blob: 9994e1729363cd938e9c5bbe6710f717d871af19 [file] [log] [blame]
#include <torch/torch.h>
at::Tensor sigmoid_add(at::Tensor x, at::Tensor y) {
return x.sigmoid() + y.sigmoid();
}
struct MatrixMultiplier {
MatrixMultiplier(int A, int B) {
tensor_ = at::ones(torch::CPU(at::kDouble), {A, B});
torch::set_requires_grad(tensor_, true);
}
at::Tensor forward(at::Tensor weights) {
return tensor_.mm(weights);
}
at::Tensor get() const {
return tensor_;
}
private:
at::Tensor tensor_;
};
bool function_taking_optional(at::optional<at::Tensor> tensor) {
return tensor.has_value();
}
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("sigmoid_add", &sigmoid_add, "sigmoid(x) + sigmoid(y)");
m.def(
"function_taking_optional",
&function_taking_optional,
"function_taking_optional");
py::class_<MatrixMultiplier>(m, "MatrixMultiplier")
.def(py::init<int, int>())
.def("forward", &MatrixMultiplier::forward)
.def("get", &MatrixMultiplier::get);
}