diff --git a/include/aidge/backend/cpu/operator/AvgPoolingImpl_kernels.hpp b/include/aidge/backend/cpu/operator/AvgPoolingImpl_kernels.hpp
index 78f8446a1acd86a8d569dc0afb22a2517bcfede0..1671759d25a5965ceca57fc1167534d7986282c4 100644
--- a/include/aidge/backend/cpu/operator/AvgPoolingImpl_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/AvgPoolingImpl_kernels.hpp
@@ -23,6 +23,22 @@
#include "aidge/utils/Types.h"
namespace Aidge {
+
+template <typename T>
+using Acc_T = typename std::conditional<std::is_floating_point<T>::value, T, double>::type;
+
+template <typename T>
+typename std::enable_if<std::is_floating_point<T>::value, T>::type
+castFromFloat(T value) {
+ return value;
+}
+
+template <typename T>
+typename std::enable_if<!std::is_floating_point<T>::value, T>::type
+castFromFloat(double value) {
+ return static_cast<T>(std::nearbyint(value));
+}
+
/**
* @brief Forward kernel for 2D AvgPoolingolution on CPU backend.
* @tparam I Input data type.
@@ -79,7 +95,7 @@ void AvgPoolingImpl2D_cpu_forward_kernel(const std::array<DimSize_t, 2>& strideD
const std::size_t ix = ox * strideDims[0];
const std::size_t iy = oy * strideDims[1];
- O sum = static_cast<O>(0);
+ Acc_T<I> sum = static_cast<Acc_T<I>>(0);
std::size_t count = 0;
for (unsigned int sy = syMin; sy < syMax; ++sy) {
@@ -90,13 +106,13 @@ void AvgPoolingImpl2D_cpu_forward_kernel(const std::array<DimSize_t, 2>& strideD
// Ensure within bounds
if ((ix + dilated_sx) < dims[2] && (iy + dilated_sy) < dims[3]) {
- sum += static_cast<O>(input[iIndex + (ix + dilated_sx) * dims[3] + (iy + dilated_sy)]);
+ sum += static_cast<Acc_T<I>>(input[iIndex + (ix + dilated_sx) * dims[3] + (iy + dilated_sy)]);
++count;
}
}
}
- output[oIndexFull] = count > 0 ? sum / static_cast<O>(count) : 0;
+ output[oIndexFull] = count > 0 ? castFromFloat<O>(sum / count) : 0;
}
}
}
diff --git a/include/aidge/backend/cpu/operator/GlobalAveragePoolingImpl_kernels.hpp b/include/aidge/backend/cpu/operator/GlobalAveragePoolingImpl_kernels.hpp
index d5e5561d02aacd8532f74d2bfd4ee2fb5a5b5dc3..7a47ccf3be4de2ee066d2d7c27a6c04f115059b4 100644
--- a/include/aidge/backend/cpu/operator/GlobalAveragePoolingImpl_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/GlobalAveragePoolingImpl_kernels.hpp
@@ -38,7 +38,7 @@ stableMean(const T* vec, size_t size) {
// Specialization for integers: perform the mean computation in float
template <typename T>
-typename std::enable_if<!std::is_floating_point<T>::value, T>::type
+typename std::enable_if<!std::is_floating_point<T>::value, double>::type
stableMean(const T* vec, size_t size) {
double mean = 0;
for (size_t i = 0; i < size; ++i) {
diff --git a/include/aidge/backend/cpu/operator/ReduceMeanImpl_kernels.hpp b/include/aidge/backend/cpu/operator/ReduceMeanImpl_kernels.hpp
index 864b89c4fa4667b70e43ed7436382e30bc150745..a156232230bd6e9be496eec2b76ccf8fcab4d9e9 100644
--- a/include/aidge/backend/cpu/operator/ReduceMeanImpl_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/ReduceMeanImpl_kernels.hpp
@@ -25,6 +25,9 @@
#include "aidge/utils/Registrar.hpp"
namespace Aidge {
+
+template <typename T>
+using Acc_T = typename std::conditional<std::is_floating_point<T>::value, T, double>::type;
template <typename T>
typename std::enable_if<std::is_floating_point<T>::value, T>::type
@@ -38,7 +41,7 @@ stableMean(const T* vec, size_t len, size_t stride) {
// Specialization for integers: perform the mean computation in float
template <typename T>
-typename std::enable_if<!std::is_floating_point<T>::value, T>::type
