diff --git a/.gitlab/ci/test.gitlab-ci.yml b/.gitlab/ci/test.gitlab-ci.yml
index 1e67ce273abc7d6b02f9e3148264ff3f9ea1cf07..924fd995aff34016cd4fa792a550d3d06db0449c 100644
--- a/.gitlab/ci/test.gitlab-ci.yml
+++ b/.gitlab/ci/test.gitlab-ci.yml
@@ -37,6 +37,7 @@ test:windows_cpp:
- Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
# Install dependencies
- choco install cmake.install --installargs '"ADD_CMAKE_TO_PATH=System"' -Y
+ - choco install python -Y
# Update PATH
- $env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
script:
diff --git a/include/aidge/operator/Add.hpp b/include/aidge/operator/Add.hpp
index c96b2c571f412124ccdfb83dde685e111448a222..ff3d1888c3bc70b61a3d4da42908d40de2d1d73e 100644
--- a/include/aidge/operator/Add.hpp
+++ b/include/aidge/operator/Add.hpp
@@ -141,7 +141,7 @@ public:
};
template <std::size_t NUM>
-inline std::shared_ptr<Node> Add(const char* name = nullptr) {
+inline std::shared_ptr<Node> Add(const std::string& name = "") {
return std::make_shared<Node>(std::make_shared<Add_Op<NUM>>(), name);
}
}
diff --git a/include/aidge/operator/FC.hpp b/include/aidge/operator/FC.hpp
index 6e4c54a030c108c29c08a8f5dfdc24d084ccc91c..db92dc9c735416d250fa32e2f9010b21b8f808c0 100644
--- a/include/aidge/operator/FC.hpp
+++ b/include/aidge/operator/FC.hpp
@@ -139,7 +139,7 @@ public:
inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
};
-inline std::shared_ptr<Node> FC(DimSize_t out_channels, bool noBias = false, const char* name = nullptr) {
+inline std::shared_ptr<Node> FC(DimSize_t out_channels, bool noBias = false, const std::string& name = "") {
// FIXME: properly handle default w&b initialization in every cases
auto fc = std::make_shared<Node>(std::make_shared<FC_Op>(out_channels, noBias), name);
addProducer(fc, 1, {out_channels, 1}, "w");
diff --git a/include/aidge/operator/LeakyReLU.hpp b/include/aidge/operator/LeakyReLU.hpp
index 64587d51de784082da455eb64aa5bbe175773b5d..1dff2550a42245351afab5b8bb1a708a8d0d8c0b 100644
--- a/include/aidge/operator/LeakyReLU.hpp
+++ b/include/aidge/operator/LeakyReLU.hpp
@@ -117,7 +117,7 @@ public:
inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
};
-inline std::shared_ptr<Node> LeakyReLU(float negativeSlope = 0.0f, const char* name = nullptr) {
+inline std::shared_ptr<Node> LeakyReLU(float negativeSlope = 0.0f, const std::string& name = "") {
// FIXME: properly handle default w&b initialization in every cases
return std::make_shared<Node>(std::make_shared<LeakyReLU_Op>(negativeSlope), name);
}
diff --git a/include/aidge/operator/Matmul.hpp b/include/aidge/operator/Matmul.hpp
index b44e8a9b9540e287ff35af1c9642c8202fd096d0..639b366912060b3e085510f312d94568e6b65f03 100644
--- a/include/aidge/operator/Matmul.hpp
+++ b/include/aidge/operator/Matmul.hpp
@@ -129,7 +129,7 @@ public:
inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
};
-inline std::shared_ptr<Node> Matmul(DimSize_t out_channels, const char* name = nullptr) {
+inline std::shared_ptr<Node> Matmul(DimSize_t out_channels, const std::string& name = "") {
// FIXME: properly handle default w&b initialization in every cases
auto matmul = std::make_shared<Node>(std::make_shared<Matmul_Op>(out_channels), name);
addProducer(matmul, 1, {1, out_channels}, "w");
diff --git a/include/aidge/operator/Producer.hpp b/include/aidge/operator/Producer.hpp
index 1f77400ce8a8ef727ea9e0a7d12477c6519ea2df..2a2f8c05355bed4b10a5711deaefc96eac1c3571 100644
--- a/include/aidge/operator/Producer.hpp
+++ b/include/aidge/operator/Producer.hpp
