mirror of
https://github.com/pocketpy/pocketpy
synced 2025-10-26 14:30:17 +00:00
1904 lines
63 KiB
C++
1904 lines
63 KiB
C++
/***************************************************************************
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* Copyright (c) Johan Mabille, Sylvain Corlay and Wolf Vollprecht *
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* Copyright (c) QuantStack *
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* *
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* Distributed under the terms of the BSD 3-Clause License. *
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* *
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* The full license is in the file LICENSE, distributed with this software. *
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****************************************************************************/
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#ifndef XTENSOR_REDUCER_HPP
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#define XTENSOR_REDUCER_HPP
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#include <algorithm>
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#include <cstddef>
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#include <initializer_list>
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#include <iterator>
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#include <stdexcept>
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#include <tuple>
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#include <type_traits>
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#include <utility>
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#include <xtl/xfunctional.hpp>
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#include <xtl/xsequence.hpp>
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#include "xaccessible.hpp"
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#include "xbuilder.hpp"
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#include "xeval.hpp"
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#include "xexpression.hpp"
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#include "xgenerator.hpp"
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#include "xiterable.hpp"
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#include "xtensor_config.hpp"
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#include "xutils.hpp"
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namespace xt
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{
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template <template <class...> class A, class... AX, class X, XTL_REQUIRES(is_evaluation_strategy<AX>..., is_evaluation_strategy<X>)>
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auto operator|(const A<AX...>& args, const A<X>& rhs)
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{
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return std::tuple_cat(args, rhs);
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}
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struct keep_dims_type : xt::detail::option_base
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{
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};
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constexpr auto keep_dims = std::tuple<keep_dims_type>{};
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template <class T = double>
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struct xinitial : xt::detail::option_base
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{
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constexpr xinitial(T val)
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: m_val(val)
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{
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}
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constexpr T value() const
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{
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return m_val;
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}
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T m_val;
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};
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template <class T>
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constexpr auto initial(T val)
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{
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return std::make_tuple(xinitial<T>(val));
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}
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template <std::ptrdiff_t I, class T, class Tuple>
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struct tuple_idx_of_impl;
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template <std::ptrdiff_t I, class T>
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struct tuple_idx_of_impl<I, T, std::tuple<>>
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{
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static constexpr std::ptrdiff_t value = -1;
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};
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template <std::ptrdiff_t I, class T, class... Types>
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struct tuple_idx_of_impl<I, T, std::tuple<T, Types...>>
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{
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static constexpr std::ptrdiff_t value = I;
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};
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template <std::ptrdiff_t I, class T, class U, class... Types>
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struct tuple_idx_of_impl<I, T, std::tuple<U, Types...>>
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{
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static constexpr std::ptrdiff_t value = tuple_idx_of_impl<I + 1, T, std::tuple<Types...>>::value;
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};
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template <class S, class... X>
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struct decay_all;
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template <template <class...> class S, class... X>
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struct decay_all<S<X...>>
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{
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using type = S<std::decay_t<X>...>;
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};
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template <class T, class Tuple>
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struct tuple_idx_of
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{
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static constexpr std::ptrdiff_t
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value = tuple_idx_of_impl<0, std::decay_t<T>, typename decay_all<Tuple>::type>::value;
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};
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template <class R, class T>
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struct reducer_options
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{
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template <class X>
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struct initial_tester : std::false_type
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{
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};
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template <class X>
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struct initial_tester<xinitial<X>> : std::true_type
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{
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};
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// Workaround for Apple because tuple_cat is buggy!
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template <class X>
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struct initial_tester<const xinitial<X>> : std::true_type
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{
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};
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using d_t = std::decay_t<T>;
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static constexpr std::size_t initial_val_idx = xtl::mpl::find_if<initial_tester, d_t>::value;
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reducer_options() = default;
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reducer_options(const T& tpl)
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{
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xtl::mpl::static_if<initial_val_idx != std::tuple_size<T>::value>(
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[this, &tpl](auto no_compile)
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{
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// use no_compile to prevent compilation if initial_val_idx is out of bounds!
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this->initial_value = no_compile(
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std::get < initial_val_idx != std::tuple_size<T>::value
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? initial_val_idx
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: 0 > (tpl)
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)
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.value();
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},
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[](auto /*np_compile*/) {}
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);
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}
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using evaluation_strategy = std::conditional_t<
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tuple_idx_of<xt::evaluation_strategy::immediate_type, d_t>::value != -1,
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xt::evaluation_strategy::immediate_type,
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xt::evaluation_strategy::lazy_type>;
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using keep_dims = std::
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conditional_t<tuple_idx_of<xt::keep_dims_type, d_t>::value != -1, std::true_type, std::false_type>;
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static constexpr bool has_initial_value = initial_val_idx != std::tuple_size<d_t>::value;
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R initial_value;
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template <class NR>
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using rebind_t = reducer_options<NR, T>;
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template <class NR>
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auto rebind(NR initial, const reducer_options<R, T>&) const
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{
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reducer_options<NR, T> res;
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res.initial_value = initial;
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return res;
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}
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};
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template <class T>
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struct is_reducer_options_impl : std::false_type
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{
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};
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template <class... X>
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struct is_reducer_options_impl<std::tuple<X...>> : std::true_type
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{
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};
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template <class T>
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struct is_reducer_options : is_reducer_options_impl<std::decay_t<T>>
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{
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};
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/**********
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* reduce *
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**********/
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#define DEFAULT_STRATEGY_REDUCERS std::tuple<evaluation_strategy::lazy_type>
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template <class ST, class X, class KD = std::false_type>
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struct xreducer_shape_type;
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template <class S1, class S2>
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struct fixed_xreducer_shape_type;
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namespace detail
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{
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template <class O, class RS, class R, class E, class AX>
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inline void shape_computation(
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RS& result_shape,
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R& result,
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E& expr,
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const AX& axes,
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std::enable_if_t<!detail::is_fixed<RS>::value, int> = 0
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)
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{
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if (typename O::keep_dims())
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{
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resize_container(result_shape, expr.dimension());
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for (std::size_t i = 0; i < expr.dimension(); ++i)
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{
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if (std::find(axes.begin(), axes.end(), i) == axes.end())
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{
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// i not in axes!
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result_shape[i] = expr.shape()[i];
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}
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else
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{
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result_shape[i] = 1;
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}
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}
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}
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else
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{
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resize_container(result_shape, expr.dimension() - axes.size());
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for (std::size_t i = 0, idx = 0; i < expr.dimension(); ++i)
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{
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if (std::find(axes.begin(), axes.end(), i) == axes.end())
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{
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// i not in axes!
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result_shape[idx] = expr.shape()[i];
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++idx;
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}
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}
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}
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result.resize(result_shape, expr.layout());
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}
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// skip shape computation if already done at compile time
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template <class O, class RS, class R, class S, class AX>
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inline void
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shape_computation(RS&, R&, const S&, const AX&, std::enable_if_t<detail::is_fixed<RS>::value, int> = 0)
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{
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}
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}
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template <class F, class E, class R, XTL_REQUIRES(std::is_convertible<typename E::value_type, typename R::value_type>)>
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inline void copy_to_reduced(F&, const E& e, R& result)
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{
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if (e.layout() == layout_type::row_major)
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{
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std::copy(
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e.template cbegin<layout_type::row_major>(),
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e.template cend<layout_type::row_major>(),
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result.data()
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);
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}
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else
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{
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std::copy(
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e.template cbegin<layout_type::column_major>(),
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e.template cend<layout_type::column_major>(),
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result.data()
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);
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}
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}
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template <
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class F,
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class E,
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class R,
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XTL_REQUIRES(xtl::negation<std::is_convertible<typename E::value_type, typename R::value_type>>)>
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inline void copy_to_reduced(F& f, const E& e, R& result)
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{
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if (e.layout() == layout_type::row_major)
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{
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std::transform(
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e.template cbegin<layout_type::row_major>(),
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e.template cend<layout_type::row_major>(),
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result.data(),
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f
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);
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}
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else
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{
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std::transform(
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e.template cbegin<layout_type::column_major>(),
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e.template cend<layout_type::column_major>(),
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result.data(),
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f
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);
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}
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}
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template <class F, class E, class X, class O>
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inline auto reduce_immediate(F&& f, E&& e, X&& axes, O&& raw_options)
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{
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using reduce_functor_type = typename std::decay_t<F>::reduce_functor_type;
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using init_functor_type = typename std::decay_t<F>::init_functor_type;
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using expr_value_type = typename std::decay_t<E>::value_type;
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using result_type = std::decay_t<decltype(std::declval<reduce_functor_type>()(
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std::declval<init_functor_type>()(),
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std::declval<expr_value_type>()
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))>;
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using options_t = reducer_options<result_type, std::decay_t<O>>;
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options_t options(raw_options);
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using shape_type = typename xreducer_shape_type<
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typename std::decay_t<E>::shape_type,
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std::decay_t<X>,
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typename options_t::keep_dims>::type;
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using result_container_type = typename detail::xtype_for_shape<
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shape_type>::template type<result_type, std::decay_t<E>::static_layout>;
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result_container_type result;
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// retrieve functors from triple struct
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auto reduce_fct = xt::get<0>(f);
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auto init_fct = xt::get<1>(f);
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auto merge_fct = xt::get<2>(f);
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if (axes.size() == 0)
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{
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result.resize(e.shape(), e.layout());
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auto cpf = [&reduce_fct, &init_fct](const auto& v)
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{
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return reduce_fct(static_cast<result_type>(init_fct()), v);
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};
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copy_to_reduced(cpf, e, result);
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return result;
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}
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shape_type result_shape{};
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dynamic_shape<std::size_t>
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iter_shape = xtl::forward_sequence<dynamic_shape<std::size_t>, decltype(e.shape())>(e.shape());
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dynamic_shape<std::size_t> iter_strides(e.dimension());
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// std::less is used, because as the standard says (24.4.5):
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// A sequence is sorted with respect to a comparator comp if for any iterator i pointing to the
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// sequence and any non-negative integer n such that i + n is a valid iterator pointing to an element
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// of the sequence, comp(*(i + n), *i) == false. Therefore less is required to detect duplicates.
