all tests now passing on windows debug

Author: dsyme

.editorconfig

@@ -63,8 +63,8 @@ dotnet_style_explicit_tuple_names = true:suggestion
 [*.cs]
 
 # spaces before parens
-csharp_space_between_method_declaration_name_and_open_parenthesis = true
-csharp_space_between_method_call_name_and_opening_parenthesis = true
+csharp_space_between_method_declaration_name_and_open_parenthesis = false
+csharp_space_between_method_call_name_and_opening_parenthesis = false
 csharp_space_after_keywords_in_control_flow_statements = true
 
 # Newline settings

src/Examples/AlexNet.cs

@@ -29,8 +29,8 @@ static void Main(string[] args)
 
             using (var train = Data.Loader.CIFAR10(_dataLocation, _trainBatchSize))
             using (var test = Data.Loader.CIFAR10(_dataLocation, _testBatchSize, false))
-            using (var model = new Model(_numClasses))
-            using (var optimizer = NN.Optimizer.Adam(model.Parameters(), 0.001))
+            using (var model = new Model("model", _numClasses))
+            using (var optimizer = NN.Optimizer.Adam(model.GetParameters(), 0.001))
             {
                 Stopwatch sw = new Stopwatch();
                 sw.Start();
@@ -53,7 +53,7 @@ private class Model : CustomModule
             private readonly AdaptiveAvgPool2D avgPool;
             private readonly Sequential classifier;
 
-            public Model(int numClasses) 
+            public Model(string name, int numClasses) : base(name)
             {
                 features = Sequential(
                     ("c1", Conv2D(3, 64, kernelSize: 3, stride: 2, padding: 1)),

src/Examples/MNIST.cs

@@ -25,8 +25,8 @@ static void Main(string[] args)
 
             using (var train = Data.Loader.MNIST(_dataLocation, _trainBatchSize))
             using (var test = Data.Loader.MNIST(_dataLocation, _testBatchSize, false))
-            using (var model = new Model())
-            using (var optimizer = NN.Optimizer.SGD(model.Parameters(), 0.01, 0.5))
+            using (var model = new Model("model"))
+            using (var optimizer = NN.Optimizer.SGD(model.GetParameters(), 0.01, 0.5))
             {
                 Stopwatch sw = new Stopwatch();
                 sw.Start();
@@ -50,7 +50,7 @@ private class Model : CustomModule
             private Linear fc1 = Linear(320, 50);
             private Linear fc2 = Linear(50, 10);
 
-            public Model()
+            public Model(string name) : base(name)
             {
                 RegisterModule("conv1", conv1);
                 RegisterModule("conv2", conv2);

src/Native/CMakeLists.txt

@@ -17,7 +17,7 @@ if(WIN32)
     add_compile_options($<$<CONFIG:Debug>:-DDEBUG>)
     add_compile_options($<$<CONFIG:Release>:-DNDEBUG>)
     add_compile_options($<$<CONFIG:Debug>:/Od>)
-    add_compile_options($<$<CONFIG:Debug>:/MTd>) # /MT will static link the VC runtime library, so it doesn't need to be installed on the target machine
+    add_compile_options($<$<CONFIG:Debug>:/MDd>) # /MT will static link the VC runtime library, so it doesn't need to be installed on the target machine
     add_compile_options($<$<CONFIG:Release>:/MT>)
     add_compile_options(/guard:cf)
     add_compile_options(/d2Zi+) # make optimized builds debugging easier

src/Native/LibTorchSharp/THSNN.cpp

@@ -17,18 +17,18 @@ EXPORT_API(int)         THSNN_Module_is_training(NNModule module);
 EXPORT_API(void)        THSNN_Module_train(NNModule module);
 EXPORT_API(void)        THSNN_Module_eval(NNModule module);
 EXPORT_API(long)        THSNN_Module_children_size(const NNModule module);
-EXPORT_API(const char*) THSNN_Module_child_name(const NNModule module, const int index);
+EXPORT_API(NNModule)    THSNN_Module_child(const NNModule module, const int index);
 EXPORT_API(const char*) THSNN_Module_name(const NNModule module);
 EXPORT_API(void)        THSNN_Module_zero_grad(const NNModule module);
 EXPORT_API(void)        THSNN_Module_save(const NNModule module, const char * location);
 EXPORT_API(NNModule)    THSNN_Module_load(const char * location, const char * name);
-EXPORT_API(NNModule)    THSNN_Module_register_module(const NNModule module, const char* name, const NNModule submodule);
+EXPORT_API(void)        THSNN_Module_register_module(const NNModule module, const char* name, const NNModule submodule);
 EXPORT_API(void)        THSNN_Module_dispose(const NNModule module);
 
