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#include <vector>
#include <torch/csrc/jit/backends/backend.h>
#include <torch/csrc/jit/mobile/nnc/context.h>
namespace torch {
namespace jit {
namespace mobile {
namespace nnc {
class NNCBackend : public PyTorchBackendInterface {
public:
explicit NNCBackend() = default;
~NNCBackend() override = default;
bool is_available() override {
return true;
}
c10::impl::GenericDict compile(
c10::IValue processed,
c10::impl::GenericDict method_compile_spec) override {
cu_ = std::make_shared<CompilationUnit>(processed);
// Input method_compile_spec:
// Key: method name
// Value: compile spec for each method
// Output:
// Key: method name
// Value: a backend handle for each method
auto spec =
c10::impl::toTypedDict<std::string, at::IValue>(method_compile_spec);
auto handles = c10::Dict<std::string, std::string>();
for (const auto& it : spec) {
// The handle for each method is the key (method name) itself.
handles.insert(it.key(), it.key());
}
return c10::impl::toGenericDict(handles);
}
c10::impl::GenericList execute(
c10::IValue handle,
c10::impl::GenericList inputs) override {
const std::string& method_name = handle.toStringRef();
auto function_name = c10::QualifiedName(method_name);
return cu_->run(function_name, inputs);
}
private:
std::shared_ptr<CompilationUnit> cu_;
};
namespace {
// TODO(mvz): temporarily disable NNC backend in mobile builds.
// static const auto cls = torch::jit::backend<NNCBackend>("nnc");
} // namespace
} // namespace nnc
} // namespace mobile
} // namespace jit
} // namespace torch
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