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if (!std::is_sorted(axes.cbegin(), axes.cend(), std::less<>()))
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{
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XTENSOR_THROW(std::runtime_error, "Reducing axes should be sorted.");
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}
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if (std::adjacent_find(axes.cbegin(), axes.cend()) != axes.cend())
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{
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XTENSOR_THROW(std::runtime_error, "Reducing axes should not contain duplicates.");
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}
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if (axes.size() != 0 && axes[axes.size() - 1] > e.dimension() - 1)
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{
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XTENSOR_THROW(
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std::runtime_error,
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"Axis " + std::to_string(axes[axes.size() - 1]) + " out of bounds for reduction."
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);
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}
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detail::shape_computation<options_t>(result_shape, result, e, axes);
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// Fast track for complete reduction
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if (e.dimension() == axes.size())
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{
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result_type tmp = options_t::has_initial_value ? options.initial_value : init_fct();
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result.data()[0] = std::accumulate(e.storage().begin(), e.storage().end(), tmp, reduce_fct);
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return result;
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}
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std::size_t leading_ax = axes[(e.layout() == layout_type::row_major) ? axes.size() - 1 : 0];
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auto strides_finder = e.strides().begin() + static_cast<std::ptrdiff_t>(leading_ax);
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// The computed strides contain "0" where the shape is 1 -- therefore find the next none-zero number
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std::size_t inner_stride = static_cast<std::size_t>(*strides_finder);
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auto iter_bound = e.layout() == layout_type::row_major ? e.strides().begin() : (e.strides().end() - 1);
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while (inner_stride == 0 && strides_finder != iter_bound)
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{
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(e.layout() == layout_type::row_major) ? --strides_finder : ++strides_finder;
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inner_stride = static_cast<std::size_t>(*strides_finder);
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}
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if (inner_stride == 0)
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{
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auto cpf = [&reduce_fct, &init_fct](const auto& v)
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{
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return reduce_fct(static_cast<result_type>(init_fct()), v);
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};
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copy_to_reduced(cpf, e, result);
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return result;
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}
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std::size_t inner_loop_size = static_cast<std::size_t>(inner_stride);
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std::size_t outer_loop_size = e.shape()[leading_ax];
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// The following code merges reduction axes "at the end" (or the beginning for col_major)
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// together by increasing the size of the outer loop where appropriate
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auto merge_loops = [&outer_loop_size, &e](auto it, auto end)
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{
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auto last_ax = *it;
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++it;
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for (; it != end; ++it)
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{
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// note that we check is_sorted, so this condition is valid
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if (std::abs(std::ptrdiff_t(*it) - std::ptrdiff_t(last_ax)) == 1)
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{
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last_ax = *it;
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outer_loop_size *= e.shape()[last_ax];
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}
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}
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return last_ax;
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};
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for (std::size_t i = 0, idx = 0; i < e.dimension(); ++i)
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{
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if (std::find(axes.begin(), axes.end(), i) == axes.end())
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{
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// i not in axes!
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iter_strides[i] = static_cast<std::size_t>(result.strides(
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)[typename options_t::keep_dims() ? i : idx]);
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++idx;
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}
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}
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if (e.layout() == layout_type::row_major)
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{
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std::size_t last_ax = merge_loops(axes.rbegin(), axes.rend());
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iter_shape.erase(iter_shape.begin() + std::ptrdiff_t(last_ax), iter_shape.end());
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iter_strides.erase(iter_strides.begin() + std::ptrdiff_t(last_ax), iter_strides.end());
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}
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else if (e.layout() == layout_type::column_major)
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{
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// we got column_major here
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std::size_t last_ax = merge_loops(axes.begin(), axes.end());
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// erasing the front vs the back
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iter_shape.erase(iter_shape.begin(), iter_shape.begin() + std::ptrdiff_t(last_ax + 1));
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iter_strides.erase(iter_strides.begin(), iter_strides.begin() + std::ptrdiff_t(last_ax + 1));
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// and reversing, to make it work with the same next_idx function
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std::reverse(iter_shape.begin(), iter_shape.end());
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std::reverse(iter_strides.begin(), iter_strides.end());
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}
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else
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{
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XTENSOR_THROW(std::runtime_error, "Layout not supported in immediate reduction.");
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}
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xindex temp_idx(iter_shape.size());
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auto next_idx = [&iter_shape, &iter_strides, &temp_idx]()
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{
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std::size_t i = iter_shape.size();
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for (; i > 0; --i)
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{
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if (std::ptrdiff_t(temp_idx[i - 1]) >= std::ptrdiff_t(iter_shape[i - 1]) - 1)
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{
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temp_idx[i - 1] = 0;
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}
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else
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{
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temp_idx[i - 1]++;
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break;
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}
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}
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return std::make_pair(
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i == 0,
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std::inner_product(temp_idx.begin(), temp_idx.end(), iter_strides.begin(), std::ptrdiff_t(0))
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);
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};
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auto begin = e.data();
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auto out = result.data();
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auto out_begin = result.data();
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std::ptrdiff_t next_stride = 0;
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std::pair<bool, std::ptrdiff_t> idx_res(false, 0);
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// Remark: eventually some modifications here to make conditions faster where merge + accumulate is
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// the same function (e.g. check std::is_same<decltype(merge_fct), decltype(reduce_fct)>::value) ...
