dnn_layer_input.h

Go to the documentation of this file.

// Copyright 2019 Claes Rolen (www.rolensystems.com)
//
//   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
namespace dnn
{

class layer_input: public layer
{
private:
    const arma::Mat<DNN_Dtype>* data_in;    
    arma::uword data_len;                   
    arma::uword data_ctr;                   
public:
    layer_input(const arma::uword n_rows, const arma::uword n_cols=1, const arma::uword n_channels=1):layer()
    {
        N_rows_right     = n_rows;
        N_cols_right     = n_cols;
        N_channels_right = n_channels;
        N_right          = N_cols_right*N_rows_right*N_channels_right;
        type             = "Input";
        id               = type;
    }

    void init(void)
    {
        N_left           = 0;
        N_cols_left      = 0;
        N_rows_left      = 0;
        N_channels_left  = 0;
        data_len         = 0;
        data_ctr         = 0;
    }

    void set_data(const arma::Mat<DNN_Dtype>* data)
    {
        data_in  = data;
        data_len = data->n_cols;
        data_ctr = 0;
    }

    void reset_batch_ctr(void)
    {
        data_ctr = 0;
    }

    void prop(void)
    {
        Y1 = data_in->col(data_ctr++);
        if(data_ctr == data_len)
            data_ctr = 0; // Wrap data
    }

    void prop_mb(void)
    {
        if( (data_ctr+N_batch)>=data_len )
        {
            // We are at the end, wrap data
            for (arma::uword k=0 ; k<N_batch ; k++ )
            {
                Y.col(k) = data_in->col(data_ctr++);
                if(data_ctr >= data_len)
                    data_ctr = 0; // Wrap data
            }
        }
        else
        {
            Y = data_in->cols(data_ctr,data_ctr+N_batch-1);
            data_ctr+=N_batch;
        }
    }

    void disp(void)
    {
        layer::disp();
        std::cout << "Output data length:   " << get_nrof_outputs() << " ["<< N_rows_right << ","<<N_cols_right<<","<< N_channels_right<<"]"<< std::endl;
    }

}; // End class layer_input
} // End namespace dnn