// Copyright (C) 2018-2026 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

#pragma once
#include "intel_gpu/primitives/fully_connected.hpp"
#include "primitive_inst.h"
#include "data_inst.h"

#include <string>
#include <memory>

namespace cldnn {
template <>
struct typed_program_node<fully_connected> : public typed_program_node_base<fully_connected> {
    using parent = typed_program_node_base<fully_connected>;

public:
    typed_program_node(std::shared_ptr<primitive> prim, program& prog)
        : parent(prim, prog) {}

    program_node& input() const { return get_dependency(0); }
    program_node& weights() const { return get_dependency(1); }
    program_node& bias() const { return get_dependency(2); }
    bool bias_term() const { return get_primitive()->bias.is_valid(); }

    std::vector<size_t> get_shape_infer_dependencies() const override { return {}; }

    using parent::get_kernel_impl_params;
    std::unique_ptr<kernel_impl_params> get_kernel_impl_params(const std::vector<layout>& in_layouts, const std::vector<layout>& out_layouts) const override {
        auto params = parent::get_kernel_impl_params(in_layouts, out_layouts);
        params->weights_layout = optional_layout(weights().get_output_layout());
        if (bias_term())
            params->bias_layout = optional_layout(bias().get_output_layout());
        return params;
    }
};

using fully_connected_node = typed_program_node<fully_connected>;

template <>
class typed_primitive_inst<fully_connected> : public typed_primitive_inst_base<fully_connected> {
    using parent = typed_primitive_inst_base<fully_connected>;
    using parent::parent;

public:
    template<typename ShapeType>
    static std::vector<layout> calc_output_layouts(fully_connected_node const& /*node*/, const kernel_impl_params& impl_param);
    static layout calc_output_layout(fully_connected_node const& node, kernel_impl_params const& impl_param);
    static kernel_impl_params get_fake_aligned_params(kernel_impl_params const& orig_impl_param);
    static std::string to_string(fully_connected_node const& node);
    static bool can_apply_single_batch_optimization(const kernel_impl_params& impl_param);

    typed_primitive_inst(network& network, fully_connected_node const& node);

    memory::ptr weights_memory() const {
        if (is_dynamic()) {
            auto weights_mem = _reordered_weights_cache.get(*_impl_params->weights_layout);
            OPENVINO_ASSERT(weights_mem != nullptr, "[GPU] Can't find proper weights memory buffer in cache");
            return weights_mem;
        } else {
            return dep_memory_ptr(1);
        }
    }
    memory::ptr bias_memory() const { return dep_memory_ptr(2); }

    bool bias_term() const { return _impl_params->bias_layout.has_value(); }
};

using fully_connected_inst = typed_primitive_inst<fully_connected>;

}  // namespace cldnn