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auto merge_border = out;
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bool merge = false;
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// TODO there could be some performance gain by removing merge checking
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// when axes.size() == 1 and even next_idx could be removed for something simpler (next_stride
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// always the same) best way to do this would be to create a function that takes (begin, out,
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// outer_loop_size, inner_loop_size, next_idx_lambda)
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// Decide if going about it row-wise or col-wise
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if (inner_stride == 1)
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{
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while (idx_res.first != true)
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{
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// for unknown reasons it's much faster to use a temporary variable and
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// std::accumulate here -- probably some cache behavior
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result_type tmp = init_fct();
|
|
tmp = std::accumulate(begin, begin + outer_loop_size, tmp, reduce_fct);
|
|
|
|
// use merge function if necessary
|
|
*out = merge ? merge_fct(*out, tmp) : tmp;
|
|
|
|
begin += outer_loop_size;
|
|
|
|
idx_res = next_idx();
|
|
next_stride = idx_res.second;
|
|
out = out_begin + next_stride;
|
|
|
|
if (out > merge_border)
|
|
{
|
|
// looped over once
|
|
merge = false;
|
|
merge_border = out;
|
|
}
|
|
else
|
|
{
|
|
merge = true;
|
|
}
|
|
};
|
|
}
|
|
else
|
|
{
|
|
while (idx_res.first != true)
|
|
{
|
|
std::transform(
|
|
out,
|
|
out + inner_loop_size,
|
|
begin,
|
|
out,
|
|
[merge, &init_fct, &reduce_fct](auto&& v1, auto&& v2)
|
|
{
|
|
return merge ? reduce_fct(v1, v2) :
|
|
// cast because return type of identity function is not upcasted
|
|
reduce_fct(static_cast<result_type>(init_fct()), v2);
|
|
}
|
|
);
|
|
|
|
begin += inner_stride;
|
|
for (std::size_t i = 1; i < outer_loop_size; ++i)
|
|
{
|
|
std::transform(out, out + inner_loop_size, begin, out, reduce_fct);
|
|
begin += inner_stride;
|
|
}
|
|
|
|
idx_res = next_idx();
|
|
next_stride = idx_res.second;
|
|
out = out_begin + next_stride;
|
|
|
|
if (out > merge_border)
|
|
{
|
|
// looped over once
|
|
merge = false;
|
|
merge_border = out;
|
|
}
|
|
else
|
|
{
|
|
merge = true;
|
|
}
|
|
};
|
|
}
|
|
if (options_t::has_initial_value)
|
|
{
|
|
std::transform(
|
|
result.data(),
|
|
result.data() + result.size(),
|
|
result.data(),
|
|
[&merge_fct, &options](auto&& v)
|
|
{
|
|
return merge_fct(v, options.initial_value);
|
|
}
|
|
);
|
|
}
|
|
return result;
|
|
}
|
|
|
|
/*********************
|
|
* xreducer functors *
|
|
*********************/
|
|
|
|
template <class T>
|
|
struct const_value
|
|
{
|
|
using value_type = T;
|
|
|
|
constexpr const_value() = default;
|
|
|
|
constexpr const_value(T t)
|
|
: m_value(t)
|
|
{
|
|
}
|
|
|
|
constexpr T operator()() const
|
|
{
|
|
return m_value;
|
|
}
|
|
|
|
template <class NT>
|
|
using rebind_t = const_value<NT>;
|
|
|
|
template <class NT>
|
|
const_value<NT> rebind() const;
|
|
|
|
T m_value;
|
|
};
|
|
|
|
namespace detail
|
|
{
|
|
template <class T, bool B>
|
|
struct evaluated_value_type
|
|
{
|
|
using type = T;
|
|
};
|
|
|
|
template <class T>
|
|
struct evaluated_value_type<T, true>
|
|
{
|
|
using type = typename std::decay_t<decltype(xt::eval(std::declval<T>()))>;
|
|
};
|
|
|
|
template <class T, bool B>
|
|
using evaluated_value_type_t = typename evaluated_value_type<T, B>::type;
|
|
}
|
|
|
|
template <class REDUCE_FUNC, class INIT_FUNC = const_value<long int>, class MERGE_FUNC = REDUCE_FUNC>
|
|
struct xreducer_functors : public std::tuple<REDUCE_FUNC, INIT_FUNC, MERGE_FUNC>
|
|
{
|
|
using self_type = xreducer_functors<REDUCE_FUNC, INIT_FUNC, MERGE_FUNC>;
|
|
using base_type = std::tuple<REDUCE_FUNC, INIT_FUNC, MERGE_FUNC>;
|
|
using reduce_functor_type = REDUCE_FUNC;
|
|
using init_functor_type = INIT_FUNC;
|
|
using merge_functor_type = MERGE_FUNC;
|
|
using init_value_type = typename init_functor_type::value_type;
|
|
|
|
xreducer_functors()
|
|
: base_type()
|
|
{
|
|
}
|
|
|
|
template <class RF>
|
|
xreducer_functors(RF&& reduce_func)
|
|
: base_type(std::forward<RF>(reduce_func), INIT_FUNC(), reduce_func)
|
|
{
|
|
}
|
|
|
|
template <class RF, class IF>
|
|
xreducer_functors(RF&& reduce_func, IF&& init_func)
|
|
: base_type(std::forward<RF>(reduce_func), std::forward<IF>(init_func), reduce_func)
|
|
{
|
|
}
|
|
|
|
template <class RF, class IF, class MF>
|
|
xreducer_functors(RF&& reduce_func, IF&& init_func, MF&& merge_func)
|
|
: base_type(std::forward<RF>(reduce_func), std::forward<IF>(init_func), std::forward<MF>(merge_func))
|
|
{
|
|
}
|
|
|
|
reduce_functor_type get_reduce() const
|
|
{
|
|
return std::get<0>(upcast());
|
|
}
|
|
|
|
init_functor_type get_init() const
|
|
{
|
|
return std::get<1>(upcast());
|
|
}
|
|
|
|
merge_functor_type get_merge() const
|
|
{
|
|
return std::get<2>(upcast());
|
|
}
|
|
|
|
template <class NT>
|
|
using rebind_t = xreducer_functors<REDUCE_FUNC, const_value<NT>, MERGE_FUNC>;
|
|
|
|
template <class NT>
|
|
rebind_t<NT> rebind()
|
|
{
|
|
return make_xreducer_functor(get_reduce(), get_init().template rebind<NT>(), get_merge());
|
|
}
|
|
|
|
private:
|
|
|
|
// Workaround for clang-cl
|
|
const base_type& upcast() const
|
|
{
|
|
return static_cast<const base_type&>(*this);
|
|
}
|
|
};
|
|
|
|
template <class RF>
|
|
auto make_xreducer_functor(RF&& reduce_func)
|
|
{
|
|
using reducer_type = xreducer_functors<std::remove_reference_t<RF>>;
|
|
return reducer_type(std::forward<RF>(reduce_func));
|
|
}
|
|
|
|
template <class RF, class IF>
|
|
auto make_xreducer_functor(RF&& reduce_func, IF&& init_func)
|
|
{
|
|
using reducer_type = xreducer_functors<std::remove_reference_t<RF>, std::remove_reference_t<IF>>;
|
|
return reducer_type(std::forward<RF>(reduce_func), std::forward<IF>(init_func));
|
|
}
|
|
|
|
template <class RF, class IF, class MF>
|
|
auto make_xreducer_functor(RF&& reduce_func, IF&& init_func, MF&& merge_func)
|
|
{
|
|
using reducer_type = xreducer_functors<
|
|
std::remove_reference_t<RF>,
|
|
std::remove_reference_t<IF>,
|
|
std::remove_reference_t<MF>>;
|
|
return reducer_type(
|
|
std::forward<RF>(reduce_func),
|
|
std::forward<IF>(init_func),
|
|
std::forward<MF>(merge_func)
|
|
);
|
|
}
|
|
|
|
/**********************
|
|
* xreducer extension *
|
|
**********************/
|
|
|
|
namespace extension
|
|
{
|
|
template <class Tag, class F, class CT, class X, class O>
|
|
struct xreducer_base_impl;
|
|
|
|
template <class F, class CT, class X, class O>
|
|
struct xreducer_base_impl<xtensor_expression_tag, F, CT, X, O>
|
|
{
|
|
using type = xtensor_empty_base;
|
|
};
|
|
|
|
template <class F, class CT, class X, class O>
|
|
struct xreducer_base : xreducer_base_impl<xexpression_tag_t<CT>, F, CT, X, O>
|
|
{
|
|
};
|
|
|
|
template <class F, class CT, class X, class O>
|
|
using xreducer_base_t = typename xreducer_base<F, CT, X, O>::type;
|
|
}
|
|
|
|
/************
|
|
* xreducer *
|
|
************/
|
|
|
|
template <class F, class CT, class X, class O>
|
|
class xreducer;
|
|
|
|
template <class F, class CT, class X, class O>
|
|
class xreducer_stepper;
|
|
|
|
template <class F, class CT, class X, class O>
|
|
struct xiterable_inner_types<xreducer<F, CT, X, O>>
|
|
{
|
|
using xexpression_type = std::decay_t<CT>;
|
|
using inner_shape_type = typename xreducer_shape_type<
|
|
typename xexpression_type::shape_type,
|
|
std::decay_t<X>,
|
|
typename O::keep_dims>::type;
|
|
using const_stepper = xreducer_stepper<F, CT, X, O>;
|
|
using stepper = const_stepper;
|
|
};
|
|
|
|
template <class F, class CT, class X, class O>
|
|
struct xcontainer_inner_types<xreducer<F, CT, X, O>>
|
|
{
|
|
using xexpression_type = std::decay_t<CT>;
|
|
using reduce_functor_type = typename std::decay_t<F>::reduce_functor_type;
|
|
using init_functor_type = typename std::decay_t<F>::init_functor_type;
|
|
using merge_functor_type = typename std::decay_t<F>::merge_functor_type;
|
|
using substepper_type = typename xexpression_type::const_stepper;
|
|
using raw_value_type = std::decay_t<decltype(std::declval<reduce_functor_type>()(
|
|
std::declval<init_functor_type>()(),
|
|
*std::declval<substepper_type>()
|
|
))>;
|
|
using value_type = typename detail::evaluated_value_type_t<raw_value_type, is_xexpression<raw_value_type>::value>;
|
|
|
|
using reference = value_type;
|
|
using const_reference = value_type;
|
|
using size_type = typename xexpression_type::size_type;
|
|
};
|
|
|
|
template <class T>
|
|
struct select_dim_mapping_type
|
|
{
|
|
using type = T;
|
|
};
|
|
|
|
template <std::size_t... I>
|
|
struct select_dim_mapping_type<fixed_shape<I...>>
|
|
{
|
|
using type = std::array<std::size_t, sizeof...(I)>;
|
|
};
|
|
|
|
/**
|
|
* @class xreducer
|
|
* @brief Reducing function operating over specified axes.
