From bbb05692024ad43f2ebd8b75a18dd377b41cb8c5 Mon Sep 17 00:00:00 2001
From: Olivier BICHLER <olivier.bichler@cea.fr>
Date: Thu, 7 Dec 2023 00:29:31 +0100
Subject: [PATCH] Fixed missing initialization
---
.../aidge/backend/cpu/operator/AddImpl.hpp | 12 ------
.../cpu/operator/AddImpl_forward_kernels.hpp | 11 +++---
.../AvgPoolingImpl_forward_kernels.hpp | 1 +
src/operator/AddImpl.cpp | 37 +------------------
4 files changed, 8 insertions(+), 53 deletions(-)
diff --git a/include/aidge/backend/cpu/operator/AddImpl.hpp b/include/aidge/backend/cpu/operator/AddImpl.hpp
index 806bbb02..bfa6fd2b 100644
--- a/include/aidge/backend/cpu/operator/AddImpl.hpp
+++ b/include/aidge/backend/cpu/operator/AddImpl.hpp
@@ -38,19 +38,7 @@ public:
return std::make_unique<AddImpl_cpu>(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() override;
};
diff --git a/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp
index 198bcbac..631ad44a 100644
--- a/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp
@@ -27,11 +27,12 @@ void AddImpl_cpu_forward_kernel(const std::size_t inputLength, const std::vector
}
O* output = static_cast<O*>(output_);
- for (std::size_t iIndex = 0; iIndex < inputs.size(); ++iIndex) {
- for (std::size_t oIndex = 0; oIndex < inputLength; ++oIndex) {
- output[oIndex] += inputs[iIndex][oIndex];
- }
- }
+ for (std::size_t oIndex = 0; oIndex < inputLength; ++oIndex) {
+ output[oIndex] = 0;
+ for (std::size_t iIndex = 0; iIndex < inputs.size(); ++iIndex) {
+ output[oIndex] += inputs[iIndex][oIndex];
+ }
+ }
}
namespace {
diff --git a/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp
index ea46a540..13c07151 100644
--- a/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/AvgPoolingImpl_forward_kernels.hpp
@@ -60,6 +60,7 @@ void AvgPoolingImpl2D_cpu_forward_kernel(const AvgPooling_Op<2>::Attrs &attrs,
for (std::size_t ch = 0; ch < dims[1]; ++ch) {
const std::size_t oIndex = (ch + batch*dims[1]) * oxSize * oySize;
const std::size_t iIndex = (ch + batch*dims[1]) * dims[2] * dims[3];
+ std::fill(output + oIndex, output+(oIndex+oxSize*oySize), 0);
for (std::size_t ox = 0; ox < oxSize; ++ox) {
const signedsize difx = static_cast<signedsize>(- ox * std::get<0>(attrs)[0]);
const std::size_t sxMin = static_cast<std::size_t>(std::max(difx, signedsize(0)));
diff --git a/src/operator/AddImpl.cpp b/src/operator/AddImpl.cpp
index 851aaa5c..fc54eca6 100644
--- a/src/operator/AddImpl.cpp
+++ b/src/operator/AddImpl.cpp
@@ -20,46 +20,11 @@
#include "aidge/backend/cpu/operator/AddImpl.hpp"
#include "aidge/backend/cpu/operator/AddImpl_forward_kernels.hpp"
-Aidge::NbElts_t Aidge::AddImpl_cpu::getNbRequiredData(const Aidge::IOIndex_t inputIdx) const {
- assert(mOp.getRawInput(inputIdx) && "requires valid input");
-
- // Requires the whole tensors
- const auto& inputDims = std::static_pointer_cast<Tensor>(mOp.getRawInput(inputIdx))->dims();
- return std::accumulate(inputDims.begin(), inputDims.end(), NbElts_t(1), std::multiplies<NbElts_t>());
-}
-
Aidge::NbElts_t Aidge::AddImpl_cpu::getNbRequiredProtected(const Aidge::IOIndex_t /*inputIdx*/) const {
- // for the direct convolution algorithm, convolutions can be in-place, if there is no padding!
+ // this implementation can be in-place
return 0;
}
-Aidge::NbElts_t Aidge::AddImpl_cpu::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.getRawOutput(0))->dims();
- return std::accumulate(outputDims.begin(), outputDims.end(), NbElts_t(1), std::multiplies<NbElts_t>());
-}
-
-Aidge::NbElts_t Aidge::AddImpl_cpu::getNbConsumedData(const Aidge::IOIndex_t inputIdx) const {
- assert(inputIdx < mNbConsumedData.size());
- return mNbConsumedData[inputIdx];
-}
-
-Aidge::NbElts_t Aidge::AddImpl_cpu::getNbProducedData(const Aidge::IOIndex_t outputIdx) const {
- assert(outputIdx < mNbProducedData.size());
- return mNbProducedData[outputIdx];
-}
-
-void Aidge::AddImpl_cpu::updateConsummerProducer() {
- for (IOIndex_t inputIdx = 0; static_cast<NbElts_t>(inputIdx) < mNbConsumedData.size(); ++inputIdx)
- mNbConsumedData[inputIdx]+= getNbRequiredData(inputIdx); // each input is consumed by the minimum amount for a forward pass
-
- mNbProducedData[0]+= getRequiredMemory(0, {});
-
-}
-
void Aidge::AddImpl_cpu::forward() {
assert(mOp.getRawInput(0) && "missing input in Add operator");
DataType datatypeFirstInput = std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dataType();
--
GitLab