+typename std::enable_if<!std::is_floating_point<T>::value, double>::type
stableMean(const T* vec, size_t len, size_t stride) {
double mean = 0;
for (size_t i = 0; i < len; ++i) {
@@ -102,13 +105,13 @@ void ReduceMeanImpl_cpu_forward_kernel(const std::vector<std::int32_t>& axes,
}
// Type should be the return type of stableMean<I>(), which is always floating point
- const decltype(stableMean<I>(input, 0, 0))* inputAccumulation = nullptr;
- decltype(stableMean<I>(input, 0, 0))* outputAccumulation = nullptr;
+ const Acc_T<I>* inputAccumulation = nullptr;
+ Acc_T<I>* outputAccumulation = nullptr;
for (const auto& axisInt : axes) {
const std::size_t a = static_cast<std::size_t>(axisInt);
outputElements /= inputDims[a];
- outputAccumulation = new I[outputElements];
+ outputAccumulation = new Acc_T<I>[outputElements];
const std::size_t dim_i = inputDims[a];
for (std::size_t pre = 0; pre < stride_pre[a]; ++pre) {
for (std::size_t post = 0; post < stride_post[a]; ++post) {
@@ -118,7 +121,7 @@ void ReduceMeanImpl_cpu_forward_kernel(const std::vector<std::int32_t>& axes,
outputAccumulation[idx_o] = stableMean<I>(input + idx_i, dim_i, stride_post[a]);
}
else {
- outputAccumulation[idx_o] = stableMean<I>(inputAccumulation + idx_i, dim_i, stride_post[a]);
+ outputAccumulation[idx_o] = stableMean<Acc_T<I>>(inputAccumulation + idx_i, dim_i, stride_post[a]);
}
}
}
diff --git a/unit_tests/operator/Test_AvgPoolingImpl.cpp b/unit_tests/operator/Test_AvgPoolingImpl.cpp
index f116934cd61375d3498ecf4e9aeb54f1eea37d3f..d0299ab56eac7ae19cfef6cf8c4bf9757bca4ab1 100644
--- a/unit_tests/operator/Test_AvgPoolingImpl.cpp
+++ b/unit_tests/operator/Test_AvgPoolingImpl.cpp
@@ -201,4 +201,25 @@ TEST_CASE("[cpu/operator] AvgPooling(forward)", "[AvgPooling][CPU]") {
op2->getOutput(0)->print();
REQUIRE(*(op2->getOutput(0)) == *myOutput5);
}
+
+ SECTION("Simple test") {
+ std::shared_ptr<Tensor> tensor =
+ std::make_shared<Tensor>(Array4D<int32_t, 1, 1, 7, 7>{{{{
+ {0, 8, 26, 35, 49, 45, 22},
+ {2, 24, 48, 66, 60, 46, 26},
+ {8, 41, 64, 68, 39, 18, 9},
+ {10, 48, 72, 76, 42, 14, 9},
+ {6, 29, 52, 65, 27, 7, 3},
+ {1, 9, 24, 31, 18, 7, 1},
+ {0, 0, 4, 6, 7, 1, 1}}}}});
+
+ auto op = AvgPooling2D_Op({7, 7});
+ op.setDataType(DataType::Int32);
+ op.setBackend("cpu");
+
+ op.associateInput(0, tensor);
+ op.forwardDims();
+ op.forward();
+ REQUIRE(op.getOutput(0)->get<int32_t>(0) == 26);
+ }
}
\ No newline at end of file
diff --git a/unit_tests/operator/Test_GlobalAveragePoolingImpl.cpp b/unit_tests/operator/Test_GlobalAveragePoolingImpl.cpp
index 8e8536accadcb874f74d4d962aae435bc1351d6e..0fd7d84b1801e0918da3f4333ea86a07fb5cc790 100644
--- a/unit_tests/operator/Test_GlobalAveragePoolingImpl.cpp
+++ b/unit_tests/operator/Test_GlobalAveragePoolingImpl.cpp
@@ -558,6 +558,27 @@ TEST_CASE("[cpu/operator] GlobalAveragePooling",
Log::info("Number of operations : {}\n", number_of_operation);
Log::info("Operation / µs = {}\n", number_of_operation / duration.count());
}
+
+ SECTION("Simple test") {
+ std::shared_ptr<Tensor> tensor =
+ std::make_shared<Tensor>(Array4D<int32_t, 1, 1, 7, 7>{{{{
+ {0, 8, 26, 35, 49, 45, 22},
+ {2, 24, 48, 66, 60, 46, 26},
+ {8, 41, 64, 68, 39, 18, 9},
+ {10, 48, 72, 76, 42, 14, 9},
+ {6, 29, 52, 65, 27, 7, 3},
+ {1, 9, 24, 31, 18, 7, 1},
+ {0, 0, 4, 6, 7, 1, 1}}}}});
+
+ auto op = GlobalAveragePooling_Op();
+ op.setDataType(DataType::Int32);
+ op.setBackend("cpu");
+
+ op.associateInput(0, tensor);
+ op.forwardDims();
+ op.forward();
+ REQUIRE(op.getOutput(0)->get<int32_t>(0) == 26);
+ }
}
}
} // namespace Aidge