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# to you under the Apache License, Version 2.0 (the
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#
#   http://www.apache.org/licenses/LICENSE-2.0
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package AI::MXNet::Gluon::ModelZoo::Vision::DenseNet;
use strict;
use warnings;
use AI::MXNet::Base;
use AI::MXNet::Function::Parameters;
use AI::MXNet::Gluon::Mouse;
extends 'AI::MXNet::Gluon::HybridBlock';

func _make_dense_block($num_layers, $bn_size, $growth_rate, $dropout, $stage_index)
{
    my $out = nn->HybridSequential(prefix=>"stage${stage_index}_");
    $out->name_scope(sub {
        for(1..$num_layers)
        {
            $out->add(_make_dense_layer($growth_rate, $bn_size, $dropout));
        }
    });
    return $out;
}

func _make_dense_layer($growth_rate, $bn_size, $dropout)
{
    my $new_features = nn->HybridSequential(prefix=>'');
    $new_features->add(nn->BatchNorm());
    $new_features->add(nn->Activation('relu'));
    $new_features->add(nn->Conv2D($bn_size * $growth_rate, kernel_size=>1, use_bias=>0));
    $new_features->add(nn->BatchNorm());
    $new_features->add(nn->Activation('relu'));
    $new_features->add(nn->Conv2D($growth_rate, kernel_size=>3, padding=>1, use_bias=>0));
    if($dropout)
    {
        $new_features->add(nn->Dropout($dropout));
    }

    my $out = nn->HybridConcurrent(axis=>1, prefix=>'');
    $out->add(nn->Identity());
    $out->add($new_features);

    return $out;
}

func _make_transition($num_output_features)
{
    my $out = nn->HybridSequential(prefix=>'');
    $out->add(nn->BatchNorm());
    $out->add(nn->Activation('relu'));
    $out->add(nn->Conv2D($num_output_features, kernel_size=>1, use_bias=>0));