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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38264 Test Plan: Imported from OSS Differential Revision: D21509277 Pulled By: glaringlee fbshipit-source-id: b0bc17d375a89b96b1bdacde5987b4f4baa9468e
41 lines
1.0 KiB
C++
41 lines
1.0 KiB
C++
#include <torch/extension.h>
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// test include_dirs in setuptools.setup with relative path
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#include <tmp.h>
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torch::Tensor sigmoid_add(torch::Tensor x, torch::Tensor y) {
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return x.sigmoid() + y.sigmoid();
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}
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struct MatrixMultiplier {
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MatrixMultiplier(int A, int B) {
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tensor_ =
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torch::ones({A, B}, torch::dtype(torch::kFloat64).requires_grad(true));
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}
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torch::Tensor forward(torch::Tensor weights) {
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return tensor_.mm(weights);
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}
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torch::Tensor get() const {
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return tensor_;
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}
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private:
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torch::Tensor tensor_;
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};
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bool function_taking_optional(c10::optional<torch::Tensor> tensor) {
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return tensor.has_value();
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}
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
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m.def("sigmoid_add", &sigmoid_add, "sigmoid(x) + sigmoid(y)");
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m.def(
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"function_taking_optional",
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&function_taking_optional,
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"function_taking_optional");
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py::class_<MatrixMultiplier>(m, "MatrixMultiplier")
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.def(py::init<int, int>())
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.def("forward", &MatrixMultiplier::forward)
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.def("get", &MatrixMultiplier::get);
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}
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