 EXPORT_API(void)        THSNN_AnyModule_dispose(const NNAnyModule module);
 //EXPORT_API(NNModule)    THSNN_AnyModule_get(const NNAnyModule module);
 
-EXPORT_API(NNModule) THSNN_custom_module(const char** names, at::Tensor** parameters, const bool* require_grad, const int length, Tensor(*forward)(Tensor), NNAnyModule* outAsAnyModule);
+EXPORT_API(NNModule) THSNN_custom_module(const char* name, const char** names, at::Tensor** parameters, const bool* require_grad, const int length, Tensor(*forward)(Tensor), NNAnyModule* outAsAnyModule);
 EXPORT_API(NNModule) THSNN_AdaptiveAvgPool2d_ctor(const int64_t* sizes, const int length, NNAnyModule* outAsAnyModule);
 EXPORT_API(Tensor)   THSNN_AdaptiveAvgPool2d_forward(const NNModule module, const Tensor tensor);
 
@@ -57,19 +57,19 @@ EXPORT_API(void)     THSNN_Linear_set_weight(const NNModule module, const Tensor
 EXPORT_API(NNModule) THSNN_ReLU_ctor(bool inplace, NNAnyModule* outAsAnyModule);
 EXPORT_API(Tensor)   THSNN_ReLU_forward(const NNModule module, const Tensor tensor);
 
-EXPORT_API(NNSequential) THSNN_Sequential_ctor();
-EXPORT_API(void)     THSNN_Sequential_push_back(const NNSequential module, const char* name, const NNAnyModule submodule);
-EXPORT_API(Tensor)   THSNN_Sequential_forward(const NNSequential module, const Tensor tensor);
+EXPORT_API(NNModule) THSNN_Sequential_ctor();
+EXPORT_API(void)     THSNN_Sequential_push_back(const NNModule module, const char* name, const NNAnyModule submodule);
+EXPORT_API(Tensor)   THSNN_Sequential_forward(const NNModule module, const Tensor tensor);
 
 EXPORT_API(void) THSNN_Optimizer_zeroGrad(const Optimizer optimizer);
 EXPORT_API(void) THSNN_Optimizer_getParameters(const Optimizer optimizer, Tensor* (*allocator)(size_t length));
 EXPORT_API(void) THSNN_Optimizer_step(const Optimizer optimizer);
 EXPORT_API(void) THSNN_Optimizer_dispose(const Optimizer optimizer);
 
-EXPORT_API(Tensor) THSTorch_binary_cross_entropy(const Tensor inputwrapper, const Tensor targetwrapper, const Tensor weightwrapper, const int64_t reduction);
-EXPORT_API(Tensor) THSTorch_mse_loss(const Tensor inputwrapper, const Tensor targetwrapper, const int64_t reduction);
-EXPORT_API(Tensor) THSTorch_nll_loss(const Tensor inputwrapper, const Tensor targetwrapper, const Tensor weightwrapper, const int64_t reduction);
-EXPORT_API(Tensor) THSTorch_poisson_nll_loss(const Tensor input, const Tensor target, const bool logInput, const bool full, const double eps, const int64_t reduction);
+EXPORT_API(Tensor) THSNN_binary_cross_entropy(const Tensor inputwrapper, const Tensor targetwrapper, const Tensor weightwrapper, const int64_t reduction);
+EXPORT_API(Tensor) THSNN_mse_loss(const Tensor inputwrapper, const Tensor targetwrapper, const int64_t reduction);
+EXPORT_API(Tensor) THSNN_nll_loss(const Tensor inputwrapper, const Tensor targetwrapper, const Tensor weightwrapper, const int64_t reduction);
+EXPORT_API(Tensor) THSNN_poisson_loss(const Tensor input, const Tensor target, const bool logInput, const bool full, const double eps, const int64_t reduction);
 
 EXPORT_API(Optimizer) THSNN_Adam_ctor(const Tensor* parameters, const int len, const double learnig_rate);