Complete implementation but runtime failing

CMakeLists.txt

@@ -9,5 +9,14 @@ find_package(Torch REQUIRED)
 
 set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")
 
+# Temporary patch while find_package(Torch) is not fixed
+file(
+        GLOB
+        LIBTORCH_PYTHON
+        "${TORCH_INSTALL_PREFIX}/lib/libtorch_python.so"
+        "${TORCH_INSTALL_PREFIX}/lib/libtorch_python.dylib"
+)
+message(STATUS "TORCH Libraries: ${LIBTORCH_PYTHON}")
+
 add_subdirectory(lib/Files)
 add_subdirectory(src)

README.md

@@ -2,5 +2,5 @@
 
 Python Wrapper to use Python classifiers from C++
 
-Explain issues with conda and libstdc++ and how to fix them
+Explain issues in Linux with conda and libstdc++ and how to fix them
 (moving conda libstdc++ to a different folder)

src/CMakeLists.txt

@@ -4,5 +4,5 @@ include_directories(${Python3_INCLUDE_DIRS})
 add_executable(main main.cc STree.cc SVC.cc PyClassifier.cc PyWrap.cc)
 add_executable(example example.cpp)
 
-target_link_libraries(main ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ArffFiles)
+target_link_libraries(main ${Python3_LIBRARIES} "${TORCH_LIBRARIES}" ${LIBTORCH_PYTHON} ArffFiles)
 target_link_libraries(example "${TORCH_LIBRARIES}" ArffFiles)

src/PyClassifier.cc

@@ -1,5 +1,7 @@
 #include "PyClassifier.h"
 #include <torch/csrc/autograd/python_variable.h>
+#include <torch/csrc/utils/tensor_numpy.h>
+#include <iostream>
 
 namespace pywrap {
 
@@ -13,7 +15,11 @@ namespace pywrap {
     {
         pyWrap->clean(module, className);
     }
-
+    PyObject* PyClassifier::toPyObject(torch::Tensor& tensor)
+    {
+        return torch::utils::tensor_to_numpy(tensor);
+        //return THPVariable_Wrap(tensor);
+    }
     std::string PyClassifier::version()
     {
         return pyWrap->version(module, className);
@@ -25,10 +31,35 @@ namespace pywrap {
     }
     PyClassifier& PyClassifier::fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states)
     {
-        PyObject* Xp = NULL;//THPVariable_Wrap(X);
+        std::cout << "Converting X to PyObject" << std::endl;
-        PyObject* yp = NULL;//THPVariable_Wrap(y);
+        std::cout << "X.defined() = " << X.defined() << std::endl;
+        //std::cout << "X.pyobj() = " << X.pyobj() << std::endl;
+        PyObject* Xp = toPyObject(X);
+        std::cout << "Converting y to PyObject" << std::endl;
+        PyObject* yp = toPyObject(y);
+        std::cout << "Calling fit" << std::endl;
         pyWrap->fit(module, className, Xp, yp);
+        Py_DECREF(Xp);
+        Py_DECREF(yp);
         return *this;
     }
+    torch::Tensor PyClassifier::predict(torch::Tensor& X)
+    {
+        PyObject* Xp = toPyObject(X);
+        auto PyResult = pyWrap->predict(module, className, Xp);
+        auto result = THPVariable_Unpack(PyResult);
+        Py_DECREF(Xp);
+        Py_DECREF(PyResult);
+        return result;
+    }
+    double PyClassifier::score(torch::Tensor& X, torch::Tensor& y)
+    {
+        PyObject* Xp = toPyObject(X);
+        PyObject* yp = toPyObject(y);
+        auto result = pyWrap->score(module, className, Xp, yp);
+        Py_DECREF(Xp);
+        Py_DECREF(yp);
+        return result;
+    }
 
 } /* namespace PyWrap */

src/PyClassifier.h

@@ -17,6 +17,7 @@ namespace pywrap {
         std::string version();
         std::string callMethodString(const std::string& method);
     private:
+        PyObject* toPyObject(torch::Tensor& tensor);
         PyWrap* pyWrap;
         std::string module;
         std::string className;

src/STree.h

@@ -7,8 +7,6 @@ namespace pywrap {
     public:
         STree() : PyClassifier("stree", "Stree") {};
         ~STree() = default;
-    private:
-
     };
 
 } /* namespace pywrap */

src/SVC.h

@@ -8,8 +8,6 @@ namespace pywrap {
         SVC() : PyClassifier("sklearn.svm", "SVC") {};
         ~SVC() = default;
         std::string version();
-    private:
-
     };
 
 } /* namespace pywrap */

src/main.cc

@@ -48,5 +48,10 @@ int main(int argc, char* argv[])
     auto svc = pywrap::SVC();
     svc.version();
     stree.version();
+    cout << string(80, '-') << endl;
+    cout << "X: " << X.sizes() << endl;
+    cout << "y: " << y.sizes() << endl;
+    auto result = svc.fit(X, y, features, className, states).score(X, y);
+    cout << "SVC score " << result << endl;
     return 0;
 }