pytorch/benchmarks/operator_benchmark/pt_extension/extension.cpp

#include <torch/extension.h>
#include <torch/script.h>

using torch::List;
using torch::Tensor;

Tensor consume(Tensor a) {
  return a;
}

List<Tensor> consume_list(List<Tensor> a) {
  return a;
}

// When JIT tracing is used on function with constant for loop,
// the for loop is optimized away because of dead code elimination.
// That caused an issue for our op benchmark which needs to run an op
// in a loop and report the execution time. This diff resolves that issue by
// registering this consume op with correct alias information which is DEFAULT.
TORCH_LIBRARY_FRAGMENT(operator_benchmark, m) {
  m.def("_consume", &consume);
  m.def("_consume.list", &consume_list);
}

PYBIND11_MODULE(benchmark_cpp_extension, m) {
  m.def("_consume", &consume, "consume");
  m.def("_consume_list", &consume_list, "consume_list");
}