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Summary: We rename the model_runner to model_container_runner to prepare for adding tests of pure model without container. Test Plan: commit itself is a test. Reviewers: Subscribers: Tasks: Tags: Pull Request resolved: https://github.com/pytorch/pytorch/pull/111324 Approved by: https://github.com/desertfire, https://github.com/chenyang78
48 lines
1.5 KiB
C++
48 lines
1.5 KiB
C++
#include <stdexcept>
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#include <torch/csrc/inductor/aoti_model_container_runner.h>
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#ifdef USE_CUDA
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#include <torch/csrc/inductor/aoti_model_container_runner_cuda.h>
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#endif
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#include "aoti_custom_class.h"
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namespace torch::aot_inductor {
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static auto registerMyAOTIClass =
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torch::class_<MyAOTIClass>("aoti", "MyAOTIClass")
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.def(torch::init<std::string, std::string>())
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.def("forward", &MyAOTIClass::forward)
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.def_pickle(
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[](const c10::intrusive_ptr<MyAOTIClass>& self)
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-> std::vector<std::string> {
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std::vector<std::string> v;
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v.push_back(self->lib_path());
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v.push_back(self->device());
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return v;
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},
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[](std::vector<std::string> params) {
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return c10::make_intrusive<MyAOTIClass>(params[0], params[1]);
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});
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MyAOTIClass::MyAOTIClass(
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const std::string& model_path,
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const std::string& device)
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: lib_path_(model_path), device_(device) {
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if (device_ == "cuda") {
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runner_ = std::make_unique<torch::inductor::AOTIModelContainerRunnerCuda>(
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model_path.c_str());
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} else if (device_ == "cpu") {
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runner_ = std::make_unique<torch::inductor::AOTIModelContainerRunnerCpu>(
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model_path.c_str());
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} else {
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throw std::runtime_error("invalid device: " + device);
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}
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}
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std::vector<torch::Tensor> MyAOTIClass::forward(
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std::vector<torch::Tensor> inputs) {
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return runner_->run(inputs);
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}
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} // namespace torch::aot_inductor
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