diff --git a/src/operator/GlobalAveragePoolingImpl.cpp b/src/operator/GlobalAveragePoolingImpl.cpp index 50048f71504e5910226ece50373b49695a5c9094..f7280360a4486fe5db6c4dfdd4c492bbe6ba302b 100644 --- a/src/operator/GlobalAveragePoolingImpl.cpp +++ b/src/operator/GlobalAveragePoolingImpl.cpp @@ -9,29 +9,33 @@ * ********************************************************************************/ -#include <cassert> -#include <chrono> // std::chrono::milliseconds -#include <numeric> // std::accumulate -#include <thread> // std::this_thread::sleep_for +#include "aidge/backend/cpu/operator/GlobalAveragePoolingImpl.hpp" + +#include <functional> +#include <memory> #include <vector> +#include "aidge/backend/cpu/operator/GlobalAveragePoolingImpl_forward_kernels.hpp" +#include "aidge/data/Data.hpp" +#include "aidge/data/Tensor.hpp" #include "aidge/operator/GlobalAveragePooling.hpp" +#include "aidge/utils/ErrorHandling.hpp" +#include "aidge/utils/Registrar.hpp" #include "aidge/utils/Types.h" -#include "aidge/backend/cpu/operator/GlobalAveragePoolingImpl.hpp" -#include "aidge/backend/cpu/operator/GlobalAveragePoolingImpl_forward_kernels.hpp" void Aidge::GlobalAveragePoolingImpl_cpu::forward() { + const GlobalAveragePooling_Op& op_ = static_cast<const GlobalAveragePooling_Op&>(mOp); // Check if input is provided - assert(std::static_pointer_cast<Tensor>(mOp.getRawInput(0)) && "missing input"); + AIDGE_ASSERT(op_.getInput(0), "missing input 0"); // Create the forward kernal with the wanted types - auto kernelFunc = Registrar<GlobalAveragePoolingImplForward_cpu>::create({std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dataType(), - std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->dataType()}); + auto kernelFunc = Registrar<GlobalAveragePoolingImplForward_cpu>::create({op_.getInput(0)->dataType(), + op_.getOutput(0)->dataType()}); // Call kernel - kernelFunc(std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dims(), - std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->getImpl()->rawPtr(), - std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl()->rawPtr()); + kernelFunc(op_.getInput(0)->dims(), + op_.getInput(0)->getImpl()->rawPtr(), + op_.getOutput(0)->getImpl()->rawPtr()); } \ No newline at end of file