@@ -128,17 +128,17 @@ inline std::shared_ptr<Node> Producer(const std::shared_ptr<Tensor> tensor, cons
}
template <std::array<DimSize_t, 1>::size_type DIM>
-void addProducer(std::shared_ptr<Node>& otherNode, const IOIndex_t inputIdx, const std::array<DimSize_t, DIM>& dims, const char* extension) {
+void addProducer(std::shared_ptr<Node>& otherNode, const IOIndex_t inputIdx, const std::array<DimSize_t, DIM>& dims, const std::string& extension) {
assert(inputIdx != gk_IODefaultIndex);
static_assert(DIM<=MaxDim,"Too many tensor dimensions required by addProducer, not supported");
- const char* prodName = otherNode->name().empty() ? nullptr : (otherNode->name() + std::string("_") + std::string(extension)).c_str();
+ const std::string prodName = (otherNode->name().empty()) ? "" : (otherNode->name() + std::string("_") + extension);
auto prod = Producer(dims, prodName);
prod->addChild(otherNode, 0, inputIdx);
otherNode->getOperator()->associateInput(inputIdx, prod->getOperator()->getRawOutput(0));
}
template <std::size_t DIM>
-void addProducer(std::shared_ptr<Node>& otherNode, const IOIndex_t inputIdx, DimSize_t const (&dims)[DIM], const char* extension) {
+void addProducer(std::shared_ptr<Node>& otherNode, const IOIndex_t inputIdx, DimSize_t const (&dims)[DIM], const std::string& extension) {
addProducer(otherNode, inputIdx, to_array(dims), extension);
}
} // namespace Aidge
diff --git a/include/aidge/operator/ReLU.hpp b/include/aidge/operator/ReLU.hpp
index 3ea90462cf2b083a1a61ae39be06471093ec9f9f..141bd3ae12c7875a90d2549a24e5c141f3ff6aba 100644
--- a/include/aidge/operator/ReLU.hpp
+++ b/include/aidge/operator/ReLU.hpp
@@ -106,7 +106,7 @@ public:
inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
};
-inline std::shared_ptr<Node> ReLU(const char* name = nullptr) {
+inline std::shared_ptr<Node> ReLU(const std::string& name = "") {
// FIXME: properly handle default w&b initialization in every cases
return std::make_shared<Node>(std::make_shared<ReLU_Op>(), name);
}
diff --git a/include/aidge/operator/Softmax.hpp b/include/aidge/operator/Softmax.hpp
index 93eb262f703ca7eb385641c77df7ae7e79c00b96..64e713b331bbbbf612ee5102ba0ea82fb108350e 100644
--- a/include/aidge/operator/Softmax.hpp
+++ b/include/aidge/operator/Softmax.hpp
@@ -106,7 +106,7 @@ public:
inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
};
-inline std::shared_ptr<Node> Softmax(const char* name = nullptr) {
+inline std::shared_ptr<Node> Softmax(const std::string& name = "") {
// FIXME: properly handle default w&b initialization in every cases
return std::make_shared<Node>(std::make_shared<Softmax_Op>(), name);
}
diff --git a/python_binding/operator/pybind_AvgPooling.cpp b/python_binding/operator/pybind_AvgPooling.cpp
index 66dadba7244a199bd4ca8a0dd814f20a8049a62f..ecbb743d33cc5750bc60aeed8e5207dcec0c23dc 100644
--- a/python_binding/operator/pybind_AvgPooling.cpp
+++ b/python_binding/operator/pybind_AvgPooling.cpp
@@ -37,10 +37,10 @@ template <DimIdx_t DIM> void declare_AvgPoolingOp(py::module &m) {
py::arg("stride_dims"),
py::arg("padding_dims"));
- m.def(("AvgPooling" + std::to_string(DIM) + "D").c_str(), [](std::vector<DimSize_t>& kernel_dims,
- const char* name,
- std::vector<DimSize_t> &stride_dims,
- std::vector<DimSize_t> &padding_dims) {
+ m.def(("AvgPooling" + std::to_string(DIM) + "D").c_str(), [](const std::vector<DimSize_t>& kernel_dims,
+ const std::string& name,
+ const std::vector<DimSize_t> &stride_dims,
+ const std::vector<DimSize_t> &padding_dims) {
// Lambda function wrapper because PyBind fails to convert const array.