|
|
*
|
|
* The xreducer class implements an \ref xexpression applying
|
|
* a reducing function to an \ref xexpression over the specified
|
|
* axes.
|
|
*
|
|
* @tparam F a tuple of functors (class \ref xreducer_functors or compatible)
|
|
* @tparam CT the closure type of the \ref xexpression to reduce
|
|
* @tparam X the list of axes
|
|
*
|
|
* The reducer's result_type is deduced from the result type of function
|
|
* <tt>F::reduce_functor_type</tt> when called with elements of the expression @tparam CT.
|
|
*
|
|
* @sa reduce
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
class xreducer : public xsharable_expression<xreducer<F, CT, X, O>>,
|
|
public xconst_iterable<xreducer<F, CT, X, O>>,
|
|
public xaccessible<xreducer<F, CT, X, O>>,
|
|
public extension::xreducer_base_t<F, CT, X, O>
|
|
{
|
|
public:
|
|
|
|
using self_type = xreducer<F, CT, X, O>;
|
|
using inner_types = xcontainer_inner_types<self_type>;
|
|
|
|
using reduce_functor_type = typename inner_types::reduce_functor_type;
|
|
using init_functor_type = typename inner_types::init_functor_type;
|
|
using merge_functor_type = typename inner_types::merge_functor_type;
|
|
using xreducer_functors_type = xreducer_functors<reduce_functor_type, init_functor_type, merge_functor_type>;
|
|
|
|
using xexpression_type = typename inner_types::xexpression_type;
|
|
using axes_type = X;
|
|
|
|
using extension_base = extension::xreducer_base_t<F, CT, X, O>;
|
|
using expression_tag = typename extension_base::expression_tag;
|
|
|
|
using substepper_type = typename inner_types::substepper_type;
|
|
using value_type = typename inner_types::value_type;
|
|
using reference = typename inner_types::reference;
|
|
using const_reference = typename inner_types::const_reference;
|
|
using pointer = value_type*;
|
|
using const_pointer = const value_type*;
|
|
|
|
using size_type = typename inner_types::size_type;
|
|
using difference_type = typename xexpression_type::difference_type;
|
|
|
|
using iterable_base = xconst_iterable<self_type>;
|
|
using inner_shape_type = typename iterable_base::inner_shape_type;
|
|
using shape_type = inner_shape_type;
|
|
|
|
using dim_mapping_type = typename select_dim_mapping_type<inner_shape_type>::type;
|
|
|
|
using stepper = typename iterable_base::stepper;
|
|
using const_stepper = typename iterable_base::const_stepper;
|
|
using bool_load_type = typename xexpression_type::bool_load_type;
|
|
|
|
static constexpr layout_type static_layout = layout_type::dynamic;
|
|
static constexpr bool contiguous_layout = false;
|
|
|
|
template <class Func, class CTA, class AX, class OX>
|
|
xreducer(Func&& func, CTA&& e, AX&& axes, OX&& options);
|
|
|
|
const inner_shape_type& shape() const noexcept;
|
|
layout_type layout() const noexcept;
|
|
bool is_contiguous() const noexcept;
|
|
|
|
template <class... Args>
|
|
const_reference operator()(Args... args) const;
|
|
template <class... Args>
|
|
const_reference unchecked(Args... args) const;
|
|
|
|
template <class It>
|
|
const_reference element(It first, It last) const;
|
|
|
|
const xexpression_type& expression() const noexcept;
|
|
|
|
template <class S>
|
|
bool broadcast_shape(S& shape, bool reuse_cache = false) const;
|
|
|
|
template <class S>
|
|
bool has_linear_assign(const S& strides) const noexcept;
|
|
|
|
template <class S>
|
|
const_stepper stepper_begin(const S& shape) const noexcept;
|
|
template <class S>
|
|
const_stepper stepper_end(const S& shape, layout_type) const noexcept;
|
|
|
|
template <class E, class Func = F, class Opts = O>
|
|
using rebind_t = xreducer<Func, E, X, Opts>;
|
|
|
|
template <class E>
|
|
rebind_t<E> build_reducer(E&& e) const;
|
|
|
|
template <class E, class Func, class Opts>
|
|
rebind_t<E, Func, Opts> build_reducer(E&& e, Func&& func, Opts&& opts) const;
|
|
|
|
xreducer_functors_type functors() const
|
|
{
|
|
return xreducer_functors_type(m_reduce, m_init, m_merge); // TODO: understand why
|
|
// make_xreducer_functor is throwing an
|
|
// error
|
|
}
|
|
|
|
const O& options() const
|
|
{
|
|
return m_options;
|
|
}
|
|
|
|
private:
|
|
|
|
CT m_e;
|
|
reduce_functor_type m_reduce;
|
|
init_functor_type m_init;
|
|
merge_functor_type m_merge;
|
|
axes_type m_axes;
|
|
inner_shape_type m_shape;
|
|
dim_mapping_type m_dim_mapping;
|
|
O m_options;
|
|
|
|
friend class xreducer_stepper<F, CT, X, O>;
|
|
};
|
|
|
|
/*************************
|
|
* reduce implementation *
|
|
*************************/
|
|
|
|
namespace detail
|
|
{
|
|
template <class F, class E, class X, class O>
|
|
inline auto reduce_impl(F&& f, E&& e, X&& axes, evaluation_strategy::lazy_type, O&& options)
|
|
{
|
|
decltype(auto) normalized_axes = normalize_axis(e, std::forward<X>(axes));
|
|
|
|
using reduce_functor_type = typename std::decay_t<F>::reduce_functor_type;
|
|
using init_functor_type = typename std::decay_t<F>::init_functor_type;
|
|
using value_type = std::decay_t<decltype(std::declval<reduce_functor_type>()(
|
|
std::declval<init_functor_type>()(),
|
|
*std::declval<typename std::decay_t<E>::const_stepper>()
|
|
))>;
|
|
using evaluated_value_type = evaluated_value_type_t<value_type, is_xexpression<value_type>::value>;
|
|
|
|
using reducer_type = xreducer<
|
|
F,
|
|
const_xclosure_t<E>,
|
|
xtl::const_closure_type_t<decltype(normalized_axes)>,
|
|
reducer_options<evaluated_value_type, std::decay_t<O>>>;
|
|
return reducer_type(
|
|
std::forward<F>(f),
|
|
std::forward<E>(e),
|
|
std::forward<decltype(normalized_axes)>(normalized_axes),
|
|
std::forward<O>(options)
|
|
);
|
|
}
|
|
|
|
template <class F, class E, class X, class O>
|
|
inline auto reduce_impl(F&& f, E&& e, X&& axes, evaluation_strategy::immediate_type, O&& options)
|
|
{
|
|
decltype(auto) normalized_axes = normalize_axis(e, std::forward<X>(axes));
|
|
return reduce_immediate(
|
|
std::forward<F>(f),
|
|
eval(std::forward<E>(e)),
|
|
std::forward<decltype(normalized_axes)>(normalized_axes),
|
|
std::forward<O>(options)
|
|
);
|
|
}
|
|
}
|
|
|
|
#define DEFAULT_STRATEGY_REDUCERS std::tuple<evaluation_strategy::lazy_type>
|
|
|
|
namespace detail
|
|
{
|
|
template <class T>
|
|
struct is_xreducer_functors_impl : std::false_type
|
|
{
|
|
};
|
|
|
|
template <class RF, class IF, class MF>
|
|
struct is_xreducer_functors_impl<xreducer_functors<RF, IF, MF>> : std::true_type
|
|
{
|
|
};
|
|
|
|
template <class T>
|
|
using is_xreducer_functors = is_xreducer_functors_impl<std::decay_t<T>>;
|
|
}
|
|
|
|
/**
|
|
* @brief Returns an \ref xexpression applying the specified reducing
|
|
* function to an expression over the given axes.
