/* * Copyright (c) 2017-2018 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/CLDirectConvolutionLayer.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/CL/kernels/CLDirectConvolutionLayerKernel.h" #include "arm_compute/core/PixelValue.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/CL/CLScheduler.h" using namespace arm_compute; CLDirectConvolutionLayer::CLDirectConvolutionLayer() : _direct_conv_kernel(), _input_border_handler(), _activationlayer_function(), _is_activationlayer_enabled(false) { } void CLDirectConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info) { // Set GPU target _direct_conv_kernel.set_target(CLScheduler::get().target()); // Configure direct convolution _direct_conv_kernel.configure(input, weights, biases, output, conv_info); // Configure border handler PixelValue &&zero_value(0.f); if(is_data_type_quantized_asymmetric(input->info()->data_type())) { zero_value = PixelValue(static_cast(input->info()->quantization_info().offset)); } _input_border_handler.configure(input, _direct_conv_kernel.border_size(), BorderMode::CONSTANT, zero_value); // Tune kernels CLScheduler::get().tune_kernel_static(_direct_conv_kernel); _is_activationlayer_enabled = act_info.enabled(); //Configure Activation Layer if(_is_activationlayer_enabled) { _activationlayer_function.configure(output, nullptr, act_info); } } Status CLDirectConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info) { ARM_COMPUTE_RETURN_ON_ERROR(CLDirectConvolutionLayerKernel::validate(input, weights, biases, output, conv_info, CLScheduler::get().target())); if(act_info.enabled()) { ARM_COMPUTE_RETURN_ON_ERROR(CLActivationLayer::validate(output, nullptr, act_info)); } return Status{}; } void CLDirectConvolutionLayer::run() { // Run border handler CLScheduler::get().enqueue(_input_border_handler, false); // Run direct convolution CLScheduler::get().enqueue(_direct_conv_kernel); //Run Activation Layer if(_is_activationlayer_enabled) { _activationlayer_function.run(); } }