WIP: Re-implement Linear in managed code.

src/Native/LibTorchSharp/THSConvolution.cpp

@@ -408,218 +408,6 @@ Tensor THSNN_FractionalMaxPool3d_forward_with_indices(const NNModule module, con
     return ResultTensor(std::get<0>(res));
 }
 
-NNModule THSNN_ZeroPad2d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ZeroPad2dOptions(padding);
-        res = create_module<torch::nn::ZeroPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ZeroPad2d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ZeroPad2dOptions({ padding_left, padding_right, padding_top, padding_bottom });
-    res = create_module<torch::nn::ZeroPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ZeroPad2d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ZeroPad2d>()->forward(*tensor));
-}
-
-NNModule THSNN_ConstantPad1d_ctor(const double value, const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ConstantPad1dOptions(padding, value);
-        res = create_module<torch::nn::ConstantPad1dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ConstantPad1d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ConstantPad1d>()->forward(*tensor));
-}
-
-NNModule THSNN_ConstantPad2d_ctor(const double value, const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ConstantPad2dOptions(padding, value);
-    res = create_module<torch::nn::ConstantPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ConstantPad2d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ConstantPad2d>()->forward(*tensor));
-}
-
-NNModule THSNN_ConstantPad3d_ctor(const double value, const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ConstantPad3dOptions(padding, value);
-    res = create_module<torch::nn::ConstantPad3dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ConstantPad3d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ConstantPad3d>()->forward(*tensor));
-}
-
-NNModule THSNN_ConstantPad1d_ctor_tuple(const double value, const int64_t padding_left, const int64_t padding_right, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ConstantPad1dOptions({ padding_left, padding_right }, value);
-    res = create_module<torch::nn::ConstantPad1dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ConstantPad2d_ctor_tuple(const double value, const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ConstantPad2dOptions({ padding_left, padding_right, padding_top, padding_bottom }, value);
-    res = create_module<torch::nn::ConstantPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ConstantPad3d_ctor_tuple(const double value, const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, const int64_t padding_front, const int64_t padding_back, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ConstantPad3dOptions({ padding_left, padding_right, padding_top, padding_bottom, padding_front, padding_back }, value);
-    res = create_module<torch::nn::ConstantPad3dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ReplicationPad1d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReplicationPad1dOptions(padding);
-    res = create_module<torch::nn::ReplicationPad1dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ReplicationPad1d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ReplicationPad1d>()->forward(*tensor));
-}
-
-NNModule THSNN_ReplicationPad2d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReplicationPad2dOptions(padding);
-    res = create_module<torch::nn::ReplicationPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ReplicationPad2d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ReplicationPad2d>()->forward(*tensor));
-}
-
-NNModule THSNN_ReplicationPad3d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReplicationPad3dOptions(padding);
-    res = create_module<torch::nn::ReplicationPad3dImpl>(opts, outAsAnyModule);
-    );
-}
-
-
-Tensor   THSNN_ReplicationPad3d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ReplicationPad3d>()->forward(*tensor));
-}
-
-NNModule THSNN_ReplicationPad1d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReplicationPad1dOptions({ padding_left, padding_right });
-    res = create_module<torch::nn::ReplicationPad1dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ReplicationPad2d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReplicationPad2dOptions({ padding_left, padding_right, padding_top, padding_bottom });
-    res = create_module<torch::nn::ReplicationPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ReplicationPad3d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, const int64_t padding_front, const int64_t padding_back, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReplicationPad3dOptions({ padding_left, padding_right, padding_top, padding_bottom, padding_front, padding_back });
-    res = create_module<torch::nn::ReplicationPad3dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ReflectionPad1d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReflectionPad1dOptions(padding);
-    res = create_module<torch::nn::ReflectionPad1dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ReflectionPad1d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ReflectionPad1d>()->forward(*tensor));
-}
-
-NNModule THSNN_ReflectionPad2d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReflectionPad2dOptions(padding);
-    res = create_module<torch::nn::ReflectionPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ReflectionPad2d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ReflectionPad2d>()->forward(*tensor));
-}
-
-NNModule THSNN_ReflectionPad3d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReflectionPad3dOptions(padding);
-    res = create_module<torch::nn::ReflectionPad3dImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor   THSNN_ReflectionPad3d_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::ReflectionPad3d>()->forward(*tensor));
-}
-
-NNModule THSNN_ReflectionPad1d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReflectionPad1dOptions({ padding_left, padding_right });
-    res = create_module<torch::nn::ReflectionPad1dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ReflectionPad2d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReflectionPad2dOptions({ padding_left, padding_right, padding_top, padding_bottom });
-    res = create_module<torch::nn::ReflectionPad2dImpl>(opts, outAsAnyModule);
-    );
-}
-
-NNModule THSNN_ReflectionPad3d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, const int64_t padding_front, const int64_t padding_back, NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::ReflectionPad3dOptions({ padding_left, padding_right, padding_top, padding_bottom, padding_front, padding_back });
-    res = create_module<torch::nn::ReflectionPad3dImpl>(opts, outAsAnyModule);
-    );
-}
-
-
 template<typename T>
 void ApplyPaddingMode(T& opts, const int64_t padding)
 {

src/Native/LibTorchSharp/THSNN.cpp

@@ -16,40 +16,6 @@ Tensor THSNN_Identity_forward(const NNModule module, const Tensor tensor)
     CATCH_TENSOR((*module)->as<torch::nn::Identity>()->forward(*tensor));
 }
 
