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stack.h
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stack.h
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#pragma once
#include <ATen/core/ivalue.h>
// TODO move this to c10 namespace
namespace torch {
namespace jit {
using c10::IValue;
using Stack = std::vector<IValue>;
using Operation = std::function<int(Stack&)>;
// An operation with N inputs and M outputs pops the last N inputs off
// the stack and pushes its M inputs onto the stack
// before: <other stack items> I0, I1, ... IN <- stack.back()
// after: <other stack items> O0, O1, ... OM
// operations are defined this way so that ownership of inputs can be
// transferred to the operation and it can incrementally drop ownership of
// tensors when they become unneeded. For large operations, like 'run an entire
// subgraph', this functionality is very important for minimizing gpu memory
// usage return value is the relative 'offset' to jump to for the next
// operation:
// pc += 1 + offset
// so a return value of 0 goes to the next instruction
// treat the last N elements of the stack as a list, looking up
// element i
static inline IValue& peek(Stack& stack, size_t i, size_t N) {
return *(stack.end() - N + i);
}
static inline const IValue& peek(const Stack& stack, size_t i, size_t N) {
return *(stack.end() - N + i);
}
// treat the last N elements of the stack as a list, looking up the
// slice starting at index i and having length len
static inline at::ArrayRef<IValue> peekSlice(
const Stack& stack,
size_t i,
size_t len,
size_t N) {
return at::ArrayRef<IValue>(stack).slice(stack.size() - N + i, len);
}
static inline at::ArrayRef<IValue> last(const Stack& stack, size_t N) {
return peekSlice(stack, 0, N, N);
}
static inline void drop(Stack& stack, size_t n) {
stack.erase(stack.end() - n, stack.end());
}
static inline IValue pop(Stack& stack) {
auto r = std::move(stack.back());
stack.pop_back();
return r;
}
static inline std::vector<IValue> pop(Stack& stack, size_t n) {
std::vector<IValue> result;
result.reserve(n);
for (size_t i = 0; i < n; ++i) {
result.push_back(std::move(peek(stack, i, n)));
}
drop(stack, n);
return result;
}
// variadic pop:
// int64_t a; at::Tensor b;
// pop(stack, a, b);
// equivalent to:
// b = pop(stack).toTensor();
// a = pop(stack).toInt();
template <typename... Types>
static inline void pop(Stack& stack, Types&... args) {
size_t i = 0;
constexpr size_t N = sizeof...(args);
int result[N] = {
(args = std::move(peek(stack, i++, N)).template to<Types>(), 0)...};
(void)result;
drop(stack, N);
}
template <typename... Types>
static inline void push(Stack& stack, Types&&... args) {
(void)std::initializer_list<int>{(stack.emplace_back(std::forward<Types>(args)), 0)...};
}
template <class T>
static inline void push_list_elements(Stack& stack, const c10::List<T>& elements) {
stack.reserve(stack.size() + elements.size());
for (T elem : elements) {
stack.push_back(std::move(elem));
}
}
// The packer here is carefully written not to make any unnecessary
// copies.
// pack takes the return values of aten functions pushes them onto the stack
template <typename T>
inline void pack(Stack& stack, T&& v) {
stack.emplace_back(std::forward<T>(v));
}
template <std::size_t remaining, typename... Args>
struct TuplePacker {
// NB: *Not* a universal reference.
static void execute(Stack& stack, std::tuple<Args...>&& t) {
// NB: The move here does not "destroy" the entire tuple, that is
// not what std::move does; only the particular tuple index
// processed here gets stolen.
pack(stack, std::get<sizeof...(Args) - remaining>(std::move(t)));
TuplePacker<remaining - 1, Args...>::execute(stack, std::move(t));
}
};
template <typename... Args>
struct TuplePacker<0, Args...> {
static void execute(Stack& stack, std::tuple<Args...>&& t){};
};
template <typename... Args>
inline void pack(Stack& stack, std::tuple<Args...>&& t) {
TuplePacker<sizeof...(Args), Args...>::execute(stack, std::move(t));
}
} // namespace jit
} // namespace torch