|
|
*
|
|
* @param f the reducing function to apply.
|
|
* @param e the \ref xexpression to reduce.
|
|
* @param axes the list of axes.
|
|
* @param options evaluation strategy to use (lazy (default), or immediate)
|
|
*
|
|
* The returned expression either hold a const reference to \p e or a copy
|
|
* depending on whether \p e is an lvalue or an rvalue.
|
|
*/
|
|
|
|
template <
|
|
class F,
|
|
class E,
|
|
class X,
|
|
class EVS = DEFAULT_STRATEGY_REDUCERS,
|
|
XTL_REQUIRES(xtl::negation<is_reducer_options<X>>, detail::is_xreducer_functors<F>)>
|
|
inline auto reduce(F&& f, E&& e, X&& axes, EVS&& options = EVS())
|
|
{
|
|
return detail::reduce_impl(
|
|
std::forward<F>(f),
|
|
std::forward<E>(e),
|
|
std::forward<X>(axes),
|
|
typename reducer_options<int, EVS>::evaluation_strategy{},
|
|
std::forward<EVS>(options)
|
|
);
|
|
}
|
|
|
|
template <
|
|
class F,
|
|
class E,
|
|
class X,
|
|
class EVS = DEFAULT_STRATEGY_REDUCERS,
|
|
XTL_REQUIRES(xtl::negation<is_reducer_options<X>>, xtl::negation<detail::is_xreducer_functors<F>>)>
|
|
inline auto reduce(F&& f, E&& e, X&& axes, EVS&& options = EVS())
|
|
{
|
|
return reduce(
|
|
make_xreducer_functor(std::forward<F>(f)),
|
|
std::forward<E>(e),
|
|
std::forward<X>(axes),
|
|
std::forward<EVS>(options)
|
|
);
|
|
}
|
|
|
|
template <
|
|
class F,
|
|
class E,
|
|
class EVS = DEFAULT_STRATEGY_REDUCERS,
|
|
XTL_REQUIRES(is_reducer_options<EVS>, detail::is_xreducer_functors<F>)>
|
|
inline auto reduce(F&& f, E&& e, EVS&& options = EVS())
|
|
{
|
|
xindex_type_t<typename std::decay_t<E>::shape_type> ar;
|
|
resize_container(ar, e.dimension());
|
|
std::iota(ar.begin(), ar.end(), 0);
|
|
return detail::reduce_impl(
|
|
std::forward<F>(f),
|
|
std::forward<E>(e),
|
|
std::move(ar),
|
|
typename reducer_options<int, std::decay_t<EVS>>::evaluation_strategy{},
|
|
std::forward<EVS>(options)
|
|
);
|
|
}
|
|
|
|
template <
|
|
class F,
|
|
class E,
|
|
class EVS = DEFAULT_STRATEGY_REDUCERS,
|
|
XTL_REQUIRES(is_reducer_options<EVS>, xtl::negation<detail::is_xreducer_functors<F>>)>
|
|
inline auto reduce(F&& f, E&& e, EVS&& options = EVS())
|
|
{
|
|
return reduce(make_xreducer_functor(std::forward<F>(f)), std::forward<E>(e), std::forward<EVS>(options));
|
|
}
|
|
|
|
template <
|
|
class F,
|
|
class E,
|
|
class I,
|
|
std::size_t N,
|
|
class EVS = DEFAULT_STRATEGY_REDUCERS,
|
|
XTL_REQUIRES(detail::is_xreducer_functors<F>)>
|
|
inline auto reduce(F&& f, E&& e, const I (&axes)[N], EVS options = EVS())
|
|
{
|
|
using axes_type = std::array<std::size_t, N>;
|
|
auto ax = xt::forward_normalize<axes_type>(e, axes);
|
|
return detail::reduce_impl(
|
|
std::forward<F>(f),
|
|
std::forward<E>(e),
|
|
std::move(ax),
|
|
typename reducer_options<int, EVS>::evaluation_strategy{},
|
|
options
|
|
);
|
|
}
|
|
|
|
template <
|
|
class F,
|
|
class E,
|
|
class I,
|
|
std::size_t N,
|
|
class EVS = DEFAULT_STRATEGY_REDUCERS,
|
|
XTL_REQUIRES(xtl::negation<detail::is_xreducer_functors<F>>)>
|
|
inline auto reduce(F&& f, E&& e, const I (&axes)[N], EVS options = EVS())
|
|
{
|
|
return reduce(make_xreducer_functor(std::forward<F>(f)), std::forward<E>(e), axes, options);
|
|
}
|
|
|
|
/********************
|
|
* xreducer_stepper *
|
|
********************/
|
|
|
|
template <class F, class CT, class X, class O>
|
|
class xreducer_stepper
|
|
{
|
|
public:
|
|
|
|
using self_type = xreducer_stepper<F, CT, X, O>;
|
|
using xreducer_type = xreducer<F, CT, X, O>;
|
|
|
|
using value_type = typename xreducer_type::value_type;
|
|
using reference = typename xreducer_type::value_type;
|
|
using pointer = typename xreducer_type::const_pointer;
|
|
using size_type = typename xreducer_type::size_type;
|
|
using difference_type = typename xreducer_type::difference_type;
|
|
|
|
using xexpression_type = typename xreducer_type::xexpression_type;
|
|
using substepper_type = typename xexpression_type::const_stepper;
|
|
using shape_type = typename xreducer_type::shape_type;
|
|
|
|
xreducer_stepper(
|
|
const xreducer_type& red,
|
|
size_type offset,
|
|
bool end = false,
|
|
layout_type l = default_assignable_layout(xexpression_type::static_layout)
|
|
);
|
|
|
|
reference operator*() const;
|
|
|
|
void step(size_type dim);
|
|
void step_back(size_type dim);
|
|
void step(size_type dim, size_type n);
|
|
void step_back(size_type dim, size_type n);
|
|
void reset(size_type dim);
|
|
void reset_back(size_type dim);
|
|
|
|
void to_begin();
|
|
void to_end(layout_type l);
|
|
|
|
private:
|
|
|
|
reference initial_value() const;
|
|
reference aggregate(size_type dim) const;
|
|
reference aggregate_impl(size_type dim, /*keep_dims=*/std::false_type) const;
|
|
reference aggregate_impl(size_type dim, /*keep_dims=*/std::true_type) const;
|
|
|
|
substepper_type get_substepper_begin() const;
|
|
size_type get_dim(size_type dim) const noexcept;
|
|
size_type shape(size_type i) const noexcept;
|
|
size_type axis(size_type i) const noexcept;
|
|
|
|
const xreducer_type* m_reducer;
|
|
size_type m_offset;
|
|
mutable substepper_type m_stepper;
|
|
};
|
|
|
|
/******************
|
|
* xreducer utils *
|
|
******************/
|
|
|
|
namespace detail
|
|
{
|
|
template <std::size_t X, std::size_t... I>
|
|
struct in
|
|
{
|
|
static constexpr bool value = xtl::disjunction<std::integral_constant<bool, X == I>...>::value;
|
|
};
|
|
|
|
template <std::size_t Z, class S1, class S2, class R>
|
|
struct fixed_xreducer_shape_type_impl;
|
|
|
|
template <std::size_t Z, std::size_t... I, std::size_t... J, std::size_t... R>
|
|
struct fixed_xreducer_shape_type_impl<Z, fixed_shape<I...>, fixed_shape<J...>, fixed_shape<R...>>
|
|
{
|
|
using type = std::conditional_t<
|
|
in<Z, J...>::value,
|
|
typename fixed_xreducer_shape_type_impl<Z - 1, fixed_shape<I...>, fixed_shape<J...>, fixed_shape<R...>>::type,
|
|
typename fixed_xreducer_shape_type_impl<
|
|
Z - 1,
|
|
fixed_shape<I...>,
|
|
fixed_shape<J...>,
|
|
fixed_shape<detail::at<Z, I...>::value, R...>>::type>;
|
|
};
|
|
|
|
template <std::size_t... I, std::size_t... J, std::size_t... R>
|
|
struct fixed_xreducer_shape_type_impl<0, fixed_shape<I...>, fixed_shape<J...>, fixed_shape<R...>>
|
|
{
|
|
using type = std::
|
|
conditional_t<in<0, J...>::value, fixed_shape<R...>, fixed_shape<detail::at<0, I...>::value, R...>>;
|
|
};
|
|
|
|