// So we use a vector that we convert in this function to a const DimeSize_t [DIM] array.
if (kernel_dims.size() != DIM) {
@@ -69,7 +69,7 @@ template <DimIdx_t DIM> void declare_AvgPoolingOp(py::module &m) {
const DimSize_t (&padding_dims_array)[DIM<<1] = tmp_padding_dims_array;
return AvgPooling<DIM>(to_array(kernel_dims_array), name, to_array(stride_dims_array), to_array(padding_dims_array));
}, py::arg("kernel_dims"),
- py::arg("name") = nullptr,
+ py::arg("name") = "",
py::arg("stride_dims") = std::vector<DimSize_t>(DIM,1),
py::arg("padding_dims") = std::vector<DimSize_t>(DIM<<1,0));
diff --git a/python_binding/operator/pybind_Conv.cpp b/python_binding/operator/pybind_Conv.cpp
index 3cf5d818f9b6e3bdfaf9a2d0b74ec0480beb6967..7e366305f287e958ea7500695c1f3285908017b1 100644
--- a/python_binding/operator/pybind_Conv.cpp
+++ b/python_binding/operator/pybind_Conv.cpp
@@ -44,11 +44,11 @@ template <DimIdx_t DIM> void declare_ConvOp(py::module &m) {
m.def(("Conv" + std::to_string(DIM) + "D").c_str(), [](DimSize_t in_channels,
DimSize_t out_channels,
- std::vector<DimSize_t>& kernel_dims,
- const char* name,
- std::vector<DimSize_t> &stride_dims,
- std::vector<DimSize_t> &padding_dims,
- std::vector<DimSize_t> &dilation_dims) {
+ const std::vector<DimSize_t>& kernel_dims,
+ const std::string& name,
+ const std::vector<DimSize_t> &stride_dims,
+ const std::vector<DimSize_t> &padding_dims,
+ const std::vector<DimSize_t> &dilation_dims) {
// Lambda function wrapper because PyBind fails to convert const array.
// So we use a vector that we convert in this function to a const DimeSize_t [DIM] array.
if (kernel_dims.size() != DIM) {
@@ -87,7 +87,7 @@ template <DimIdx_t DIM> void declare_ConvOp(py::module &m) {
}, py::arg("in_channels"),
py::arg("out_channels"),
py::arg("kernel_dims"),
- py::arg("name") = nullptr,
+ py::arg("name") = "",
py::arg("stride_dims") = std::vector<DimSize_t>(DIM,1),
py::arg("padding_dims") = std::vector<DimSize_t>(DIM<<1,0),
py::arg("dilation_dims") = std::vector<DimSize_t>(DIM,1));
diff --git a/python_binding/operator/pybind_ConvDepthWise.cpp b/python_binding/operator/pybind_ConvDepthWise.cpp
index b64409bdbb5f094e85cb094017a6fb837893a2db..8a81e7ba184536cbd535db24519495400bce6fdb 100644
--- a/python_binding/operator/pybind_ConvDepthWise.cpp
+++ b/python_binding/operator/pybind_ConvDepthWise.cpp
@@ -39,11 +39,11 @@ template <DimIdx_t DIM> void declare_ConvDepthWiseOp(py::module &m) {
py::arg("padding_dims"),
py::arg("dilation_dims"));
- m.def(("ConvDepthWise" + std::to_string(DIM) + "D").c_str(), [](std::vector<DimSize_t>& kernel_dims,
- const char* name,
- std::vector<DimSize_t> &stride_dims,
- std::vector<DimSize_t> &padding_dims,
- std::vector<DimSize_t> &dilation_dims) {
+ m.def(("ConvDepthWise" + std::to_string(DIM) + "D").c_str(), [](const std::vector<DimSize_t>& kernel_dims,
+ const std::string& name,
+ const std::vector<DimSize_t> &stride_dims,
+ const std::vector<DimSize_t> &padding_dims,
+ const std::vector<DimSize_t> &dilation_dims) {
// Lambda function wrapper because PyBind fails to convert const array.
