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

#pragma once

#include "intel_gpu/graph/serialization/binary_buffer.hpp"
#include "intel_gpu/runtime/engine.hpp"
#include "intel_gpu/runtime/memory.hpp"
#include "intel_gpu/runtime/stream.hpp"
#include "intel_gpu/runtime/utils.hpp"
#include "intel_gpu/runtime/tensor.hpp"
#include "intel_gpu/primitives/primitive.hpp"

#include "intel_gpu/graph/fused_primitive_desc.hpp"

#include <cstdint>
#include <string>
#include <vector>
#include <memory>

namespace cldnn {

struct program;
struct network;


struct ExecutionFlags : public std::bitset<5> {
    static const size_t SHAPE_CHANGED = 0;
    static const size_t IMPL_CHANGED = 1;
    static const size_t MEMORY_CHANGED = 2;
    static const size_t ARG_UPDATE_REQUIRED = 3;
    static const size_t SKIP = 4;
};

struct kernel_impl_params final {
    struct Hasher {
        size_t operator()(const kernel_impl_params &k) const {
            return k.hash();
        }
    };

    const program *prog;
    cldnn::device_type dev_type;
    stream::ptr strm;
    std::shared_ptr<const primitive> desc;
    size_t unique_id;
    bool _can_be_optimized = false;
    bool _runtime_skippable = false;
    std::vector<layout> input_layouts;
    std::vector<layout> output_layouts;
    std::vector<tensor> input_offsets;
    std::vector<cldnn::fused_primitive_desc> fused_desc;
#ifdef ENABLE_ONEDNN_FOR_GPU
    std::vector<cldnn::fused_primitive_desc_onednn> fused_desc_onednn;
    std::shared_ptr<dnnl::primitive_attr> attrs_onednn;
#endif // ENABLE_ONEDNN_FOR_GPU

    std::vector<event::ptr> dep_events = {};
    event::ptr out_event = nullptr;

    ExecutionFlags flags;

    optional_layout weights_layout = optional_layout();

    optional_layout bias_layout = optional_layout();
    optional_layout weights_zero_points_layout = optional_layout();
    optional_layout activations_zero_points_layout = optional_layout();
    optional_layout compensation_layout = optional_layout();
    std::vector<layout> state_layouts;

    std::map<size_t, memory::ptr> memory_deps = {};
    size_t primary_input_idx = 0;
    std::vector<std::shared_ptr<program>> inner_progs = {};
    std::vector<std::shared_ptr<network>> inner_nets = {};
    std::vector<std::map<size_t, primitive_id>> io_output_maps = {};
    // TODO : These values are temporarily added for prior box.
    // Such values decided at runtime shape infer and primitive creation will be handled with more generalized way in the near future.
    std::vector<size_t> output_size;
    std::vector<size_t> img_size;

    std::map<size_t, size_t> in_port_to_shape_info_offset = {};
    std::map<size_t, size_t> out_port_to_shape_info_offset = {};

    kernel_impl_params() : prog(nullptr), dev_type(cldnn::device_type::integrated_gpu), strm(nullptr), desc(nullptr), unique_id(0) {
    }

    kernel_impl_params(program& _prog,
                       cldnn::device_type _dev_type,
                       stream::ptr _strm,
                       std::shared_ptr<const primitive> _desc,
                       size_t _uid,
                       const std::vector<layout>& _in_layouts,
                       const std::vector<layout>& _out_layouts,
                       const std::vector<cldnn::fused_primitive_desc>& _fused_descs)
                       : prog(&_prog)
                       , dev_type(_dev_type)
                       , strm(std::move(_strm))
                       , desc(std::move(_desc))
                       , unique_id(_uid)
                       , input_layouts(_in_layouts)
                       , output_layouts(_out_layouts)
                       , fused_desc(_fused_descs)
                       , primary_input_idx(0) {
    }

    ~kernel_impl_params() = default;

    const layout& get_input_layout(size_t idx = 0) const {
        OPENVINO_ASSERT(input_layouts.size() > idx,
                        "The size of input layouts must be greater than the requested index: ",
                        "Requested index is ", idx, ", ",
                        "but the size of input layouts is ", input_layouts.size());
        return input_layouts[idx];
    }

    layout get_non_padded_input_layout(size_t idx = 0) const {
        auto input_layout = get_input_layout(idx);
        auto result = layout({input_layout.get_partial_shape(), input_layout.data_type, input_layout.format});
        return result;
    }

    const layout& get_output_layout(size_t idx = 0) const {
        OPENVINO_ASSERT(output_layouts.size() > idx,
                        "The size of output layouts must be greater than the requested index: ",
                        "Requested index is ", idx, ", ",
                        "but the size of output layouts is ", output_layouts.size());
        return output_layouts[idx];
    }

    layout& get_output_layout(size_t idx = 0) {
        OPENVINO_ASSERT(output_layouts.size() > idx,
                        "The size of output layouts must be greater than the requested index: ",
                        "Requested index is ", idx, ", ",
                        "but the size of output layouts is ", output_layouts.size());
        return output_layouts[idx];
    }

    size_t get_input_layout_size() const {
        return input_layouts.size();
    }

    bool has_fused_primitives() const { return !fused_desc.empty(); }

    ov::element::Type_t get_output_element_type() const {
        if (fused_desc.empty())
            return output_layouts[0].data_type;
        return fused_desc.back().output_layout.data_type;
    }

    bool is_dynamic() const {
        for (auto& i : input_layouts)
            if (i.is_dynamic())
                return true;
        for (auto& i : output_layouts)
            if (i.is_dynamic())
                return true;
        return false;
    }

    bool can_be_optimized() const {
        return _can_be_optimized;
    }

    bool runtime_skippable() const {
        return _runtime_skippable;
    }

    template <class PType>
    std::shared_ptr<const PType> typed_desc() const { return std::static_pointer_cast<const PType>(desc); }

    template <class PType>
    bool is_type() const {
        return std::static_pointer_cast<const PType>(desc)->type == PType::type_id();
    }

    const program& get_program() const {
        OPENVINO_ASSERT(prog != nullptr, "[GPU] Program pointer in kernel_impl_params is not initialized");
        return *prog;
    }

    const device_info& get_device_info() const;

    stream& get_stream() const { return *strm; }
    stream::ptr get_stream_ptr() const { return strm; }

    size_t hash() const;
    bool operator==(const kernel_impl_params& rhs) const;
};

}  // namespace cldnn

namespace ov::intel_gpu {
using RuntimeParams = cldnn::kernel_impl_params;
}  // namespace ov::intel_gpu