/***************************
|
|
* helper for return types *
|
|
***************************/
|
|
|
|
template <class T>
|
|
struct xreducer_size_type
|
|
{
|
|
using type = std::size_t;
|
|
};
|
|
|
|
template <class T>
|
|
using xreducer_size_type_t = typename xreducer_size_type<T>::type;
|
|
|
|
template <class T>
|
|
struct xreducer_temporary_type
|
|
{
|
|
using type = T;
|
|
};
|
|
|
|
template <class T>
|
|
using xreducer_temporary_type_t = typename xreducer_temporary_type<T>::type;
|
|
|
|
/********************************
|
|
* Default const_value rebinder *
|
|
********************************/
|
|
|
|
template <class T, class U>
|
|
struct const_value_rebinder
|
|
{
|
|
static const_value<U> run(const const_value<T>& t)
|
|
{
|
|
return const_value<U>(t.m_value);
|
|
}
|
|
};
|
|
}
|
|
|
|
/*******************************************
|
|
* Init functor const_value implementation *
|
|
*******************************************/
|
|
|
|
template <class T>
|
|
template <class NT>
|
|
const_value<NT> const_value<T>::rebind() const
|
|
{
|
|
return detail::const_value_rebinder<T, NT>::run(*this);
|
|
}
|
|
|
|
/*****************************
|
|
* fixed_xreducer_shape_type *
|
|
*****************************/
|
|
|
|
template <class S1, class S2>
|
|
struct fixed_xreducer_shape_type;
|
|
|
|
template <std::size_t... I, std::size_t... J>
|
|
struct fixed_xreducer_shape_type<fixed_shape<I...>, fixed_shape<J...>>
|
|
{
|
|
using type = typename detail::
|
|
fixed_xreducer_shape_type_impl<sizeof...(I) - 1, fixed_shape<I...>, fixed_shape<J...>, fixed_shape<>>::type;
|
|
};
|
|
|
|
// meta-function returning the shape type for an xreducer
|
|
template <class ST, class X, class O>
|
|
struct xreducer_shape_type
|
|
{
|
|
using type = promote_shape_t<ST, std::decay_t<X>>;
|
|
};
|
|
|
|
template <class I1, std::size_t N1, class I2, std::size_t N2>
|
|
struct xreducer_shape_type<std::array<I1, N1>, std::array<I2, N2>, std::true_type>
|
|
{
|
|
using type = std::array<I2, N1>;
|
|
};
|
|
|
|
template <class I1, std::size_t N1, class I2, std::size_t N2>
|
|
struct xreducer_shape_type<std::array<I1, N1>, std::array<I2, N2>, std::false_type>
|
|
{
|
|
using type = std::array<I2, N1 - N2>;
|
|
};
|
|
|
|
template <std::size_t... I, class I2, std::size_t N2>
|
|
struct xreducer_shape_type<fixed_shape<I...>, std::array<I2, N2>, std::false_type>
|
|
{
|
|
using type = std::conditional_t<sizeof...(I) == N2, fixed_shape<>, std::array<I2, sizeof...(I) - N2>>;
|
|
};
|
|
|
|
namespace detail
|
|
{
|
|
template <class S1, class S2>
|
|
struct ixconcat;
|
|
|
|
template <class T, T... I1, T... I2>
|
|
struct ixconcat<std::integer_sequence<T, I1...>, std::integer_sequence<T, I2...>>
|
|
{
|
|
using type = std::integer_sequence<T, I1..., I2...>;
|
|
};
|
|
|
|
template <class T, T X, std::size_t N>
|
|
struct repeat_integer_sequence
|
|
{
|
|
using type = typename ixconcat<
|
|
std::integer_sequence<T, X>,
|
|
typename repeat_integer_sequence<T, X, N - 1>::type>::type;
|
|
};
|
|
|
|
template <class T, T X>
|
|
struct repeat_integer_sequence<T, X, 0>
|
|
{
|
|
using type = std::integer_sequence<T>;
|
|
};
|
|
|
|
template <class T, T X>
|
|
struct repeat_integer_sequence<T, X, 2>
|
|
{
|
|
using type = std::integer_sequence<T, X, X>;
|
|
};
|
|
|
|
template <class T, T X>
|
|
struct repeat_integer_sequence<T, X, 1>
|
|
{
|
|
using type = std::integer_sequence<T, X>;
|
|
};
|
|
}
|
|
|
|
template <std::size_t... I, class I2, std::size_t N2>
|
|
struct xreducer_shape_type<fixed_shape<I...>, std::array<I2, N2>, std::true_type>
|
|
{
|
|
template <std::size_t... X>
|
|
static constexpr auto get_type(std::index_sequence<X...>)
|
|
{
|
|
return fixed_shape<X...>{};
|
|
}
|
|
|
|
// if all axes reduced
|
|
using type = std::conditional_t<
|
|
sizeof...(I) == N2,
|
|
decltype(get_type(typename detail::repeat_integer_sequence<std::size_t, std::size_t(1), N2>::type{})),
|
|
std::array<I2, sizeof...(I)>>;
|
|
};
|
|
|
|
// Note adding "A" to prevent compilation in case nothing else matches
|
|
template <std::size_t... I, std::size_t... J, class O>
|
|
struct xreducer_shape_type<fixed_shape<I...>, fixed_shape<J...>, O>
|
|
{
|
|
using type = typename fixed_xreducer_shape_type<fixed_shape<I...>, fixed_shape<J...>>::type;
|
|
};
|
|
|
|
namespace detail
|
|
{
|
|
template <class S, class E, class X, class M>
|
|
inline void shape_and_mapping_computation(S& shape, E& e, const X& axes, M& mapping, std::false_type)
|
|
{
|
|
auto first = e.shape().begin();
|
|
auto last = e.shape().end();
|
|
auto exclude_it = axes.begin();
|
|
|
|
using value_type = typename S::value_type;
|
|
using difference_type = typename S::difference_type;
|
|
auto d_first = shape.begin();
|
|
auto map_first = mapping.begin();
|
|
|
|
auto iter = first;
|
|
while (iter != last && exclude_it != axes.end())
|
|
{
|
|
auto diff = std::distance(first, iter);
|
|
if (diff != difference_type(*exclude_it))
|
|
{
|
|
*d_first++ = *iter++;
|
|
*map_first++ = value_type(diff);
|
|
}
|
|
else
|
|
{
|
|
++iter;
|
|
++exclude_it;
|
|
}
|
|
}
|
|
|
|
auto diff = std::distance(first, iter);
|
|
auto end = std::distance(iter, last);
|
|
std::iota(map_first, map_first + end, diff);
|
|
std::copy(iter, last, d_first);
|
|
}
|
|
|
|
template <class S, class E, class X, class M>
|
|
inline void
|
|
shape_and_mapping_computation_keep_dim(S& shape, E& e, const X& axes, M& mapping, std::false_type)
|
|
{
|
|
for (std::size_t i = 0; i < e.dimension(); ++i)
|
|
{
|
|
if (std::find(axes.cbegin(), axes.cend(), i) == axes.cend())
|
|
{
|
|
// i not in axes!
|
|
shape[i] = e.shape()[i];
|
|
}
|
|
else
|
|
{
|
|
shape[i] = 1;
|
|
}
|
|
}
|
|
std::iota(mapping.begin(), mapping.end(), 0);
|
|
}
|
|
|
|
template <class S, class E, class X, class M>
|
|
inline void shape_and_mapping_computation(S&, E&, const X&, M&, std::true_type)
|
|
{
|
|
}
|
|
|
|
template <class S, class E, class X, class M>
|
|
inline void shape_and_mapping_computation_keep_dim(S&, E&, const X&, M&, std::true_type)
|
|
{
|
|
}
|
|
}
|
|
|
|
/***************************
|
|
* xreducer implementation *
|
|
***************************/
|
|
|
|
/**
|
|
* @name Constructor
|
|
*/
|
|
//@{
|
|
/**
|
|
* Constructs an xreducer expression applying the specified
|
|
* function to the given expression over the given axes.