-NNModule THSNN_Linear_ctor(const int64_t input_size, const int64_t output_size, const bool bias,
-    NNAnyModule* outAsAnyModule)
-{
-    CATCH_RETURN_NNModule(
-        auto opts = torch::nn::LinearOptions(input_size, output_size).bias(bias);
-        res = create_module<torch::nn::LinearImpl>(opts, outAsAnyModule);
-    );
-}
-
-Tensor THSNN_Linear_forward(const NNModule module, const Tensor tensor)
-{
-    CATCH_TENSOR((*module)->as<torch::nn::Linear>()->forward(*tensor));
-}
-
-Tensor THSNN_Linear_bias(const NNModule module)
-{
-    return get_bias<torch::nn::Linear>(module);
-}
-
-void THSNN_Linear_set_bias(const NNModule module, const Tensor bias)
-{
-    set_bias<torch::nn::Linear>(module, bias);
-}
-
-Tensor THSNN_Linear_weight(const NNModule module)
-{
-    return get_weight<torch::nn::Linear>(module);
-}
-
-void THSNN_Linear_set_weight(const NNModule module, const Tensor weight)
-{
-    set_weight<torch::nn::Linear>(module, weight);
-}
-
 Tensor THSNN_functional_linear(const Tensor input, const Tensor weights, const Tensor bias)
 {
     CATCH_TENSOR(bias == nullptr ?

src/Native/LibTorchSharp/THSNN.h

@@ -94,42 +94,6 @@ EXPORT_API(Tensor)   THSNN_LPPool1d_forward(const NNModule module, const Tensor
 EXPORT_API(NNModule) THSNN_LPPool2d_ctor(double norm_type, const int64_t* kernelSize, const int kernelSizeLength, const int64_t* stride, const int strideLength, bool ceil_mode, NNAnyModule* outAsAnyModule);
 EXPORT_API(Tensor)   THSNN_LPPool2d_forward(const NNModule module, const Tensor tensor);
 
-// Padding
-
-EXPORT_API(NNModule) THSNN_ZeroPad2d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ZeroPad2d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ZeroPad2d_forward(const NNModule module, const Tensor tensor);
-
-EXPORT_API(NNModule) THSNN_ConstantPad1d_ctor(const double value, const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ConstantPad1d_ctor_tuple(const double value, const int64_t padding_left, const int64_t padding_right, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ConstantPad1d_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(NNModule) THSNN_ConstantPad2d_ctor(const double value, const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ConstantPad2d_ctor_tuple(const double value, const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ConstantPad2d_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(NNModule) THSNN_ConstantPad3d_ctor(const double value, const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ConstantPad3d_ctor_tuple(const double value, const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, const int64_t padding_front, const int64_t padding_back, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ConstantPad3d_forward(const NNModule module, const Tensor tensor);
-
-EXPORT_API(NNModule) THSNN_ReplicationPad1d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ReplicationPad1d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ReplicationPad1d_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(NNModule) THSNN_ReplicationPad2d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ReplicationPad2d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ReplicationPad2d_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(NNModule) THSNN_ReplicationPad3d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ReplicationPad3d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, const int64_t padding_front, const int64_t padding_back, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ReplicationPad3d_forward(const NNModule module, const Tensor tensor);
-
-EXPORT_API(NNModule) THSNN_ReflectionPad1d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ReflectionPad1d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ReflectionPad1d_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(NNModule) THSNN_ReflectionPad2d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ReflectionPad2d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ReflectionPad2d_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(NNModule) THSNN_ReflectionPad3d_ctor(const int64_t padding, NNAnyModule* outAsAnyModule);
-EXPORT_API(NNModule) THSNN_ReflectionPad3d_ctor_tuple(const int64_t padding_left, const int64_t padding_right, const int64_t padding_top, const int64_t padding_bottom, const int64_t padding_front, const int64_t padding_back, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_ReflectionPad3d_forward(const NNModule module, const Tensor tensor);
-
 // Convolution
 
 EXPORT_API(NNModule) THSNN_Conv1d_ctor(const int64_t inputChannel, const int64_t outputChannel, const int64_t kernelSize, const int64_t stride, const int64_t padding, const int64_t dilation, const int64_t paddingMode, const int64_t groups, const bool bias, NNAnyModule* outAsAnyModule);
@@ -325,12 +289,6 @@ EXPORT_API(Tensor) THSNN_unfold(const Tensor input, const int64_t kernel1, const
 
 EXPORT_API(NNModule) THSNN_Identity_ctor(NNAnyModule* outAsAnyModule);
 EXPORT_API(Tensor)   THSNN_Identity_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(NNModule) THSNN_Linear_ctor(const int64_t input_size, const int64_t output_size, const bool with_bias, NNAnyModule* outAsAnyModule);
-EXPORT_API(Tensor)   THSNN_Linear_forward(const NNModule module, const Tensor tensor);
-EXPORT_API(Tensor)   THSNN_Linear_bias(const NNModule module);
-EXPORT_API(void)     THSNN_Linear_set_bias(const NNModule module, const Tensor tensor);
-EXPORT_API(Tensor)   THSNN_Linear_weight(const NNModule module);
-EXPORT_API(void)     THSNN_Linear_set_weight(const NNModule module, const Tensor tensor);
 
 EXPORT_API(Tensor) THSNN_functional_linear(const Tensor input, const Tensor weights, const Tensor bias);
 EXPORT_API(Tensor) THSNN_functional_bilinear(const Tensor input1, const Tensor input2, const Tensor weights, const Tensor bias);