#ifndef MIGRAPHX_GUARD_OPERATORS_ARGMIN_HPP
#define MIGRAPHX_GUARD_OPERATORS_ARGMIN_HPP

#include <migraphx/check_shapes.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/functional.hpp>
#include <migraphx/par_for.hpp>
#include <migraphx/config.hpp>
#include <migraphx/value.hpp>
#include <migraphx/op/normalize_attribute.hpp>

namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace op {

struct argmin
{
    int64_t axis = 0;

    template <class Self, class F>
    static auto reflect(Self& self, F f)
    {
        return pack(f(self.axis, "axis"));
    }

    value attributes() const
    {
        value normalize;
        normalize["axis"] = value::array{normalize_attribute::include_min};
        return {{"normalize_axes", normalize}};
    }

    std::string name() const { return "argmin"; }

    shape normalize_compute_shape(std::vector<shape> inputs) const
    {
        check_shapes{inputs, *this}.has(1).standard();
        auto lens     = inputs[0].lens();
        int64_t n_dim = static_cast<int64_t>(lens.size());
        if(axis >= n_dim || axis < 0)
        {
            MIGRAPHX_THROW("ARGMIN: axis is out of range.");
        }

        int64_t tuned_axis = (axis < 0) ? axis + n_dim : axis;
        lens[tuned_axis]   = 1;

        return {shape::int64_type, lens};
    }

    template <class T>
    int64_t calc_argmin(T& input,
                        int64_t tuned_axis,
                        std::vector<std::size_t>& indices,
                        size_t item_num) const
    {
        auto min_val      = input(indices.begin(), indices.end());
        int64_t min_index = 0;
        for(std::size_t i = 1; i < item_num; ++i)
        {
            indices[tuned_axis] = i;
            auto cur_val        = input(indices.begin(), indices.end());
            if(min_val > cur_val)
            {
                min_val   = cur_val;
                min_index = i;
            }
        }

        return min_index;
    }

    argument compute(const shape& output_shape, std::vector<argument> args) const
    {
        argument result{output_shape};
        auto n_dim                 = args.front().get_shape().lens().size();
        auto tuned_axis            = axis < 0 ? axis + n_dim : axis;
        std::size_t batch_item_num = args.front().get_shape().lens()[tuned_axis];

        result.visit([&](auto output) {
            args[0].visit([&](auto input) {
                par_for(output_shape.elements(), [&](auto i) {
                    auto data_idx = output_shape.multi(i);
                    output[i]     = this->calc_argmin(input, tuned_axis, data_idx, batch_item_num);
                });
            });
        });

        return result;
    }
};

} // namespace op
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx

#endif