|
|
*
|
|
* @param func the function to apply
|
|
* @param e the expression to reduce
|
|
* @param axes the axes along which the reduction is performed
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
template <class Func, class CTA, class AX, class OX>
|
|
inline xreducer<F, CT, X, O>::xreducer(Func&& func, CTA&& e, AX&& axes, OX&& options)
|
|
: m_e(std::forward<CTA>(e))
|
|
, m_reduce(xt::get<0>(func))
|
|
, m_init(xt::get<1>(func))
|
|
, m_merge(xt::get<2>(func))
|
|
, m_axes(std::forward<AX>(axes))
|
|
, m_shape(xtl::make_sequence<inner_shape_type>(
|
|
typename O::keep_dims() ? m_e.dimension() : m_e.dimension() - m_axes.size(),
|
|
0
|
|
))
|
|
, m_dim_mapping(xtl::make_sequence<dim_mapping_type>(
|
|
typename O::keep_dims() ? m_e.dimension() : m_e.dimension() - m_axes.size(),
|
|
0
|
|
))
|
|
, m_options(std::forward<OX>(options))
|
|
{
|
|
// std::less is used, because as the standard says (24.4.5):
|
|
// A sequence is sorted with respect to a comparator comp if for any iterator i pointing to the
|
|
// sequence and any non-negative integer n such that i + n is a valid iterator pointing to an element
|
|
// of the sequence, comp(*(i + n), *i) == false. Therefore less is required to detect duplicates.
|
|
if (!std::is_sorted(m_axes.cbegin(), m_axes.cend(), std::less<>()))
|
|
{
|
|
XTENSOR_THROW(std::runtime_error, "Reducing axes should be sorted.");
|
|
}
|
|
if (std::adjacent_find(m_axes.cbegin(), m_axes.cend()) != m_axes.cend())
|
|
{
|
|
XTENSOR_THROW(std::runtime_error, "Reducing axes should not contain duplicates.");
|
|
}
|
|
if (m_axes.size() != 0 && m_axes[m_axes.size() - 1] > m_e.dimension() - 1)
|
|
{
|
|
XTENSOR_THROW(
|
|
std::runtime_error,
|
|
"Axis " + std::to_string(m_axes[m_axes.size() - 1]) + " out of bounds for reduction."
|
|
);
|
|
}
|
|
|
|
if (!typename O::keep_dims())
|
|
{
|
|
detail::shape_and_mapping_computation(
|
|
m_shape,
|
|
m_e,
|
|
m_axes,
|
|
m_dim_mapping,
|
|
detail::is_fixed<shape_type>{}
|
|
);
|
|
}
|
|
else
|
|
{
|
|
detail::shape_and_mapping_computation_keep_dim(
|
|
m_shape,
|
|
m_e,
|
|
m_axes,
|
|
m_dim_mapping,
|
|
detail::is_fixed<shape_type>{}
|
|
);
|
|
}
|
|
}
|
|
|
|
//@}
|
|
|
|
/**
|
|
* @name Size and shape
|
|
*/
|
|
|
|
/**
|
|
* Returns the shape of the expression.
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer<F, CT, X, O>::shape() const noexcept -> const inner_shape_type&
|
|
{
|
|
return m_shape;
|
|
}
|
|
|
|
/**
|
|
* Returns the shape of the expression.
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
inline layout_type xreducer<F, CT, X, O>::layout() const noexcept
|
|
{
|
|
return static_layout;
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline bool xreducer<F, CT, X, O>::is_contiguous() const noexcept
|
|
{
|
|
return false;
|
|
}
|
|
|
|
//@}
|
|
|
|
/**
|
|
* @name Data
|
|
*/
|
|
|
|
/**
|
|
* Returns a constant reference to the element at the specified position in the reducer.
|
|
* @param args a list of indices specifying the position in the reducer. Indices
|
|
* must be unsigned integers, the number of indices should be equal or greater than
|
|
* the number of dimensions of the reducer.
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
template <class... Args>
|
|
inline auto xreducer<F, CT, X, O>::operator()(Args... args) const -> const_reference
|
|
{
|
|
XTENSOR_TRY(check_index(shape(), args...));
|
|
XTENSOR_CHECK_DIMENSION(shape(), args...);
|
|
std::array<std::size_t, sizeof...(Args)> arg_array = {{static_cast<std::size_t>(args)...}};
|
|
return element(arg_array.cbegin(), arg_array.cend());
|
|
}
|
|
|
|
/**
|
|
* Returns a constant reference to the element at the specified position in the reducer.
|
|
* @param args a list of indices specifying the position in the reducer. Indices
|
|
* must be unsigned integers, the number of indices must be equal to the number of
|
|
* dimensions of the reducer, else the behavior is undefined.
|
|
*
|
|
* @warning This method is meant for performance, for expressions with a dynamic
|
|
* number of dimensions (i.e. not known at compile time). Since it may have
|
|
* undefined behavior (see parameters), operator() should be preferred whenever
|
|
* it is possible.
|
|
* @warning This method is NOT compatible with broadcasting, meaning the following
|
|
* code has undefined behavior:
|
|
* @code{.cpp}
|
|
* xt::xarray<double> a = {{0, 1}, {2, 3}};
|
|
* xt::xarray<double> b = {0, 1};
|
|
* auto fd = a + b;
|
|
* double res = fd.uncheked(0, 1);
|
|
* @endcode
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
template <class... Args>
|
|
inline auto xreducer<F, CT, X, O>::unchecked(Args... args) const -> const_reference
|
|
{
|
|
std::array<std::size_t, sizeof...(Args)> arg_array = {{static_cast<std::size_t>(args)...}};
|
|
return element(arg_array.cbegin(), arg_array.cend());
|
|
}
|
|
|
|
/**
|
|
* Returns a constant reference to the element at the specified position in the reducer.
|
|
* @param first iterator starting the sequence of indices
|
|
* @param last iterator ending the sequence of indices
|
|
* The number of indices in the sequence should be equal to or greater
|
|
* than the number of dimensions of the reducer.
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
template <class It>
|
|
inline auto xreducer<F, CT, X, O>::element(It first, It last) const -> const_reference
|
|
{
|
|
XTENSOR_TRY(check_element_index(shape(), first, last));
|
|
auto stepper = const_stepper(*this, 0);
|
|
if (first != last)
|
|
{
|
|
size_type dim = 0;
|
|
// drop left most elements
|
|
auto size = std::ptrdiff_t(this->dimension()) - std::distance(first, last);
|
|
auto begin = first - size;
|
|
while (begin != last)
|
|
{
|
|
if (begin < first)
|
|
{
|
|
stepper.step(dim++, std::size_t(0));
|
|
begin++;
|
|
}
|
|
else
|
|
{
|
|
stepper.step(dim++, std::size_t(*begin++));
|
|
}
|
|
}
|
|
}
|
|
return *stepper;
|
|
}
|
|
|
|
/**
|
|
* Returns a constant reference to the underlying expression of the reducer.
