/*
// Copyright (c) 2016 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
*/

///////////////////////////////////////////////////////////////////////////////////////////////////
#pragma once
#include "api/CPP/deconvolution.hpp"
#include "primitive_inst.h"

namespace cldnn
{

template <>
struct typed_program_node<deconvolution> : public typed_program_node_base<deconvolution>
{
    using parent = typed_program_node_base<deconvolution>;

public:
    typed_program_node(std::shared_ptr<primitive> prim, program_impl& prog)
        : parent(prim, prog)
        , split(this->get_primitive()->split())
        , depthwise_sep_opt(false)
        , groups(this->get_primitive()->groups)
    {
        support_padding(true);
    }

    
    void set_split(int32_t node_split) { split = node_split; }
    int32_t get_split() const { return split; }

    void set_depthwise_sep_opt(bool node_depthwise_sep_opt) { depthwise_sep_opt = node_depthwise_sep_opt; }
    bool get_depthwise_sep_opt() const { return depthwise_sep_opt; }

    void set_groups(uint32_t node_groups) { groups = node_groups; }
    uint32_t get_groups() const { return groups; }

    program_node& input() const { return get_dependency(0); }

    program_node& weights(size_t idx = 0) const
    {
        if (static_cast<int32_t>(idx) >= get_split())
            throw std::range_error("weights offset too big");

        return get_dependency(1 + idx);
    }

    program_node& bias(size_t idx = 0) const
    { 
        if (static_cast<int32_t>(idx) >= get_split())
            throw std::range_error("bias offset too big");

        return get_dependency(1 + this->get_split() + idx);
    }

    bool bias_term() const
    {
        if (get_primitive()->bias.size() != 0)
            return true;
        else
            return false;
    }

    program_node& fused_sum(size_t idx = 0) const
    {
        if (static_cast<int32_t>(idx) > 0)
            throw std::range_error("Only one input for fused sum is supported");

        size_t d_idx = 1 + this->get_split() + idx;
        d_idx += bias_term() ? this->get_split() : 0;
        return get_dependency(d_idx);
    }

    bool has_fused_sum() const
    {
        size_t d_idx = 1 + this->get_split();
        d_idx += bias_term() ? this->get_split() : 0;
        return dependencies.size() == (d_idx + 1);
    }

private:
    int32_t split;
    bool depthwise_sep_opt;
    uint32_t groups;
};

using deconvolution_node = typed_program_node<deconvolution>;

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

public:
    static layout calc_output_layout(deconvolution_node const& node);
    static std::string to_string(deconvolution_node const& node);

public:
    typed_primitive_inst(network_impl& network, deconvolution_node const& node);

    memory_impl& weights_memory(size_t index) const
    {
        if (node.get_groups() == 1) {
            if (static_cast<int32_t>(index) >= node.get_split())
                throw std::range_error("weights offset too big");
            return dep_memory(1 + index);
        }
        else { // all weights are in one buffer
            return dep_memory(1);
        }
    }

    memory_impl& bias_memory(size_t index) const
    {
        if (node.get_groups() == 1) {
            if (argument.bias.size() == 0 && static_cast<int32_t>(index) >= node.get_split())
                throw std::range_error("no bias data");
            if (static_cast<int32_t>(index) > node.get_split())
                throw std::range_error("bias offset too big");
            return dep_memory(1 + node.get_split() + index);
        }
        else { // all bias are in one buffer
            return dep_memory(2);
        }
    }

    bool bias_term() const
    {
        if (argument.bias.size() != 0)
            return true;
        else
            return false;
    }
};

using deconvolution_inst = typed_primitive_inst<deconvolution>;

}
