diff --git a/include/aidge/data/Tensor.hpp b/include/aidge/data/Tensor.hpp
index 903ce2f10c3f8c362aeb2ec1d331a49d3b2d9e7f..7195f0b204c78a389541eb21409377a1eab3d24f 100644
--- a/include/aidge/data/Tensor.hpp
+++ b/include/aidge/data/Tensor.hpp
@@ -377,11 +377,8 @@ class Tensor : public Data,
*/
void setDataType(const DataType dt) {
if (mImpl && (dataType() != dt)) {
- // get ptr before changing Tensor backend or the type difference will trigger a warning
- const void *data = mImpl->rawPtr();
- mDataType = dt;
std::unique_ptr<TensorImpl> newImpl = Registrar<Tensor>::create({mImpl->backend(), dt})(*this);
- newImpl->copy(data, size()); // /!\ it does not cast data but reinterpret them
+ newImpl->copyCast(mImpl->rawPtr(), size(), mDataType);
mImpl = std::move(newImpl);
}
mDataType = dt;
@@ -487,7 +484,7 @@ class Tensor : public Data,
- std::string toString() {
+ std::string toString() const {
if (dims().empty()) { return "{}"; }
std::string res;
std::size_t dim = 0;
@@ -580,7 +577,7 @@ class Tensor : public Data,
return res;
}
- inline void print() { printf("%s\n", toString().c_str()); }
+ inline void print() const { printf("%s\n", toString().c_str()); }
std::shared_ptr<Tensor> grad() {
if (!mGrad) {
diff --git a/include/aidge/operator/ConvDepthWise.hpp b/include/aidge/operator/ConvDepthWise.hpp
index c374c7f71c8d1d7b2fd3fba289670bff7dd632c8..e03524643763e4e03edf91a51f6e41aafe2fe972 100644
--- a/include/aidge/operator/ConvDepthWise.hpp
+++ b/include/aidge/operator/ConvDepthWise.hpp
@@ -169,11 +169,19 @@ public:
mImpl = Registrar<ConvDepthWise_Op<DIM>>::create(name)(*this);
mOutputs[0]->setBackend(name, device);
- // FIXME: temporary workaround
+ // By default, automatically set backend for weight and bias inputs
getInput(1)->setBackend(name, device);
getInput(2)->setBackend(name, device);
}
+ void setDataType(const DataType& dt) const override {
+ mOutputs[0]->setDataType(dt);
+
+ // By default, automatically set data type for weight and bias inputs
+ getInput(1)->setDataType(dt);
+ getInput(2)->setDataType(dt);
+ }
+
static const std::vector<std::string> getInputsName(){
return {"data_input", "weight", "bias"};
}
diff --git a/include/aidge/operator/Convert.hpp b/include/aidge/operator/Convert.hpp
index 6a08fbf0d0f222681b7578afabf3195a8ff860a0..cb54ffbf7487396c0fd9477265f9274f150aa39e 100644
--- a/include/aidge/operator/Convert.hpp
+++ b/include/aidge/operator/Convert.hpp
@@ -57,10 +57,6 @@ public:
mOutputs[0]->setBackend(name, device);
}
- void setDataType(const DataType& dataType) const override {
- mOutputs[0]->setDataType(dataType);
- }
-
void forward() override;
static const std::vector<std::string> getInputsName(){
diff --git a/include/aidge/operator/FC.hpp b/include/aidge/operator/FC.hpp
index beb5f82f57dfdd4ace6ddd24bc8af7f3871c7f5f..2e7b3a22f333c103e1ebda632ff798cbd47e5b46 100644
--- a/include/aidge/operator/FC.hpp
+++ b/include/aidge/operator/FC.hpp
@@ -99,12 +99,19 @@ public:
mImpl = Registrar<FC_Op>::create(name)(*this);
mOutputs[0]->setBackend(name, device);
- // FIXME: temporary workaround
- getInput(0)->setBackend(name, device);
+ // By default, automatically set backend for weight and bias inputs
getInput(1)->setBackend(name, device);
getInput(2)->setBackend(name, device);
}
+ void setDataType(const DataType& dt) const override {
+ mOutputs[0]->setDataType(dt);
+
+ // By default, automatically set data type for weight and bias inputs
+ getInput(1)->setDataType(dt);
+ getInput(2)->setDataType(dt);
+ }
+
static const std::vector<std::string> getInputsName(){
return {"data_input", "weight", "bias"};
}
diff --git a/include/aidge/utils/TensorUtils.hpp b/include/aidge/utils/TensorUtils.hpp
index 6387619546c66922e48cf95a8a56487d4b0d0641..cb10f2f8d036c3d794a124d10507fa22c8253d90 100644
--- a/include/aidge/utils/TensorUtils.hpp
+++ b/include/aidge/utils/TensorUtils.hpp
@@ -31,10 +31,10 @@
* @param absolute absolute error allowed (shoulmd be positive)
* @return true if both tensor are approximately equal and have the datatype, shape. Else return false
*/
-template <typename T>
+template <typename T1, typename T2 = T1>
bool approxEq(Aidge::Tensor t1, Aidge::Tensor t2, float relative, float absolute){
- assert(t1.dataType() == t2.dataType());
- assert(t1.dataType() == NativeType<T>::type);
+ assert(t1.dataType() == NativeType<T1>::type);
+ assert(t2.dataType() == NativeType<T2>::type);
assert(relative >= 0);
assert(absolute >= 0 && absolute<=1);
@@ -42,7 +42,7 @@ bool approxEq(Aidge::Tensor t1, Aidge::Tensor t2, float relative, float absolute
return false;
}
for(size_t i; i < t1.size(); ++i){
- if (static_cast<float>(std::abs(t1.get<T>(i) - t2.get<T>(i))) > (absolute + (relative * static_cast<float>(std::abs(t2.get<T>(i)))))){
+ if (static_cast<float>(std::abs(t1.get<T1>(i) - t2.get<T2>(i))) > (absolute + (relative * static_cast<float>(std::abs(t2.get<T2>(i)))))){
return false;
}
}
diff --git a/src/backend/TensorImpl.cpp b/src/backend/TensorImpl.cpp
index 371d775d7db379db62e3cb18876b44667fc0b9f6..282f1222e8e944ab5afc2e5545e67be3b3b0f331 100644
--- a/src/backend/TensorImpl.cpp
+++ b/src/backend/TensorImpl.cpp
@@ -15,6 +15,10 @@
#include "aidge/utils/ErrorHandling.hpp"
void Aidge::TensorImpl::copyFrom(const TensorImpl& srcImpl, NbElts_t length) {
+ if (srcImpl == *this) {
+ return;
+ }
+
if (srcImpl.device() != device()) {
if (srcImpl.backend() == backend()) {
// Same backend, but different device
diff --git a/src/data/Tensor.cpp b/src/data/Tensor.cpp
index a4690ea4284fb4759d76b62ed25c447c8f50370c..1f8257a706607d626ecec33a094352842445a4c0 100644
--- a/src/data/Tensor.cpp
+++ b/src/data/Tensor.cpp
@@ -42,7 +42,7 @@ const Aidge::Tensor& Aidge::Tensor::refCast(std::shared_ptr<Tensor>& fallback, c
const auto device = getImpl()->device();
fallback->setBackend(device.first, device.second);
fallback->resize(dims());
- fallback->getImpl()->copyCast(getImpl()->rawPtr(), size(), dt);
+ fallback->getImpl()->copyCast(getImpl()->rawPtr(), size(), dataType());
return *fallback;
}
}