/* * Copyright (c) 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/ClIndirectConv2d.h" #include "arm_compute/core/KernelDescriptors.h" #include "arm_compute/core/Types.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/helpers/MemoryHelpers.h" #include "src/gpu/cl/kernels/ClIndirectConv2dAddressPrecalculationKernel.h" #include "src/gpu/cl/kernels/ClIndirectConv2dKernel.h" #include "src/gpu/cl/utils/ClAuxTensorHandler.h" #include "src/runtime/heuristics/indirect_conv/ClIndirectConvKernelConfig.h" #include "src/runtime/heuristics/indirect_conv/IClIndirectConvKernelConfig.h" using namespace arm_compute::cl_indirect_conv; namespace arm_compute { namespace opencl { using namespace arm_compute::experimental; namespace { DirectConvComputeKernelInfo config_indirect_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 = ClIndirectConvKernelConfigurationFactory::create(gpu_target); return t->configure(src, weights, conv_info); } } // namespace void ClIndirectConv2d::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); // Reuse the direct convolution descriptor const DirectConvComputeKernelInfo desc = config_indirect_convolution_nhwc(src, weights, conv_info); // Configure indirect convolution kernels auto k0 = std::make_unique(); auto k1 = std::make_unique(); k0->set_target(CLScheduler::get().target()); k1->set_target(CLScheduler::get().target()); k0->configure(compile_context, src, weights, &_indirect_buffer, conv_info, desc); k1->configure(compile_context, src, weights, biases, &_indirect_buffer, dst, conv_info, act_info, desc); _addr_precalculation_kernel = std::move(k0); _indirect_conv_kernel = std::move(k1); _is_prepared = false; // Tune kernels CLScheduler::get().tune_kernel_static(*_indirect_conv_kernel); // Request memory for the indirect buffer _aux_mem[IndirectBuffer] = MemoryInfo(offset_int_vec(IndirectBuffer), MemoryLifetime::Persistent, _indirect_buffer.total_size()); } Status ClIndirectConv2d::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_indirect_convolution_nhwc(src, weights, conv_info); TensorShape ind_buffer_shape = misc::shape_calculator::compute_indirect_buffer_shape( src->tensor_shape(), src->data_layout(), weights->tensor_shape(), conv_info, desc); TensorInfo indirect_buffer(ind_buffer_shape, 1, DataType::S32); ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClIndirectConv2dAddressPrecalculationKernel::validate( src, weights, &indirect_buffer, conv_info, desc)); ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClIndirectConv2dKernel::validate(src, weights, biases, &indirect_buffer, dst, conv_info, act_info, desc)); return Status{}; } void ClIndirectConv2d::run(ITensorPack &tensors) { CLAuxTensorHandler indirect_buffer(offset_int_vec(IndirectBuffer), _indirect_buffer, tensors, true); prepare(tensors); ITensorPack indirect_conv2d_pack(tensors); indirect_conv2d_pack.add_const_tensor(ACL_SRC_3, indirect_buffer.get()); // Run indirect convolution CLScheduler::get().enqueue_op(*_indirect_conv_kernel, indirect_conv2d_pack, true); } void ClIndirectConv2d::prepare(ITensorPack &constants) { if (!_is_prepared) { ICLTensor *indirect_buffer_aux = utils::cast::polymorphic_downcast(constants.get_tensor(offset_int_vec(IndirectBuffer))); ARM_COMPUTE_ERROR_ON(indirect_buffer_aux == nullptr); ARM_COMPUTE_LOG_INFO_WITH_FUNCNAME_ACL("Preparing indirect buffer"); CLAuxTensorHandler indirect_buffer(_indirect_buffer, *indirect_buffer_aux); ARM_COMPUTE_ERROR_ON(indirect_buffer.get()->cl_buffer().get() == nullptr); ITensorPack indirect_buffer_pack{{ACL_DST, indirect_buffer.get()}}; CLScheduler::get().enqueue_op(*_addr_precalculation_kernel, indirect_buffer_pack, true); _is_prepared = true; } } experimental::MemoryRequirements ClIndirectConv2d::workspace() const { return _aux_mem; } } // namespace opencl } // namespace arm_compute