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer<F, CT, X, O>::expression() const noexcept -> const xexpression_type&
|
|
{
|
|
return m_e;
|
|
}
|
|
|
|
//@}
|
|
|
|
/**
|
|
* @name Broadcasting
|
|
*/
|
|
//@{
|
|
/**
|
|
* Broadcast the shape of the reducer to the specified parameter.
|
|
* @param shape the result shape
|
|
* @param reuse_cache parameter for internal optimization
|
|
* @return a boolean indicating whether the broadcasting is trivial
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
template <class S>
|
|
inline bool xreducer<F, CT, X, O>::broadcast_shape(S& shape, bool) const
|
|
{
|
|
return xt::broadcast_shape(m_shape, shape);
|
|
}
|
|
|
|
/**
|
|
* Checks whether the xreducer can be linearly assigned to an expression
|
|
* with the specified strides.
|
|
* @return a boolean indicating whether a linear assign is possible
|
|
*/
|
|
template <class F, class CT, class X, class O>
|
|
template <class S>
|
|
inline bool xreducer<F, CT, X, O>::has_linear_assign(const S& /*strides*/) const noexcept
|
|
{
|
|
return false;
|
|
}
|
|
|
|
//@}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
template <class S>
|
|
inline auto xreducer<F, CT, X, O>::stepper_begin(const S& shape) const noexcept -> const_stepper
|
|
{
|
|
size_type offset = shape.size() - this->dimension();
|
|
return const_stepper(*this, offset);
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
template <class S>
|
|
inline auto xreducer<F, CT, X, O>::stepper_end(const S& shape, layout_type l) const noexcept
|
|
-> const_stepper
|
|
{
|
|
size_type offset = shape.size() - this->dimension();
|
|
return const_stepper(*this, offset, true, l);
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
template <class E>
|
|
inline auto xreducer<F, CT, X, O>::build_reducer(E&& e) const -> rebind_t<E>
|
|
{
|
|
return rebind_t<E>(
|
|
std::make_tuple(m_reduce, m_init, m_merge),
|
|
std::forward<E>(e),
|
|
axes_type(m_axes),
|
|
m_options
|
|
);
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
template <class E, class Func, class Opts>
|
|
inline auto xreducer<F, CT, X, O>::build_reducer(E&& e, Func&& func, Opts&& opts) const
|
|
-> rebind_t<E, Func, Opts>
|
|
{
|
|
return rebind_t<E, Func, Opts>(
|
|
std::forward<Func>(func),
|
|
std::forward<E>(e),
|
|
axes_type(m_axes),
|
|
std::forward<Opts>(opts)
|
|
);
|
|
}
|
|
|
|
/***********************************
|
|
* xreducer_stepper implementation *
|
|
***********************************/
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline xreducer_stepper<F, CT, X, O>::xreducer_stepper(
|
|
const xreducer_type& red,
|
|
size_type offset,
|
|
bool end,
|
|
layout_type l
|
|
)
|
|
: m_reducer(&red)
|
|
, m_offset(offset)
|
|
, m_stepper(get_substepper_begin())
|
|
{
|
|
if (end)
|
|
{
|
|
to_end(l);
|
|
}
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::operator*() const -> reference
|
|
{
|
|
reference r = aggregate(0);
|
|
return r;
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::step(size_type dim)
|
|
{
|
|
if (dim >= m_offset)
|
|
{
|
|
m_stepper.step(get_dim(dim - m_offset));
|
|
}
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::step_back(size_type dim)
|
|
{
|
|
if (dim >= m_offset)
|
|
{
|
|
m_stepper.step_back(get_dim(dim - m_offset));
|
|
}
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::step(size_type dim, size_type n)
|
|
{
|
|
if (dim >= m_offset)
|
|
{
|
|
m_stepper.step(get_dim(dim - m_offset), n);
|
|
}
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::step_back(size_type dim, size_type n)
|
|
{
|
|
if (dim >= m_offset)
|
|
{
|
|
m_stepper.step_back(get_dim(dim - m_offset), n);
|
|
}
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::reset(size_type dim)
|
|
{
|
|
if (dim >= m_offset)
|
|
{
|
|
// Because the reducer uses `reset` to reset the non-reducing axes,
|
|
// we need to prevent that here for the KD case where.
|
|
if (typename O::keep_dims()
|
|
&& std::binary_search(m_reducer->m_axes.begin(), m_reducer->m_axes.end(), dim - m_offset))
|
|
{
|
|
// If keep dim activated, and dim is in the axes, do nothing!
|
|
return;
|
|
}
|
|
m_stepper.reset(get_dim(dim - m_offset));
|
|
}
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::reset_back(size_type dim)
|
|
{
|
|
if (dim >= m_offset)
|
|
{
|
|
// Note that for *not* KD this is not going to do anything
|
|
if (typename O::keep_dims()
|
|
&& std::binary_search(m_reducer->m_axes.begin(), m_reducer->m_axes.end(), dim - m_offset))
|
|
{
|
|
// If keep dim activated, and dim is in the axes, do nothing!
|
|
return;
|
|
}
|
|
m_stepper.reset_back(get_dim(dim - m_offset));
|
|
}
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::to_begin()
|
|
{
|
|
m_stepper.to_begin();
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline void xreducer_stepper<F, CT, X, O>::to_end(layout_type l)
|
|
{
|
|
m_stepper.to_end(l);
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::initial_value() const -> reference
|
|
{
|
|
return O::has_initial_value ? m_reducer->m_options.initial_value
|
|
: static_cast<reference>(m_reducer->m_init());
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::aggregate(size_type dim) const -> reference
|
|
{
|
|
reference res;
|
|
if (m_reducer->m_e.size() == size_type(0))
|
|
{
|
|
res = initial_value();
|
|
}
|
|
else if (m_reducer->m_e.shape().empty() || m_reducer->m_axes.size() == 0)
|
|
{
|
|
res = m_reducer->m_reduce(initial_value(), *m_stepper);
|
|
}
|
|
else
|
|
{
|
|
res = aggregate_impl(dim, typename O::keep_dims());
|
|
if (O::has_initial_value && dim == 0)
|
|
{
|
|
res = m_reducer->m_merge(m_reducer->m_options.initial_value, res);
|
|
}
|
|
}
|
|
return res;
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::aggregate_impl(size_type dim, std::false_type) const -> reference
|
|
{
|
|
// reference can be std::array, hence the {} initializer
|
|
reference res = {};
|
|
size_type index = axis(dim);
|
|
size_type size = shape(index);
|
|
if (dim != m_reducer->m_axes.size() - 1)
|
|
{
|
|
res = aggregate_impl(dim + 1, typename O::keep_dims());
|
|
for (size_type i = 1; i != size; ++i)
|
|
{
|
|
m_stepper.step(index);
|
|
res = m_reducer->m_merge(res, aggregate_impl(dim + 1, typename O::keep_dims()));
|
|
}
|
|
}
|
|
else
|
|
{
|
|
res = m_reducer->m_reduce(static_cast<reference>(m_reducer->m_init()), *m_stepper);
|
|
for (size_type i = 1; i != size; ++i)
|
|
{
|
|
m_stepper.step(index);
|
|
res = m_reducer->m_reduce(res, *m_stepper);
|
|
}
|
|
}
|
|
m_stepper.reset(index);
|
|
return res;
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::aggregate_impl(size_type dim, std::true_type) const -> reference
|
|
{
|
|
// reference can be std::array, hence the {} initializer
|
|
reference res = {};
|
|
auto ax_it = std::find(m_reducer->m_axes.begin(), m_reducer->m_axes.end(), dim);
|
|
if (ax_it != m_reducer->m_axes.end())
|
|
{
|
|
size_type index = dim;
|
|
size_type size = m_reducer->m_e.shape()[index];
|
|
if (ax_it != m_reducer->m_axes.end() - 1 && size != 0)
|
|
{
|
|
res = aggregate_impl(dim + 1, typename O::keep_dims());
|
|
for (size_type i = 1; i != size; ++i)
|
|
{
|
|
m_stepper.step(index);
|
|
res = m_reducer->m_merge(res, aggregate_impl(dim + 1, typename O::keep_dims()));
|
|
}
|
|
}
|
|
else
|
|
{
|
|
res = m_reducer->m_reduce(static_cast<reference>(m_reducer->m_init()), *m_stepper);
|
|
for (size_type i = 1; i != size; ++i)
|
|
{
|
|
m_stepper.step(index);
|
|
res = m_reducer->m_reduce(res, *m_stepper);
|
|
}
|
|
}
|
|
m_stepper.reset(index);
|
|
}
|
|
else
|
|
{
|
|
if (dim < m_reducer->m_e.dimension())
|
|
{
|
|
res = aggregate_impl(dim + 1, typename O::keep_dims());
|
|
}
|
|
}
|
|
return res;
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::get_substepper_begin() const -> substepper_type
|
|
{
|
|
return m_reducer->m_e.stepper_begin(m_reducer->m_e.shape());
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::get_dim(size_type dim) const noexcept -> size_type
|
|
{
|
|
return m_reducer->m_dim_mapping[dim];
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::shape(size_type i) const noexcept -> size_type
|
|
{
|
|
return m_reducer->m_e.shape()[i];
|
|
}
|
|
|
|
template <class F, class CT, class X, class O>
|
|
inline auto xreducer_stepper<F, CT, X, O>::axis(size_type i) const noexcept -> size_type
|
|
{
|
|
return m_reducer->m_axes[i];
|
|
}
|
|
}
|
|
|
|
#endif
|