#pragma once
#include <ATen/core/Tensor.h>
#include <ATen/core/Variadic.h>
#include <torch/csrc/autograd/variable.h>
#include <cstdint>
#include <tuple>
#include <type_traits>
#include <utility>
namespace torch {
using at::IterArgs;
struct CountTensors : IterArgs<CountTensors> {
size_t out = 0;
void operator()(const at::Tensor& x) {
out += 1;
}
void operator()(const c10::optional<at::Tensor>& x) {
out += x.has_value();
}
void operator()(at::ArrayRef<at::Tensor> xs) {
out += xs.size();
}
};
template <typename... Args>
size_t count_tensors(Args&&... args) {
return CountTensors().apply(std::forward<Args>(args)...).out;
}
struct CountVariables : IterArgs<CountVariables> {
size_t out = 0;
void operator()(const autograd::Variable& x) {
out += 1;
}
void operator()(at::ArrayRef<autograd::Variable> xs) {
out += xs.size();
}
};
template <typename... Args>
inline size_t count_variables(Args&&... args) {
return CountVariables().apply(std::forward<Args>(args)...).out;
}
//===----------------------------------------------------------------------===//
// std::index_sequence shim for C++11
//===----------------------------------------------------------------------===//
// A container of type-template parameter indices.
template <size_t... Is>
struct Indices {};
// Decrements the index N, adds N-1 to the list of indices and forwards
// whatever we already have.
template <size_t N, size_t... Is>
struct MakeIndices : MakeIndices<N - 1, N - 1, Is...> {};
// Partial specialization that forms our base case. When N is zero, we stop
// and define a typedef that will be visible to earlier classes due to
// inheritance. The typedef we define is an index list containing the numbers
// 0 through N-1.
template <size_t... Is>
struct MakeIndices<0, Is...> {
using indices = Indices<Is...>;
};
//===----------------------------------------------------------------------===//
// Utilities
//===----------------------------------------------------------------------===//
template <bool value, typename T = void>
using enable_if_t = typename std::enable_if<value, T>::type;
template <bool value, typename T = void>
using disable_if_t = enable_if_t<!value, T>;
template <typename T>
using decay_t = typename std::decay<T>::type;
namespace detail {
template <bool...>
struct pack;
} // namespace detail
template <bool... values>
struct all_of : std::is_same<
detail::pack<values..., true>,
detail::pack<true, values...>> {};
template <bool...>
struct any_of;
template <>
struct any_of<> : std::false_type {};
template <bool head, bool... tail>
struct any_of<head, tail...> {
static constexpr bool value = head || any_of<tail...>::value;
};
template <bool... values>
struct none_of {
static constexpr bool value = !any_of<values...>::value;
};
template <bool... values>
using enable_if_all_of_t = enable_if_t<all_of<values...>::value>;
template <typename T, typename... Ts>
using disable_if_contains_t =
enable_if_all_of_t<(!std::is_same<T, decay_t<Ts>>::value)...>;
template <typename Function, typename... Ts>
void apply(Function function, Ts&&... ts) {
// https://stackoverflow.com/questions/13978916/inserting-a-variadic-argument-list-into-a-vector
// Creates a dummy array, so that each function call is evaluated in order.
// `(function(), 0)` is because `function` should (!) return `void`, so
// according to the comma operator, it is evaluated and its result (`void`)
// is discarded. Then the zero is evaluated and used as an element in the
// array. The first zero ensures the array is not empty.
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays)
int _[]{0, (function(std::forward<Ts>(ts)), 0)...};
(void)_;
}
template <
typename ReturnType,
typename... Ts,
typename Function,
typename Accessor>
ReturnType unpack(Function function, Accessor accessor) {
return ReturnType(unpack<ReturnType, Ts...>(
std::move(function),
std::move(accessor),
typename MakeIndices<sizeof...(Ts)>::indices()));
}
template <
typename ReturnType,
typename... Ts,
typename Function,
typename Accessor,
size_t... Is>
ReturnType unpack(Function function, Accessor accessor, Indices<Is...>) {
return ReturnType(function(accessor.template operator()<Ts>(Is)...));
}
} // namespace torch