectConvComputeKernelInfo config_direct_convolution_nhwc(const ITensorInfo *src, const ITensorInfo *weights, const PadStrideInfo &conv_info) { // Get GPU target GPUTarget gpu_target = CLScheduler::get().target(); std::unique_ptr t = ClDirectConvKernelConfigurationFactory::create(gpu_target); return t->configure(src, weights, conv_info); } } // namespace void ClDirectConv2d::configure(const CLCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *dst, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(src); ARM_COMPUTE_LOG_PARAMS(src, weights, biases, dst, conv_info, act_info); // Initialize the direct convolution descriptor const DirectConvComputeKernelInfo desc = config_direct_convolution_nhwc(src, weights, conv_info); // Configure direct convolution kernel const ActivationLayerInfo conv2d_act_info = (src->data_layout() == DataLayout::NHWC && is_data_type_float(src->data_type())) ? act_info : ActivationLayerInfo(); auto k = std::make_unique(); k->set_target(CLScheduler::get().target()); k->configure(compile_context, src, weights, biases, dst, conv_info, conv2d_act_info, desc); _direct_conv_kernel = std::move(k); // Configure border handler PixelValue zero_value(0.f); if (is_data_type_quantized_asymmetric(src->data_type())) { zero_value = PixelValue(0, src->data_type(), src->quantization_info()); } auto b = std::make_unique(); b->configure(compile_context, src, _direct_conv_kernel->border_size(), BorderMode::CONSTANT, zero_value); _src_border_handler = std::move(b); // Fused activation is currently supported for NHWC and floating point types if (act_info.enabled() && !conv2d_act_info.enabled()) { auto a = std::make_unique(); a->configure(compile_context, dst, dst, act_info); _activation_kernel = std::move(a); } // Tune kernels CLScheduler::get().tune_kernel_static(*_direct_conv_kernel); } Status ClDirectConv2d::validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info) { // Initialize the direct convolution descriptor const DirectConvComputeKernelInfo desc = config_direct_convolution_nhwc(src, weights, conv_info); ARM_COMPUTE_RETURN_ON_ERROR( kernels::ClDirectConv2dKernel::validate(src, weights, biases, dst, conv_info, ActivationLayerInfo(), desc)); if (act_info.enabled()) { ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClActivationKernel::validate(dst, dst, act_info)); } return Status{}; } void ClDirectConv2d::run(ITensorPack &tensors) { // Run border handler CLScheduler::get().enqueue_op(*_src_border_handler.get(), tensors, false); // Run direct convolution CLScheduler::get().enqueue_op(*_direct_conv_kernel.get(), tensors, false); // Run activation kernel if (_activation_kernel) { auto act_pack = select_activation_src_dst(tensors); CLScheduler::get().enqueue_op(*_activation_kernel.get(), act_pack, false); } } } // namespace opencl } // namespace arm_compute