fully_connected.hpp

/*
// 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 "../C/fully_connected.h"
#include "primitive.hpp"

namespace cldnn
{



struct fully_connected : public primitive_base<fully_connected, CLDNN_PRIMITIVE_DESC(fully_connected)>
{
    CLDNN_DECLATE_PRIMITIVE(fully_connected)

    
    fully_connected(
        const primitive_id& id,
        const primitive_id& input,
        const primitive_id& weights,
        const primitive_id& bias = "",
        bool with_activation = false,
        float activation_slp = 0.0f,
        const padding& output_padding = padding()
        )
        : primitive_base(id, {input}, output_padding)
        , weights(weights)
        , bias(bias)
        , with_activation(with_activation)
        , activation_negative_slope(activation_slp)
    {
    }

    fully_connected(const dto* dto)
        :primitive_base(dto)
        , weights(dto->weights)
        , bias(dto->bias)
        , with_activation(dto->with_activation != 0)
        , activation_negative_slope(dto->activation_negative_slope)
    {
    }

    primitive_id weights;
    primitive_id bias;
    bool with_activation;
    float activation_negative_slope;

protected:
    std::vector<std::reference_wrapper<const primitive_id>> get_dependencies() const override 
    {
        if (bias.empty())
            return{ weights };
        else
            return{ weights, bias }; 
    }

    void update_dto(dto& dto) const override
    {
        dto.weights = weights.c_str();
        dto.bias = bias.c_str();
        dto.with_activation = with_activation;
        dto.activation_negative_slope = activation_negative_slope;
    }
};
}