diff --git a/include/aidge/backend/cpu/operator/ReduceMeanImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/ReduceMeanImpl_forward_kernels.hpp
index 25796f222a35261ddbeb9032e9dd1c4e79ccc263..d7a967e84f53924a4b050ed79d1220f9bc79232e 100644
--- a/include/aidge/backend/cpu/operator/ReduceMeanImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/ReduceMeanImpl_forward_kernels.hpp
@@ -96,7 +96,7 @@ void ReduceMeanImpl_cpu_forward_kernel(const typename ReduceMean_Op::Attrs& attr
// Copy elements from inputAccumulation to output while dividing by divisor
I divisor = totalElements / outputElements;
std::transform(inputAccumulation, inputAccumulation + outputElements, output,
- [divisor](int element) { return element / divisor; });
+ [divisor](I element) { return element / divisor; });
if (outputAccumulation) {
delete[] outputAccumulation;
}
diff --git a/src/operator/ReshapeImpl.cpp b/src/operator/ReshapeImpl.cpp
index 02dea1da3d4422abf37b62193bba83e83c87a83f..11df6f663d9a78476103d9671d9d428719c0126d 100644
--- a/src/operator/ReshapeImpl.cpp
+++ b/src/operator/ReshapeImpl.cpp
@@ -9,13 +9,13 @@
*
********************************************************************************/
-#include <cassert>
+#include "aidge/backend/cpu/operator/ReshapeImpl.hpp"
+#include "aidge/backend/cpu/operator/ReshapeImpl_forward_kernels.hpp"
+#include "aidge/data/Tensor.hpp"
#include "aidge/operator/Reshape.hpp"
#include "aidge/utils/Types.h"
-
-#include "aidge/backend/cpu/operator/ReshapeImpl.hpp"
-#include "aidge/backend/cpu/operator/ReshapeImpl_forward_kernels.hpp"
+#include "aidge/utils/ErrorHandling.hpp"
Aidge::NbElts_t Aidge::ReshapeImpl_cpu::getNbRequiredProtected(const Aidge::IOIndex_t /*inputIdx*/) const {
// this implementation can be in-place
@@ -23,17 +23,17 @@ Aidge::NbElts_t Aidge::ReshapeImpl_cpu::getNbRequiredProtected(const Aidge::IOIn
}
void Aidge::ReshapeImpl_cpu::forward() {
- assert(std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->size() ==
- std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->size()
- && "input must have the same overall size as shape");
+ const Reshape_Op& op_ = static_cast<const Reshape_Op&>(mOp);
+ AIDGE_ASSERT(op_.getInput(0)->size() == op_.getOutput(0)->size(),
+ "input must have the same overall size as shape");
// Find the correct kernel type
auto kernelFunc = Registrar<ReshapeImplForward_cpu>::create({
- std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dataType(),
- std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->dataType()});
+ op_.getInput(0)->dataType(),
+ op_.getOutput(0)->dataType()});
// Call kernel
- kernelFunc(std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->size(),
- std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->getImpl()->rawPtr(),
- std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->getImpl()->rawPtr());
+ kernelFunc(op_.getInput(0)->size(),
+ op_.getInput(0)->getImpl()->rawPtr(),
+ op_.getOutput(0)->getImpl()->rawPtr());
}
diff --git a/unit_tests/operator/Test_ReduceMeanImpl.cpp b/unit_tests/operator/Test_ReduceMeanImpl.cpp
index 494b7a6ace17173ef7b956bc9dabf4d27e665e5a..d9bf68b78d1ece371cbfb5cda3c502f82eaf97de 100644
--- a/unit_tests/operator/Test_ReduceMeanImpl.cpp
+++ b/unit_tests/operator/Test_ReduceMeanImpl.cpp
@@ -17,6 +17,7 @@
#include "aidge/operator/Conv.hpp"
#include "aidge/backend/cpu.hpp"
+#include "aidge/utils/TensorUtils.hpp"
using namespace Aidge;
@@ -138,35 +139,60 @@ TEST_CASE("[cpu/operator] ReduceMean(forward)", "[ReduceMean][CPU]") {
}
SECTION("all_axes") {
- std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array3D<float,3,2,2> {
- {
- {
- { 5.0, 1.0 },
- { 20.0, 2.0 }
- },
- {
- { 30.0, 1.0 },
- { 40.0, 2.0 }
- },
+ SECTION("1") {
+ std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array3D<float,3,2,2> {
{
- { 55.0, 1.0 },
- { 60.0, 2.0 }
+ {
+ { 5.0, 1.0 },
+ { 20.0, 2.0 }
+ },
+ {
+ { 30.0, 1.0 },
+ { 40.0, 2.0 }
+ },
+ {
+ { 55.0, 1.0 },
+ { 60.0, 2.0 }
+ }
}
- }
- });
- std::shared_ptr<Tensor> myOutput = std::make_shared<Tensor>(Array1D<float,1> {
- {18.25}
- });
+ });
+ std::shared_ptr<Tensor> myOutput = std::make_shared<Tensor>(Array1D<float,1> {
+ {18.25}
+ });
- std::shared_ptr<Node> myReduceMean = ReduceMean({0, 1, 2}, 0);
- auto op = std::static_pointer_cast<OperatorTensor>(myReduceMean -> getOperator());
- op->associateInput(0,myInput);
- op->setDataType(DataType::Float32);
- op->setBackend("cpu");
- op->computeOutputDims();
- myReduceMean->forward();
- op->getOutput(0)->print();
+ std::shared_ptr<Node> myReduceMean = ReduceMean({0, 1, 2}, 0);
+ auto op = std::static_pointer_cast<OperatorTensor>(myReduceMean -> getOperator());
+ op->associateInput(0,myInput);
+ op->setDataType(DataType::Float32);
+ op->setBackend("cpu");
+ op->computeOutputDims();
+ myReduceMean->forward();
+ op->getOutput(0)->print();
- REQUIRE(*(op->getOutput(0)) == *myOutput);
+ REQUIRE(*(op->getOutput(0)) == *myOutput);
+ }
+ SECTION("2") {
+ std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array2D<float,5,4> {
+ {{ 0.004232f, 0.105120f, 0.045124f, 0.009205f},
+ { 0.000766f, 0.272162f, 0.503560f, 0.044163f},
+ { 0.049755f, 0.000305f, 0.143634f, 0.013253f},
+ { 0.096258f, 0.311231f, 0.358143f, 0.000452f},
+ { 0.468617f, 0.015693f, 0.145316f, 0.000105f}}
+ });
+ std::shared_ptr<Tensor> myOutput = std::make_shared<Tensor>(Array1D<float,1> {
+ {0.1293547f}
+ });
+
+ std::shared_ptr<Node> myReduceMean = ReduceMean({0, 1}, 0);
+ auto op = std::static_pointer_cast<OperatorTensor>(myReduceMean -> getOperator());
+ op->associateInput(0,myInput);
+ op->setDataType(DataType::Float32);
+ op->setBackend("cpu");
+ op->computeOutputDims();
+ myReduceMean->forward();
+ op->getOutput(0)->print();
+ // approxEq<float>(*(op->getOutput(0)), *myOutput);
+ REQUIRE(approxEq<float>(*(op->getOutput(0)), *myOutput));
+ }
}
}
\ No newline at end of file