// So we use a vector that we convert in this function to a const DimeSize_t [DIM] array.
if (kernel_dims.size() != DIM) {
@@ -80,7 +80,7 @@ template <DimIdx_t DIM> void declare_ConvDepthWiseOp(py::module &m) {
const DimSize_t (&dilation_dims_array)[DIM] = tmp_dilation_dims_array;
return ConvDepthWise<DIM>(to_array(kernel_dims_array), name, to_array(stride_dims_array), to_array(padding_dims_array), to_array(dilation_dims_array));
}, py::arg("kernel_dims"),
- py::arg("name") = nullptr,
+ py::arg("name") = "",
py::arg("stride_dims") = std::vector<DimSize_t>(DIM,1),
py::arg("padding_dims") = std::vector<DimSize_t>(DIM<<1,0),
py::arg("dilation_dims") = std::vector<DimSize_t>(DIM,1));
diff --git a/python_binding/operator/pybind_Producer.cpp b/python_binding/operator/pybind_Producer.cpp
index 5757891a30c5b40dcfa5ff99b1f06e00376f475a..ea9880800059e8993996e67138f89419c165fc4f 100644
--- a/python_binding/operator/pybind_Producer.cpp
+++ b/python_binding/operator/pybind_Producer.cpp
@@ -25,7 +25,7 @@ namespace Aidge {
template <DimIdx_t DIM>
void declare_Producer(py::module &m) {
// m.def(("Producer_" + std::to_string(DIM)+"D").c_str(), py::overload_cast<shared_ptr<Node>&>(&Producer<DIM>), py::arg("dims"), py::arg("name"));
- m.def("Producer", static_cast<std::shared_ptr<Node>(*)(const std::array<DimSize_t, DIM>&, const char*)>(&Producer), py::arg("dims"), py::arg("name") = nullptr);
+ m.def("Producer", static_cast<std::shared_ptr<Node>(*)(const std::array<DimSize_t, DIM>&, const std::string&)>(&Producer), py::arg("dims"), py::arg("name") = "");
}
@@ -36,7 +36,7 @@ void init_Producer(py::module &m) {
"ProducerOp",
py::multiple_inheritance())
.def("dims", &Producer_Op::dims);
- m.def("Producer", static_cast<std::shared_ptr<Node>(*)(const std::shared_ptr<Tensor>, const char*)>(&Producer), py::arg("tensor"), py::arg("name") = nullptr);
+ m.def("Producer", static_cast<std::shared_ptr<Node>(*)(const std::shared_ptr<Tensor>, const std::string&)>(&Producer), py::arg("tensor"), py::arg("name") = "");
declare_Producer<1>(m);
declare_Producer<2>(m);
diff --git a/src/scheduler/Scheduler.cpp b/src/scheduler/Scheduler.cpp
index fce46397ffd286a2ddbe254752b241578415e3d8..def7185f47f95aaddff95a975cc01e87bbcfb118 100644
--- a/src/scheduler/Scheduler.cpp
+++ b/src/scheduler/Scheduler.cpp
@@ -20,7 +20,7 @@
#include "aidge/graph/Node.hpp"
#include "aidge/utils/Types.h"
-void drawProgressBar(double progress, int barWidth, const char* additionalInfo = nullptr) {
+void drawProgressBar(double progress, int barWidth, const std::string& additionalInfo = "") {
putchar('[');
int pos = static_cast<int>(barWidth * progress);
for (int i = 0; i < barWidth; ++i) {
@@ -29,7 +29,7 @@ void drawProgressBar(double progress, int barWidth, const char* additionalInfo =
else
putchar(' ');
}
- printf("] %d%% | %s\r", static_cast<int>(progress * 100), (additionalInfo ? additionalInfo : ""));
+ printf("] %d%% | %s\r", static_cast<int>(progress * 100), additionalInfo);
fflush(stdout);
}
@@ -122,8 +122,7 @@ void Aidge::SequentialScheduler::forward(bool frowardDims, bool verbose) {
else
drawProgressBar(static_cast<float>(computationOver.size()) / static_cast<float>(computationNumber), 50,
(std::string("running ") + runnable->type() + "_" +
- std::to_string(reinterpret_cast<uintptr_t>(runnable.get())))
- .c_str());
+ std::to_string(reinterpret_cast<uintptr_t>(runnable.get()))));
const auto tStart = std::chrono::high_resolution_clock::now();
runnable->forward();
const auto tEnd = std::chrono::high_resolution_clock::now();