From 74886e269a94b2cecefb7e1f747ff93ecfe5879a Mon Sep 17 00:00:00 2001
From: Olivier BICHLER <olivier.bichler@cea.fr>
Date: Fri, 20 Oct 2023 16:30:19 +0200
Subject: [PATCH] Updated op impl with new default impl
---
.../aidge/backend/cuda/operator/ConvImpl.hpp | 18 +------
src/operator/ConvImpl.cpp | 53 -------------------
2 files changed, 1 insertion(+), 70 deletions(-)
diff --git a/include/aidge/backend/cuda/operator/ConvImpl.hpp b/include/aidge/backend/cuda/operator/ConvImpl.hpp
index 9391998..31b80ad 100644
--- a/include/aidge/backend/cuda/operator/ConvImpl.hpp
+++ b/include/aidge/backend/cuda/operator/ConvImpl.hpp
@@ -27,15 +27,9 @@
#include "aidge/backend/cuda/utils/CudaUtils.hpp"
namespace Aidge {
-// class Conv_Op;
-
template <DimIdx_t DIM>
class ConvImpl_cuda : public OperatorImpl {
private:
- const Conv_Op<DIM> &mOp;
- std::array<NbElts_t, 3> mNbConsumedData = {0, 0, 0};
- std::array<NbElts_t, 1> mNbProducedData = {0};
-
// CuDNN specific variables
cudnnConvolutionDescriptor_t mConvDesc = nullptr;
cudnnFilterDescriptor_t mFilterDesc = nullptr;
@@ -44,24 +38,14 @@ private:
void* mWorkspace = nullptr;
public:
- ConvImpl_cuda(const Conv_Op<DIM> &op) : mOp(op) {}
+ ConvImpl_cuda(const Conv_Op<DIM> &op) : OperatorImpl(op) {}
static std::unique_ptr<ConvImpl_cuda> create(const Conv_Op<2> &op) {
return std::make_unique<ConvImpl_cuda>(op);
}
public:
- NbElts_t getNbRequiredData(const IOIndex_t inputIdx) const override final;
- NbElts_t getNbRequiredProtected(const IOIndex_t inputIdx) const override final;
- NbElts_t getRequiredMemory(const IOIndex_t /*outputIdx*/, const std::vector<DimSize_t> &/*inputsSize*/) const override final;
- NbElts_t getNbConsumedData(const IOIndex_t inputIdx) const override final;
- NbElts_t getNbProducedData(const IOIndex_t outputIdx) const override final;
- void updateConsummerProducer() override final;
-
void forward();
-
- void backward();
-
~ConvImpl_cuda();
private:
diff --git a/src/operator/ConvImpl.cpp b/src/operator/ConvImpl.cpp
index e21bc92..3591bdf 100644
--- a/src/operator/ConvImpl.cpp
+++ b/src/operator/ConvImpl.cpp
@@ -22,56 +22,6 @@
#include "aidge/backend/cuda/operator/ConvImpl.hpp"
#include "aidge/backend/cuda/utils/CudaContext.hpp"
-template <Aidge::DimIdx_t DIM>
-Aidge::NbElts_t Aidge::ConvImpl_cuda<DIM>::getNbRequiredData(const Aidge::IOIndex_t inputIdx) const {
- assert(mOp.getInput(inputIdx) && "requires valid input");
-
- // Requires the whole tensors
- const auto &inputDims = std::static_pointer_cast<Tensor>(mOp.getInput(inputIdx))->dims();
-
- return std::accumulate(inputDims.begin(), inputDims.end(), Aidge::NbElts_t(1), std::multiplies<NbElts_t>());
-}
-
-template <Aidge::DimIdx_t DIM>
-Aidge::NbElts_t Aidge::ConvImpl_cuda<DIM>::getNbRequiredProtected(IOIndex_t /*inputIdx*/) const {
- // for the direct convolution algorithm, convolutions can be in-place, if
- // there is no padding!
- return 0;
-}
-
-template <Aidge::DimIdx_t DIM>
-Aidge::NbElts_t Aidge::ConvImpl_cuda<DIM>::getRequiredMemory(const Aidge::IOIndex_t outputIdx,
- const std::vector<Aidge::DimSize_t> &/*inputsSize*/) const {
- // Requires the whole tensors, regardless of available data on inputs
- assert(outputIdx == 0 && "operator has only one output");
- (void) outputIdx;
-
- const auto &outputDims = std::static_pointer_cast<Tensor>(mOp.getOutput(0))->dims();
- return std::accumulate(outputDims.begin(), outputDims.end(), NbElts_t(1), std::multiplies<NbElts_t>());
-}
-
-template <Aidge::DimIdx_t DIM>
-Aidge::NbElts_t Aidge::ConvImpl_cuda<DIM>::getNbConsumedData(Aidge::IOIndex_t inputIdx) const {
- assert(static_cast<std::size_t>(inputIdx) < mNbConsumedData.size());
- return mNbConsumedData[static_cast<std::size_t>(inputIdx)];
-}
-
-template <Aidge::DimIdx_t DIM>
-Aidge::NbElts_t Aidge::ConvImpl_cuda<DIM>::getNbProducedData(Aidge::IOIndex_t outputIdx) const {
- assert((outputIdx == 0) && (static_cast<std::size_t>(outputIdx) < mNbProducedData.size()));
- return mNbProducedData[static_cast<std::size_t>(outputIdx)];
-}
-
-template <Aidge::DimIdx_t DIM>
-void Aidge::ConvImpl_cuda<DIM>::updateConsummerProducer(){
- // Update producer-consumer data
- for (std::size_t inputIdx = 0; inputIdx < mNbConsumedData.size(); ++inputIdx)
- mNbConsumedData[inputIdx] += getNbRequiredData(static_cast<IOIndex_t>(inputIdx)); // each input is consumed by the minimum
- // amount for a forward pass
-
- mNbProducedData[0] += getRequiredMemory(0, {});
-}
-
template <Aidge::DimIdx_t DIM>
void Aidge::ConvImpl_cuda<DIM>::forward() {
// FIXME: uncomment the following code once memory handling will work
@@ -215,9 +165,6 @@ Aidge::ConvImpl_cuda<DIM>::~ConvImpl_cuda() {
}
}
-template <Aidge::DimIdx_t DIM>
-void Aidge::ConvImpl_cuda<DIM>::backward() { printf("Not implemented yet.\n"); }
-
// Template declarations
template class Aidge::ConvImpl_cuda<2>;
--
GitLab