Files
pytorch/test/cpp_extensions/extension.cpp
Peter Goldsborough 393ad6582d Use torch:: instead of at:: in all C++ APIs (#13523)
Summary:
In TorchScript and C++ extensions we currently advocate a mix of `torch::` and `at::` namespace usage. In the C++ frontend I had instead exported all symbols from `at::` and some from `c10::` into the `torch::` namespace. This is far, far easier for users to understand, and also avoid bugs around creating tensors vs. variables. The same should from now on be true for the TorchScript C++ API (for running and loading models) and all C++ extensions.

Note that since we're just talking about typedefs, this change does not break any existing code.

Once this lands I will update stuff in `pytorch/tutorials` too.

zdevito ezyang gchanan
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13523

Differential Revision: D12942787

Pulled By: goldsborough

fbshipit-source-id: 76058936bd8707b33d9e5bbc2d0705fc3d820763
2018-11-06 14:32:25 -08:00

38 lines
971 B
C++

#include <torch/extension.h>
torch::Tensor sigmoid_add(torch::Tensor x, torch::Tensor y) {
return x.sigmoid() + y.sigmoid();
}
struct MatrixMultiplier {
MatrixMultiplier(int A, int B) {
tensor_ =
torch::ones({A, B}, torch::dtype(torch::kFloat64).requires_grad(true));
}
torch::Tensor forward(torch::Tensor weights) {
return tensor_.mm(weights);
}
torch::Tensor get() const {
return tensor_;
}
private:
torch::Tensor tensor_;
};
bool function_taking_optional(c10::optional<torch::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);
}