/******************************************************************************** * Copyright (c) 2023 CEA-List * * This program and the accompanying materials are made available under the * terms of the Eclipse Public License 2.0 which is available at * http://www.eclipse.org/legal/epl-2.0. * * SPDX-License-Identifier: EPL-2.0 * ********************************************************************************/ #include "aidge/operator/FC.hpp" #include <memory> #include <string> #include <vector> #include "aidge/data/Data.hpp" #include "aidge/data/Tensor.hpp" #include "aidge/utils/ErrorHandling.hpp" #include "aidge/utils/StaticAttributes.hpp" #include "aidge/utils/Types.h" const std::string Aidge::FC_Op::Type = "FC"; void Aidge::FC_Op::associateInput(const Aidge::IOIndex_t inputIdx, const std::shared_ptr<Aidge::Data>& data) { AIDGE_ASSERT(inputIdx < 3, "Operators {} supports only {} inputs", type(), nbInputs()); AIDGE_ASSERT(data->type() == Tensor::Type, "input data must be of Tensor type"); // TODO: FIXME: check this, because data dims may not be initialized at this point... //if (inputIdx == 2) { // assert(std::dynamic_pointer_cast<Tensor>(data)->size() == ((this->template getAttr<FCAttr::NoBias>()) == false ? static_cast<std::size_t>(this->template getAttr<FCAttr::OutChannels>()) : 0)); // assert(std::dynamic_pointer_cast<Tensor>(data)->nbDims() == 1); //} mInputs[inputIdx] = std::dynamic_pointer_cast<Tensor>(data); if (inputIdx == 0 && getInput(0)->nbDims() == 1) mInputs[inputIdx]->resize({1, getInput(inputIdx)->size()}); } void Aidge::FC_Op::computeOutputDims() { bool associated = true; for (IOIndex_t i = 0; i < nbInputs(); ++i) { if (!getInput(i)) { AIDGE_THROW_OR_ABORT(std::runtime_error, "{}: input #{} should be associated with a Tensor", type(), i); } associated &= !(getInput(i)->empty()); } if (associated) { // <batch, OutChannels> mOutputs[0]->resize({getInput(0)->dims()[0], this->template getAttr<FCAttr::OutChannels>()}); } } void Aidge::FC_Op::setBackend(const std::string& name, Aidge::DeviceIdx_t device) { SET_IMPL_MACRO(FC_Op, *this, name); mOutputs[0]->setBackend(name, device); // By default, automatically set backend for weight and bias inputs getInput(1)->setBackend(name, device); getInput(2)->setBackend(name, device); }