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#pragma once
#include <c10/core/impl/PyInterpreter.h>
#include <c10/macros/Macros.h>
#include <c10/util/python_stub.h>
#include <atomic>
namespace c10 {
// A PyHandleCache represents a cached pointer from a C++ object to
// a Python object that represents that object analogously in Python.
// Upon a cache hit, the relevant object can be retrieved after a test
// and then a memory load. Two conditions must hold to be able to use this
// class:
//
// - This must truly be a cache; e.g., the caller must be able to produce
// the object some other way if the cache hit misses.
//
// - This must truly be a handle; e.g., the Python object referenced by
// this class must have static lifetime. This means we don't have to
// maintain strong ownership or deallocate the object when the C++ object
// dies. Static lifetime is a good idea in conjunction with the cache,
// since if you are producing a fresh object on miss you won't be
// maintaining object identity. If you need bidirectional ownership,
// you will want to factor out the pattern in TensorImpl with
// resurrection.
//
// This cache is expected to not improve perf under torchdeploy, as one
// interpreter will fill up the cache, and all the interpreters will be
// unable to use the slot. A potential improvement is to have multiple
// slots (one per interpreter), which will work in deployment scenarios
// where there a stable, fixed number of interpreters. You can also store
// the relevant state in the Python library, rather than in the non-Python
// library (although in many cases, this is not convenient, as there may
// not be a way to conveniently index based on the object.)
class PyHandleCache {
public:
PyHandleCache() : pyinterpreter_(nullptr), data_(nullptr) {}
// Attempt to fetch the pointer from the cache, if the PyInterpreter
// matches. If it doesn't exist, or the cache entry is not valid,
// use slow_accessor to get the real pointer value and return that
// (possibly writing it to the cache, if the cache entry is
// available.)
template <typename F>
PyObject* ptr_or(impl::PyInterpreter* self_interpreter, F slow_accessor)
const {
// Note [Memory ordering on Python interpreter tag]
impl::PyInterpreter* interpreter =
pyinterpreter_.load(std::memory_order_acquire);
if (C10_LIKELY(interpreter == self_interpreter)) {
return data_;
} else if (interpreter == nullptr) {
auto* r = slow_accessor();
impl::PyInterpreter* expected = nullptr;
// attempt to claim this cache entry with the specified interpreter tag
if (pyinterpreter_.compare_exchange_strong(
expected, self_interpreter, std::memory_order_acq_rel)) {
data_ = r;
}
// This shouldn't be possible, as you should be GIL protected
TORCH_INTERNAL_ASSERT(expected != self_interpreter);
return r;
} else {
return slow_accessor();
}
}
private:
mutable std::atomic<impl::PyInterpreter*> pyinterpreter_;
mutable PyObject* data_;
};
} // namespace c10
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