blob: 6ea1aa4671af9f01b4adb05b36953c9fb6d35472 [file] [log] [blame]
#pragma once
#include "ATen/ATen.h"
#include "torch/csrc/jit/ivalue.h"
namespace torch { namespace jit {
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);
}
// 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;
}
// 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) {
constexpr size_t N = sizeof...(args);
int result[N] = {
(stack.push_back(std::forward<Types>(args)), 0)...
};
(void) result;
}
// 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.push_back(IValue(std::move(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));
}
}}